While we're at it, will someone please show the Yale professors how to handle negative earnings so that they don't exclude these along with so many others that are not in the standard and poor earnings series he used, which used to report yearly six months after the end of the year if at all, perhaps using earnings price ratio?

Phil McDonnell writes: 

The use of PE ratios is very bad for historical studies. A simple mental experiment shows why. Suppose earnings result in a current PE ratio of 10. If earnings are cut in half the new PE will be 20, other things being equal. As earnings get smaller and smaller the PE rises to near infinity as earnngs approach zero.

When earnings go negative the PE suddenly flips from very large positive to negative. This causes the variable to go from a monotonic increasing to sudden negative.

At this point the Yale professor had no choice but to eliminate any such data.Using a slightly different variable of E/P eliminates the problem. It becomes a monotonic variable. When the E factor gets very small the E/P variable goes smaller. When E starts to go negative the variable goes negative with no loss of continuity. With this change there is no need to throw data out.



Big G, from anonymous

January 30, 2017 | 1 Comment

 I guess I'm oblivious of the goings-on in those 7 countries.

The map shows 7 really rotten (and now forbidden) apples, plus the 3 unaffected ones (whose citizens are more likely Western university educated):

"Google Tells Offshore Staff To Return To The US After Trump Executive Order"

How did the US hi tech sector manage to pick up all those enumerated in the story? And why would it rely on future inflow from exactly there?

Phil McDonnell writes:

A certain eponymous person was sent from the googleplex to Zurich to act as a liason to the home office software resources for all the many remote development offices. They had offices in all the major euro cities, muslim cities, Moscow, India, China and South Korea. Some offices were acquired when big G bought a software company like in Moscow. In china they built the local presence around a guru named Lee but it proved to be a disappointment and was closed.

The goal is two pronged. They want to attract world class talent and to maintain a presence in every country in the world. One has been to many lunches at the googleplex. In my estimation the majority of people there were not born in the US.

If one were to conclude that this is because Goog wants to take over the world I would respond that you are warm. You are just not thinking big enough. They simply wish to take over the universe.

anonymous writes:

Sounds like "Big G" is the IS (Information Services) strong-arm of Freemasonry. The new non-contingent being—one token ring to rule us all.



 I asked Brett one more time to quantify some of his multiple classifications and descriptions of cycles and advance declines et al and he responded: "Very nice quanatification of cycles with admirable transparancy of track record fromm @stockspotter. Brett is a Dr of great respect and is adverse to mumbo in all forms. But someone should look at stockspotter to see if it passes the usual scientific standards.

Phil McDonnell writes:

I first came across John Ehlers in the early 1990s. He and I traded his MESA program for my Option Trader software. MESA stands for Maximum Entropy Spectral Analysis. I had earlier written a Fast Fourier Transform (FFT) program which is similar to MESA. FFT constructs a set of multiple cycles over 32, 64 or 128 days to 'fit' the recent history of the market. The problem is that cycles evolve with time. MESA attempts to fix that by taking a shorter term average cycle than FFT.

My experience then was that the software seemed to have some promise but it was not perfect. It offered a look-ahead graph of where the market would go and that was how you picked potential winners.

A quick look at the site showed a track record of 'closed trades" for the last quarter of 2016. I glanced at the first 10 pages of trades. Out of this sub-sample of 140 trades very few were losers. On the face of it this seems to be a very successful system.

But there is a catch. The trade record shows only a few days (3-6) on the first page. But later pages show a clear trend of more days in a trade (~5-9) as it goes on. This may be evidence of some sort of 'first profitable close' exit strategy. Thus there may be a larger number of deferred losers hidden in the undisclosed current trades which were not revealed.

As it stands the data cannot really be analyzed scientifically. However that does not mean that there is not something interesting here.



Say that you have a yearly goal of 40% and you achieved in 7 months, or that you have a monthly goal of 10% and you achieved it in 11 days. Do you stop trading at this point? Or do you continue trading thinking the luck is on your side at the moment? Or do you adjust your goal and continue trading with the new goal?

Cheers, Leo

Victor Niederhoffer writes: 

The market will sometimes go much below your goal and to even things out you have to make as much as you can above your goal. Furthermore, the market doesn't care whether you've achieved your goal or not, it will always go its own way, and if you can make a profit on an expected future value basis, you should go for it. Luck is random, but the skill will persist. Apparently you or a colleague has it. Don't throw it out.

Andrew Goodwin writes: 

Your answer may rest in the structure of your money management operation. If it is a hedge fund structure, then heed the following points made in a post on the If you get behind you must know how you will deal with the moral hazard. Since you are ahead greatly, then your incentive is to take the money unless you know with some certainty that you cannot fall below a high watermark and will likely increase your gains.

1) The management fee, over time, usually does not generate enough income to operate and the profitable traders expect bonuses even when the overall fund loses.

2) The winning traders will leave to other firms or will start their own if there is no performance fee gathered to pay them.

3) If fund performance goes negative then high watermark provisions normally go into action. This can lead the manager to swing for the fences or simply close shop.

4) The wind down of the fund can deplete the investor assets and lead to general price markdowns of holdings especially if others had similar strategies and exposure.

5) The fleeing investors will enter into a new fund with a new high watermark and start the process over again.

Here is where the game gets interesting. The author suggests creating exotic option outcome provisions that he calls "Modified High Watermark."

These include A) Reset to zero under certain circumstances. B) Amortize the losses over a period so that the manager can still earn some incentive fee. C) Create a rolling period for the high watermark so that after a time the mark level drops.

His modified high watermark solutions might keep the manager from swinging when the performance fee looks too distant and might keep genuinely unlucky managers around until their skill manifests itself in due course.

Nigel Davies writes: 

There's a case for reducing leverage as one's account size increases so as to reduce the 'risk of ruin', and for some this might be done in a very systematic way. Another question is if there's a point at which one's financial goals have been achieved, especially if one's dreams lie elsewhere. 

Bill Rafter writes: 

You did not specify if your annual goal of 40 percent is based on analysis that suggests a 40 percent return is the mean or maximum. Let me assume that the 40 percent is the maximum annual gain you have ever achieved, if only as an academic exercise. Thus the 40 percent is your quitting point based on perfect knowledge of a particular system.

How frequently have you been calculating your forecasts (or inherently, your position choices?) As was learned from the Cassandra Scenario, "that more-frequent forecasting is inherently profitable, even more so than some forms of perfect knowledge." So:

(1) If 40 percent is your mean annual gain, then continue to trade at the higher level. That is, if you started at 1000 and now have 1400, continue to trade the 1400. Obviously it would also be good to shorten your forecasting period. (2) If 40 percent is your maximum expected gain, then pocket the 400 and start over trading with 1000. Shortening the forecasting period is not a given in this case.

Phil McDonnell adds: 

Let us assume the market has a normal distribution of returns and that the probability of making a 40% return or better, at random is 15%. Then if you decide to take all profits at the 40% level then your probability of a 40% gain will double to 30%. This result follows directly from the Reflection Principle.

The above assumes that your returns are random and implicitly assumes that you have no ability to predict the market. To the extent that you can predict then you should make your decision on your current outlook and not on any arbitrary price point like 40%.

Gibbons Burke comments: 

It seems to me that one should be disposed to let the markets give you as much as it wants to give you without putting artificial limits on that phenomenon, but that practical limits should be enforced on how much lucre it can remove from your wallet. Is more return ever a bad thing, assuming that the distribution of returns is not serially correlated? As our gracious host has noted, the markets have no idea how much money you have made or lost, so the idea of reversion to the mean on an equity curve makes no sense in the same way that it makes sense for market prices which are making repeated excursions up and down seeking the implicit underlying value of the thing (the ever-changing "mean" to which the market is always reverting.)

So, setting a goal to achieve a 40% return seems a reasonable thing to do, but I submit that this goal should be accompanied by the qualifier "or more" and be willing to let a good thing continue.

Regarding the 'limiting losses' idea, in the Market Wizards interview with Jack Schwager, Paul Tudor Jones admitted to having risk control circuit breakers in place so that if he ever lost more than x% in a month he would shut down trading for the remainder of that month. Limiting and rationing losses in ways such as this seem like a reasonable discipline if one is going to set limits on how the market will affect your stake.

An old floor trader's trick I learned while reporting on the futures pits is that if a trader enjoys a windfall gain on a trade, and reaches a pre-figured goal (or more), he takes half the position off the table as a positive reward for being right and taking action on that conviction. Leave the rest of the position on to collect any further gain which the market might want to provide, but he raises the stop to break-even for the remaining position (not counting the profits already taken off the table) in order that a winner would not then turn into a loss. If he stop get hit, he still has half of a windfall gain return in the bank. If the market continues in a favorable move and another windfall gain is realized, the process can be repeated.

This tactic has an anti-martingale character which some more bold traders might object to.

All these thoughts are mostly elaborations on the first two fundamental rules of trading: 1) let your winners ride, 2) cut losses.

Stefan Martinek comments: 

This loss avoiding behavior was well researched by Paul Willman and others. It is observed within traders of all levels approaching a bonus target; cutting off is generally viewed as irrational and Willman discusses how to adjust incentives to get a trader back to risk neutrality. Which reminds me more general but relevant quote from W. Eckhardt: "Since most small to moderate profits tend to vanish, the market teaches you to cash them in before they get away.

Since the market spends more time in consolidations than in trends, it teaches you to buy dips andsell rallies. Since the market trades through the same prices again and again and seems, if only you wait long enough, to return to prices it has visited before, it teaches you to hold on to bad trades. The market likes to lull you into the false security of high success rate techniques, which often lose disastrously in the long run.

The general idea is that what works most of the time is nearly the opposite of what works in the long run.



Welcome back former student Mr. Mc. And let it be known that whenever I talk in England, I tell the students "don't listen to the triumphal trio as to their conclusions for the future. They suffer from the English disease or the Old Shiller disease. They believe that the dividend model is the sine qua non of the thing that causes returns. And because the dividend yield is not as high now (or in the crazy Shiller instantiation the dividend yield is not as volatile as the stock returns) that the return in the future can't be as high as the past." But .. but. The retention rate varies with possibilities for after service returns, and likely returns on investments and investor preference. If no dividends were paid, the returns would be at least as high, probably higher considering all the opportunities for rent payments from the foundations like those of the cattle trader and the returns from lobbying.

Philip J. McDonnell writes:

In the US the dividend yield is only part of the non-appreciation return. Another significant part is the potential for stock buybacks and other financial engineering maneuvers.

Jim Sogi writes:

Wow, all the old timers coming back, Lack, Seattle Phil, Roger, Kim, Larry, Jeff. Almost like the old glory days when Chair was a high roller and rented the whole Delmonicos for a party for a thousand friends. Welcome back Phil! Those were the days! I love the Spec List! Thanks a billion Mr Niederhoffer for everything. 



At the risk of telling all to be calm before a crash….I offer the below chart as an antidote to the 2014/1929 'analogue' stuff flying through cyberspace at the moment.

One hopes Messrs Stigler & Lorie would be proud of me.

Phil McDonnell adds: 

One of the common caveats in looking at correlations and analogs is that the correlation should be based on price changes rather than price levels. Using levels leads to spurious high correlations in both directions.

My concern is that using charts of price levels is essentially the same thing as calculating a correlation based on levels. It will lead to spurious conclusions.



One of the common caveats in looking at correlations and analogs is that the correlation should be based on price changes rather than price levels. Using levels leads to spurious high correlations in both directions.

My concern is that using charts of price levels is essentially the same thing as calculating a correlation based on levels. It will lead to spurious conclusions.



 I wish I hadn't written the chapter on poker in edspec. I hadn't played for 30 years when I wrote it, and all I did was read some books from the gamblers book club, and then write about it as a layman, poseur, armchair geezer. I wasted 5 pages of everyone's time on it. And anyone who knows the game would have seen I was out of my league. I try not to be as ignorant of my ignorance as I once was.

The current issue of Outside is all about the secrets of survival. What it takes to stay alive. I am ignorant on this subject. The only thing I know about it, is from books, that when you're the captain, you're supposed to be the last man out, until you say "every man for himself" as Aubrey did. Also, what I read in L'Amour about always being aggressive at the beginning when threatened with a life saving situation. But people on this site are infinitely more knowledgeable than I on this subject as are all my kids and partner, who all had to spend a few days alone in the Vermont wilderness as part of the Mountain School they went to.

So please, give us your survival things, and comment on what Outside said, so that we can survive better in speculation, a consummation devoutly to be wished, and which the all seeing eye would like to do so many things in this life over again related thereto.

Jim Sogi writes: 

 Many cases of death in the wilderness are as a result of a series of small stupid mistakes that compound and make what is not a deadly situation, into a deadly one. First is lack of preparation. The classic case is the two hour hike without proper basics such as jackets, maps, water, shoes, compass and the weather gets bad. The party hurries, mistake 2. One in the party gets injured: mistake 3. The parties separate to get help: mistake
4. Both parties become disoriented and lost and panic, running about. mistake 5. Their bodies are found days later a few feet off the path. All stupid mistakes, compounding a nice situation and tipping into irretrievable disaster. It is the same as Chair talks about: a good base of operation. Basic needs of the operation in the wild are adequate shoes, protection from weather, warmth and hydration, and basic navigation.

The second main survival issues are the basic needs of human survival: water and warmth. One can go for days, and almost weeks without food, but without water, hours can bring on death. If the body goes just a few degrees below or above its normal temperature, body and mental functions shut down and the person goes into a stupor. It can happen in 70-80 temperatures surprisingly.

Often, the simple cure to avoiding the above is just to stop. People have a real need to be doing something, and often it is not helpful and leads to disaster. How many parallels there are to trading!

I have a simple survival first aid package. Loss of blood is one of main causes of battlefield death. Unless bleeding is stopped, death will quickly follow often in minutes. Cetox granules go in the wound and staunch the bleeding by forming clots. Pressure and bandaging or sealing with stitches or tape will stabilize until further help. Also in the kit are pain killers. Sprains and breaks are common, and pain killer will allow the party to limp or carry to further help. The commercial first aid kits are often a waste. Water treatment is top of the survival bag list to kill giardia and cryptosporidium that will cause runs and dehydration. A small tarp or space blanket and jacket will provide enough shelter to avoid hypothermia by blocking wind and rain. Tape such as dermoplast or even duct tape can be used to staunch bleeding, make splints and stabilize breaks and sprains. A good flint and steel and tinder and water proof matches will help build a fire to keep warm. That's about all in my kit. All the crap in the commercial kits tend to be useless weight. Most survival situations only last 3 days. By then 95 percent are rescued or dead. Just stay warm, drink water, and keep your blood inside you.


98.6 The Art of Keeping Your Ass Alive
Cody Lundin
Backcountry Skiing Skills Wheeler, Margaret
First Aid: A Pocket Guide Van Tilburg
Glacier Travel and Crevasse Rescue ,
Selters, Andrew

Deep Survival, Gonzales, Lawrence

Phil McDonnell writes: 

About the only thing I can add to Mr. Sogi's excellent summary of survival techniques is to recommend the choice of tinder for the flint and steel technique. I have considerable experience from Boy Scout days with flint and steel. The best tinder by far is steel wool. I believe the reason is that hitting the steel against the flint throws off molten steel sparks which somehow are attracted to the steel wool fibers. In competitions I used to be able to boil a #10 tin can of water in 3-4 minutes.

Pitt T. Maner III writes: 

 I occasionally watch the Les Stroud Survivorman show and he has some good ideas on the subject. Similar to Mr. Sogi.

For urban disaster he emphasizes having a basic kit stored in a plastic container.

In Stroud's view it is ideal to keep:
1) a week's supply of water and 2) a nice first aid kit (probably doesn't hurt for everyone in the family to take the Red Cross First Aid/CPR course or from another qualified provider. He advises having a 3) crank-up radio to keep in touch with outside world and 4) a shake, non-battery flashlight. 5) Water proof matches, 6) Rope, 7) a Multi-Tool.

During the hurricane season a trip to Costco to prepare for a possible storm is important. Easy to pick up canned goods, water and other items needed. A little wine to share with your fellow condo survivors doesn't hurt either when the power and water go off for a week and you are sweltering without the A/C. I like a big lantern-type flashlight with fresh batteries so you can read a bit at night.

At any rate, Stroud emphasizes staying dry to avoid hypothermia in the wilderness. Exposure is a big risk in the wilds.

Ed Stewart writes: 

 James has an excellent summary of important points.  I will add (or expand on) a few.

First, be very cautious when venturing into new territory.  If one is experienced at hiking a certain path or mountain or area, Don't assume "it is all the same" when you go to a new place.   Don't assume, "I know how to find my way".   I grew up in rural New England and spent a great deal of time in the woods (back country type skiing, hiking, fishing, etc) from a young age.   My families home was near a govt owned wilderness area, and over time I got to know the terrain extremely well in terms of having a mental map and orientation, but also things like natural formations that could be useful as shelter, etc. Knowing a wilderness territory is like knowing where the "utilities" are that you can access from any position.

It is very dangerous to generalize such specific knowledge into thinking "I am good at finding my way", a mistake I experienced and learned from.

Wear the right clothes initially, not just in a backup capacity. What is comfortable in ideal conditions (light cotton long sleeve T-shirt, etc) can be a disaster when conditions change. Material that is waterproof and/or maintains insulating ability when wet is always good.

Extreme danger emerges out of "usual" situations and seemingly small challenges. It is hard to see danger without experience. For example a recreational hiker thinks, "that small rock formation would be fun to climb".   The problem is, how it looks at the bottom (easy!) is a distortion relative to what one sees close up (unstable rocks, dirt, etc) from a now dangerous height. "From a distance" assessments are not an accurate judge of things for most people.

Focus on external factors that reveal themselves through the five senses. Take the time to observe. Stop and listen. Look at shadows, type of earth you are on, gradient, sounds, smells. Getting into that observation mode, not talking, not focusing on your own thoughts but on what is "out there." Bringing the senses alive to the slightest changes in the environment is a significant survival skill.

Experience coping with blood and guts, both literally and metaphorically, prepares one for survival. Many people are very deceived about survival situations because most of modern life is very safe, sanitized, and compartmentalized. Meat comes in a plastic package. "Someone else" does the dirty work. "Someone else" fixes an injured person. "Someone else" makes things safe and secure. People are squeamish about crossing boundaries, and when confronted with them can panic or become ill. An easy way to develop a natural survival mentality in any circumstance is to look for ways to cross boundaries before one is forced to do so.

The sound of a heavy metal bell can carry a great distance.  As I said, I grew up in a very rural area and our home was on a large number of acres. When I was out late fishing, etc, my mom had a very heavy metal bell that she would ring– a sound which would carry for miles and alert me to come home — and immediately, automatically set my orientation.   There are plenty of ways that a low cost item like this can be used.

Vince Fulco writes: 

 Besides some of the other great pubs listed here, the US Special Forces Medical Handbook (a bit dated) can be found on amazon and similar for $10. There is plenty of food for thought for the non-medical professional for when the stuff hits the fan in a bigger way.

Vincent Andres writes: 

I remember well one of Reinhold Messner's simple tips.

When in danger, you are yourself the very first level of protection (and also one of the best, since your reaction can be very immediate). So work well on this very first level, and don't count on somebody else doing the job for you.

This is also a very libertarian and Randian tip.




 Kim Zussman sent me this paper "Sunspots, GDP, and the Stock Market"

The paper strikes me as an affront to the scientific methodology. Here are a few dubious quotes from the Conclusion:

The calculations yield a rock-bottom level of 7919 for the DJIA in early 2014,

On the contrary, one is surprised that the correlation between DJIA and GDP turns out to be scientifically insignificant. Are our scientific criteria too stringent in this case?

If one accepts that there must be some correlation between GDP growth and stock-market growth as displayed in Fig. 5, then one cannot use the lack of scientific proof as an argument against the existence of correlation between the stock market and sunspots (Fig. 2), or between GDP and sunspots (Fig. 4).



Aversion to losses or aversion to risk? Which of the two is addressed by willingness and ability to close out losing trades?

Well, without invoking mathematics where it is not necessary, it is common and logical to place on the table that when a losing trade is closed one has the willingness and aversion to the risk of the persistence of loss becoming into a bigger one and one does not have aversion to the present level of loss in being accepted.

Now on the other hand, unwillingness to stop out a losing trade is indeed loss aversion.

The computations that show that having utilized some sort of mechanical rules for stopping out adverse incursions actually increased the probability of meeting with adverse incursions is totally flawed abuse of statistics.

Several arguments:

1) Historical data analysis does not undertake the "uncertainty at a given moment to decide upon" into account and is definitely incorporating hindsight 20:20 vision mind-set.

2) Any measurements of uncertainty and thus risk are never definite, since measurement of uncertainty too will be having an uncertainty of its own. So a trader in the middle of a losing trade has to decide that the level of uncertainty in his method, mind or cognition regarding the calculation of the "value of uncertainty" in his trade has become too high for him to handle. That's where humility, the currency that prevents others from profiting more from your mistake, can come into play and allow the willingness to hit the stop.

3) However, when either with or without the illusions of statistical computations of stop losses increasing the probability of meeting with more losing trades, one fails to control the human weakness of loss aversion, to somehow and anyhow turn that loss into a profit, one is becoming totally risk-insensitive. From skill, the turf changes to the power of prayer. The game begins to change from action to hope. Inconsistency of thoughts thus turns one into a trader who is continuing to hold on to risk without a mental apparatus to assess it or react to it. As the loss continues to grow not only the lack of willingness to take it hurts, the ability to accept the increasingly bigger loss also dwindles rapidly.

I am ready to be thrown before any firing squads of mathematical minds and ideas on this list if they can with or without numbers help me learn how come this list celebrates and cherishes a human value of humility and yet indulges in an idea that staying on in a trade that has incurred a level of loss greater than anticipated when the trade was opened are mutually consistent.

I would close my submission for now with one thought:

When loss aversion creeps in it makes a decision system (mind) risk-insensitive and with no respect for risk, returns are impossible. Yet, if a mind continues to be risk-averse it does not have loss-insensitivity and in humility such a mind closes out risk that has turned out to be less than comprehensible.

Phil McDonnell responds: 

Since I am the well known culprit I shall give Mr. Kedia a reply. If the probability of a decline art the end of a period of time equal to your stop is p then the probability of losing the stop amount with a stop loss strategy is 2 * p. It is simply a derived relationship. It is what it is.

It is not a misuse of statistics but rather a description of how a stop loss exit strategy will change the distribution of returns. Larry Connors studied over 200,000 trades from a winning system and compared the results with and without stops. He found the use of stops increased the probability of loss and reduced the expected gain.

In my opinion the best way to trade is to reduce position size so that no one loss hurts your account too badly. That means many small positions to me.

Larry Williams adds:

Ahhh here I go off on a rant; please excuse a tired old mans bitterness at system vendors who claim stops hurt performance.

Yes, they are correct in that the statistics of your system will look better if one) you don't use a stop and two) your use a market with a perpetual upward bias like the stock indexes have been, usually.

They are absolutely totally incorrect in terms of living the life of a trader. So what if I am long in a position that eventually shows a profit but because I did not have a stop loss that one trade moved against be 20,000 or $30,000 and it took a year or so to get out of? Yeah, the numbers look good (high accuracy) with no stops but it's one hell of a lifestyle.

High accuracy is a false God.

Consistency and never being in a place where you can get killed is more critical. Perhaps Mr. Connors has never sat through the reality of a large loss, especially in a large position. I have; I would rather battle the devil at midnight on a new moon with both hands tied behind my back.

It's one thing to have a system with "good numbers" it is quite another thing to be a trader and have to deal with reality.

It only takes one bullet in the chamber to kill you when playing Russian roulette. As near as I can tell trading without any stops, in any way whatsoever, is just the American version of this form of spinning the wheel.

Play the game as you wish but please heed the warnings of an old man.

Leo Jia adds: 

I have been studying the use of stops. Due to loss aversion I guess, I would like to use narrow stops. But among the various strategies I have yet found one working well with narrow stops. Good stops have to be relatively wide in my cases, but having no stops or stops that are too wide clearly hurts results (my trades are time limited). So a good choice for me is to size the position according to the stop size.

Sushil Kedia writes: 

If you reduce position size can it be argued that a position of Size N reduces to N-n implies that you took a stop loss on n lots out of N you held. Then too, it validates the fact that you do take stops.

Anatoly Veltman writes: 

Larry covered main bases (different markets, different position sizes, different lifestyles) pretty well. I just want to be sure that reader doesn't end up with wrong impression. I think the best conclusion is "it depends".

And because my act follows Larry's (who is certainly biased in favor of stops), let me try this. If you enter based on value (which is certainly against trend), then there is no justification available for a stop. Unless you argue that this stop proves you were an idiot on the entry. But if you are an idiot on value entries, then why play value…

Anton Johnson writes: 

 The problem with using Conners' simulation as evidence that placing a trade stop-loss reduces returns is that he tested a winning system that likely had never experienced any 5-sigma negative excursions prior to the test date. And of course there are no guarantees that his strategy, or any unbounded trading strategy, will perpetually avoid massive drawdowns.

When implementing a strategic trade, a good compromise between profit maximization and loss mitigation can be achieved by balancing trade size along with a stop-loss, which when placed at a level that only an extreme event will trigger, will likely contain losses to a predetermined range, and also prevent getting stopped-out of a potential winner. If one is disciplined, maintaining a mental stop-loss level is preferable to an order pre-placed in the book, and available for all the bots to scan.

Larry Williams adds: 

But speaking of stops, I go back to my litany, my preaching the essential reason for never putting stops on an exchange server, or even your brokers server. Putting stops on servers means that your stop becomes part of the market. And not in a positive sort of way either. Pick a price, hit the button, and take the hit. Discipline is key here.

Ed Stewart writes: 

A trader needs a decision process for managing the expectation or expected value of the trade as well as the equity position. The problems occur when these two things are in conflict.

The thing with stops is that at times it makes no sense to get out of a trade when the expected value is still good. What is the difference between exiting at a small stop-loss point 4X in a row vs. one loss of that same size? Well, if at each "stop out" point the expected value was favorable, it makes no sense, one is just locking in losses. At times the best "next trade" is simply staying in the current trade.

However, I see Larry's point and it is a good one. Yet, the example of letting a loss get huge or holding an underwater position for a year is to me something of a false alternative. No exit strategy but hoping for a profit at some point is not a reasonable alternative.

What maters, I think, is the expected value of the trade at each moment, and balancing that against equity and a margin or error to ensure, "staying in the game".

Given this I always trade with mental stops, if not on individual positions, on total account equity. Having that "self-preservation" discipline is useful.

Jeff Watson writes: 

I learned very early on in the pit on how to go for the stops, and that weaned me off of stops completely (except in my head).



We have had numerous discussions on this venue regarding stop losses. Part of the surprise from those discussions is that using a stop loss will double your odds of having a loss in the amount of the stop loss.

However the same is true for a profit target. Using a profit target will double your probability of having a gain equal to the target gain. The reason for both phenomena is that in a random walk half of all such trades will get reversed after hitting the target or the stop. The fancy name for this is the Reflection Principle.

Larry Williams writes: 

In a random walk, half of all stops/targets get hit, so if that is not true in several trading systems, does it suggest the market is not random?

Anatoly Veltman writes: 

Electronic markets are far from random. Your broker's HFT frontruns your orders, and non-broker largest HFTs parallel run your orders. Thus your limit (profit-taking?) order is played against by unabling, and your stop-loss order is played against by triggering. Random? Not to your account.

Ralph Vince asks: 

But can non-random ticks, sampled on a bigger time frame, degenerate into randomness?

Anatoly Veltman replies: 

In the sense that all those orders, magnified by HFT mechanism, will carry markets somewhere - sure. The other question is: OK, so 70% of executed trades resulted in robbing the outsider spec - but the HFTs and the brokers have not fully benefited by your loss, because of their high overhead (the arms race, et al). So ok, the wall street salaries, the IT salaries get financed out of your pocket. Then the only way to keep you in the game is to inflate your remaining funds…So the mechanism will continue on…but to what end, if the economy is not picking up? So the result may well be non-random: all prices will go up.

Gary Rogan writes: 

Clearly the natural drift and/or inflation-driven accelerated drift will result in an upward bias that will make a random walk impossible. In addition, if there is an HFT-induced tendency to hit stops and not hit limit orders (by the way are there any objective statistics that prove that?) the question becomes: would an independent observer looking at the data tick by tick, but who is not himself placing limit/stop orders be able to tell that the statistical nature of the tick distribution has changed?

Jeff Rollert says: 

No, HFT is attacking your behavioral biases. Not the academic ones ones. Your bids show your hands.

These are modeled after high yield bond trading patterns.

How would you trade if the book was open and public? That is the point. Trading systems are rational, and your systems are easy prey…seriously, inject the random. To borrow a sports analogy, you can't bore a machine into an error.



Those who choose not to read good books have no advantages over those who cannot read. (Attributed to Mark Twain.) A similar thing applies to research and data: Those who do not collect (and scrutinize) their own data, have no advantages over those who get their ideas and data from journalists or poor data suppliers. I would venture an educated guess that most of the managed investment money is handled by managers getting their information from journalists. Gentlemen, that's your competition. Go forth and prosper.

In quantitative analysis (irrespective of whether its data origins are financial statements or market prices) the guy with the best data has a definite advantage. Conversely, the best analytical mind coupled with poor quality data is at a disadvantage. Let me first deal with the problems of price data.

In equities, back-testing requires using deceased stocks to eliminate survivor bias. That means that to test the Russell 3000 over say 15 years, you need data on maybe 8,000 stocks. You cannot collect those by symbol, because symbols get recycled. So you try SEDOL or CUSIP numbers, but even those have problems. The holy of holies, CRSP has problems. And you cannot simply toss out the missing stocks without experiencing bias. Also note that the constituents of the R3k decrease monthly and are refreshed annually.

Obviously you have to adjust for dividends because you want to compare total returns. That introduces the dividend adjustment problem: do you use multiplicative adjustment or subtraction? Either one is problematic: destroying round numbers or creating negative numbers.

However the problems with data create tremendous opportunities to those who mine it. You know you are on to something when:

1. A major data provider has all of the dates of certain data off by 1 day. (systematic error) You call to ask why that is, and they don't have any idea what you are talking about. "How can you possibly know apriori that their data is wrong?" So you quickly reverse yourself and apologize for being mistaken. Everyone who uses that data has the error. They are counting things that are impossible.

2. You circumvent data suppliers and go directly to the exchange (or government website) because intermediaries screw it up. Hey, you cannot expect data replication to be perfect. (idiosyncratic error)

3. You disregard seasonally adjusted data in favor of raw data, and do your own seasonal adjustment. You cannot do this for every dataset, but certainly for the important ones.

4. A free provider (e.g. government or an exchange) provides detailed instructions on how to data mine their site. But the instructions are wrong. You call and the service people don't know what you are talking about. You eventually get to speak to the geeks and somehow learn the right way to get access. They confirm that no one had those problems before. WHY? Because no one else is looking at the data. He shoots; he scores!
These examples are like lifting back the bride's burqa, thinking that she might have a beard, and being surprised that she is absolutely beautiful.


a. When at all possible, go directly to the source. That may mean the exchanges or the government agency itself rather than your data supplier, and may appear unnecessary on the surface. But if you want to find the mistakes that most cannot find, you have to look in different places.

b. Look for site or download counters and check them out. Come back to them and recheck the numbers later to see the average daily hit rate. I was absolutely delighted to learn that I was one of only four downloaders of certain data.

c. Further check that data (with the counter) to see if it is available on Bloomberg or another major source.

d. Look for alternatives to the data you seek. The alternatives might not be the exact data, but they may be good surrogates. Real numbers for something close to what you want are better than bullsh*t numbers from a poorly conducted survey.

e. I cannot overemphasize the importance of checking the data, and checking that your data mining routine has collected it properly. Errors (either systematic or idiosyncratic) regularly occur. As renowned data cruncher John Tukey said, "There is no substitute for looking at the data." (Exploratory Data Analysis)

Typical problems you have to avoid:

- Look-ahead bias and survivor bias

- Lack of statistical significance - engineers typically require 30-50 observations, but market traders (such as technical analysts) frequently consider one event as significant. Don't do that!

- Testing on a sample of data that may not include the pattern. The solution to that of course is to always use the population, rather than a sample.

- Frequently you may test something on an index as a precursor to testing on thousands of individual stocks (or worse, options). But indices do not necessarily behave like individual stocks. ETFs might be a solution, but they are in themselves just smaller indices.

Those who challenge the validity of data mining (and also market timing) tend to cite as their proof that the first order daily changes in stock prices are random. We can concede that point, but there are lots more relationships to be studied than daily changes.

Data mining can be successful for any number of reasons but the juiciest fruit is to be found in the following ways:

- Analysis of data that is unknown or unseen by most people or, better yet, subject to systematic error (~finding buried treasure)

- Better analysis of existing data. (~having a better brain) Note that some of this will be serendipitous. Exploration by definition will lead you to discovering things you did not expect.

- Incredible persistence (hard work).

Should you seek to do fundamental analysis you will find different and more exasperating problems. We know many of them first hand.

The first problem is that the data is not easily accessed. It tends to cost quite a lot of money, and much of it has systematic errors. We have not found a commercial data supplier that did not have systematic errors.

The cost can be prohibitive. The major high-end quote provider places limits on the amount of data one can retrieve in a given period. We also know that provider uses a lot of humans in the process and has a lot of errors. Looking further afield, the fundamental data vendors we found are three in number. One replied quickly with a quote of $30,000 for the back data and a 1-year subscription going forward. Another came back a month later and wanted $72,000 for the same, and the third never came back to us. When I informed the higher priced service that they were above their competitors, they asked if their "pricing committee" could know what we were quoted by their competitors. That does not tend to make one comfortable, as what kind of business does not know what their competitors charge? Particularly if they make the point of having a pricing committee.

There is an alternative to buying fundamental data – getting it yourself. In theory this should be straightforward: the S.E.C. has all of the relevant files online. But if you are looking to get data on say the R3k for 15 years, you will have to collect it from approximately a half-million 10K and 10Q files.

Uniformity is generally not the rule, and you need some uniformity when doing computer mining. For example, sometimes a 10Q will be labeled "Ten Q" which has to be planned for. Unless you have access to a lot of people from the sub-continent, you want to do this automatically, which will also enable you to avoid things like transposition errors committed by humans. But some things are easier for humans than for computers. For example, most data constituting a company's total assets are listed as "Total Assets". Sometimes that is misspelled, and sometimes the number appears with a double underline, and other times without. Usually the next line starts with "Liabilities", but not always. It's laughable, but not fun.

We cut our teeth on a subset of the universe, REITs. The 172 that we found interesting had approximately 8,000 10K and 10Q files. After a lot of work we managed to get data cleanly from all but about 50. We consider that a major success, but even that low failure rate means we will have to go through about 3,000 files manually for the entire universe of a half-million files.

The good news is that having unrestricted access to such data provides a lot of opportunities. We are making a leap of faith that the data and our analysis will improve our existing results. Of course there isn't a guarantee, but that's the way to bet.

Phil McDonnell writes: 

Thanks to Bill for his excellent survey of data collection techniques and especially the pitfalls. There is little to add to his survey except one thing. That is when there are retroactive changes to data. To handle that case one needs to time stamp your data as to the time received. This caution applies to both fundamental data as well as price data which can be 'adjusted' a day or two later.

The worst example if this was Enron. The Enron data which showed the fraud was only released several years after the bankruptcy.



One of the most valuable things I learned from the Chair is how not to do a study.

Let us summarize how to do a study. First define a pattern or event of some type. Then calculate the expected return subsequent to that event when the event happened. Then compare that return to the returns for all other non-event time periods. Do a t-test to establish significance at the 95% level.

That said the real problem is how can we insure ourselves against the possibility of biasing our study or otherwise completely messing up. the first thing that comes to mind is to never include data in your decision process that was not known at the time. For example Enron went bankrupt and then several years later after an audit the financial results were released showing that the original releases had been fraudulent. You cannot use the adjusted data based on the argument that it is the best data. Only the original data was known at the time so you must use that.

The same thing goes for price data. You have to use the prices that were known at the close if you are doing a buy at the close study. You cannot use retrospectively adjusted prices when the data is adjusted later than the supposed decision was made.

Always use tradeables. For example the S&P 500 index does not trade as an index. The S&P futures do and SPY does as well so one would use either of them as data for your study. The reason is that individual stocks can have stale quotes. Some of the smaller stocks in an index do not trade nearly as often as the larger caps. Thus the index can be behind the true position of the market. The tradeables trade and thus are subject to arbitrage that tends to keep them in line with the real market level.

This is a short list of things not to do. However it is representative of the fact that it is harder to learn what not to do than what to do. Other contributions would be welcome.

Victor Niederhoffer adds:

Always simulate what the chances were that your observed results were due to pure luck and take into account the path that your results would take and what that would have required of money management.

Consider the impact of retrospection on your results. The human mind is capable of ascertaining many regularities that occurred in the past, and is good at uncovering them in a study after the events occurred, but not very good at uncovering predictions based on new data that they are not already privy too. Never use range forecasts as they don't tell you whether you would have made or lost. Be aware of the difference between description and prediction, and statistical significance versus predictive distributions.

Never be overconfident. Do take account of the drift in your data, and the shape of the distributions you are drawing from. Mr. T, is not very good if only 2 or 3 observations removed from your sample would change the results.

To what extent are the regularities you believe you have uncovered been extant in the literature or the knowledge of shrewd fast moving traders. That changes things. What is the extent of regression bias in your results? 

Alston Mabry comments:

Something else, basically another riff on the Chair's comments: I find that statistics like means and correlations are, of course, useful, but they almost always hide important, idiosyncratic structure in the underlying data. In a sense, summary statistics are "intended" to do that, but I find it useful to unpack them and examine the structure in the data series, how the summary stats change over time, etc.

Anton Johnson writes: 

A couple of important things to consider.

Large changes in outcome resulting from small adjustments of a parameter is a sign of over-fitting and usually bodes badly for real-time results. Sometimes eliminating or finding a suitable replacement for the sensitive parameter will result in a more robust and usable model.

As a general rule, the number of parameters used in a study should be FAR fewer than the number of resulting trade signals.

Ken Drees adds:

Coach Bob Knight's new book The Power of Negative Thinking mentions "NO" being safer than yes. You can always more easily change a "no" into a "yes" versus the opposite–deciding to change your mind from positive to negative.

The gist of the book is to tamp down the uber positive thinking crowd–no, you can't do anything you want, no, you can't magically power your way to a fine end. PONT, Power of Negative Thinking is how Knight coached. He explains it that you must limit faults, limit mistakes–if we don't do these things then we have a chance to win. He keys on dealing with negatives to achieve a positive. He must have come across a lot of less disciplined approaches to coaching in order to come up with an against the grain type philosophy (PONT).

A lot of his points are probably already in the quiver of the sharpened spec. His hyper worried routines, careful study of the opponent, downplaying of good fortune and constant moving of yesterday's win into the rearview mirror broadens out into that persona you conjure when you think of him–that brooding face, those searching eyes–never smiling. The idea of "can't do it" was probably the most different from what we hear today–most are afraid to say "can't–that it means "I won't". Knight loves the honesty of a player saying I can't understand that assignment, or I can't push myself any farther. I would not recommend the book to cross over into speculation, but it's a quick read and there are more than some items to enjoy.

During it, I thought about player health in relation to speculating. I am my own coach. It's a luxury to have someone call your number and sit you down for a breather, to know you may need rest over more drill. How do I know that I am playing/ trading fatigued—only after a poor result? Knight seems to have the keen memory still in gear. There are some interesting stories about his games and Big 10 accomplishments.

Coach Knight will definitely tell you "No".  

Leo Jia writes: 

Very interesting, Ken. Thank you for sharing.

There seems to be some rationale in being positive. As I understand it, when one says "yes, I can do it" and envisions the actual doing, he actually plants a seed in his subconscious brain. The subconscious brain can be more powerful in many ways than the conscious. So planting a seed there is to use the additional powers of the brain, which are not accessible by the conscious mind normally, and thus increase one's chance of achieving a goal.



 Having internalized some basic aspects of wave counts, such as alternation of corrective waves within a motive wave, coming back to the counts produced by Advanced GET is a strange experience, as the software-generated counts seem quite wrong.

Have others, as I now have, given up using software to mark the key wave points? Of course one would still use a software grid to mark Fibonacci retracements.

Anatoly Veltman writes: 

Actually, Advanced Get by Tom Joseph was very good when first introduced in late 80's-early 90's. Trick was that one should have also attended Tom's weekend workshop (mostly held near an airport in Ohio), to be tipped on the whole essence: type 1 and type 2 trades, wave 4 index and oscilator. Without figuring out when Wave 4's odds diminish to unacceptable — there is no reliable Elliott Wave trading. And Fib retracements are great — but ONLY if EW type 1 or type 2 trade has first been isolated. I taught Tom's methods for about 15 years. Not sure if any of my students succeeded in black-boxing the entire methodology.

Tim Melvin writes:

Did someone really say fibonacci on the spec list? This could get interesting if it is anything like the old days…

Anatoly Veltman writes: 

Well, that's the whole point. Loving to say Fib doesn't test well– when the wrong application was tested to begin with.

Phil McDonnell writes: 

To be sure one must test something according to the right way of doing things. However that is exactly the problem with wave counts and the like. The rules are so arcane and convoluted even so called experts disagree on them.

If you get 5 different Elliot exerts in a room you will get 5 different wave counts at the same time. It is a bit like the game of Fizzbin. The rules keep changing and are unnecessarily complex. 

Leo Jia writes: 

I think one probably should take this argument as a not-bad news for Elliot theory or any theory that gives non-consenting results. It means that it likely has some statistical truth in it that is worth one's effort in seeking. Don't we agree that a market theory delivering definitive results does not exist or, if exists, ought to be thrown out?

Steve Ellison writes: 

Trying to stay in line with our raison d'etre, I have been coding a method for retrospectively identifying highs and lows of multiple levels of significance.

My approach is to go bottom up, starting with an idea I got from one of the Senator's books. A local high is a bar whose close is higher than the closes of both the previous bar and the following bar. A local low is a bar whose close is lower than the closes of both the previous bar and the following bar (a sequence of 2 or more bars with equal closes count as one bar for this purpose).

After identifying the local highs and lows, I move up a level. A 2nd level high is one that is higher than both the preceding local high and the following local high. A 2nd level high cannot be recognized until one bar after the lower local high that follows the 2nd level high. I record the time at which the 2nd level high could have been recognized.

I follow similar rules to identify 3rd level, 4th level, etc., highs and lows and the times at which they could have been recognized in retrospect.

I haven't finished yet, but this method should give me a platform for testing hypotheses about "primary trends", etc.

Anatoly Veltman writes:

Tom Joseph's contribution to E.W. trading, in my view, was much greater than Prechter's or RN.Elliott's. Tom basically said with his excellent refined Type 1 trade: don't ever place any bid, unless:

1) you've already observed a valid impulse (with extended third wave)
2) a correction is currently in progress, approaching 38% of preceding rally
3) you're filtering this correction with oscilator return to 0, and fourth-wave index still sufficient for fifth wave
4) fifth wave projection extends to at least 2:1 profit/loss ratio, incl. all possible slippage.

I say: if all these conditions are not met (and this may not occur every day) - never place a bid at 38% retracement. If all these conditions are not met, you'll have to bid only at near-100% retracement. What does this principle have to do with popular E.W. or popular Fibonacci methods. Nothing!!

Laurence Glazier writes: 

Sure, things are complicated and one would not wish to poke a stick into a hornets nest, but … some things are complicated.

It took hundreds of years to elicit the laws of harmony from the canon of classical music (many to this day deny their existence). Put five composers in a room and have them harmonise a tune (the non-believers might refuse to!), and they will do it five different ways, but they will all have added to the map of knowledge.

Even knowing those laws, one could not reasonably predict how a piece of music would continue if Pause were pressed (unless it were minimalist) - but one might anticipate it would return to the tonic key, and that the free fantasia would not be over-long, and so on.

Those laws are difficult, unprovable, and without material substance but are the result of empirical observation.

Gibbons Burke writes: 

CTA E.W. Dreiss used, in the 1990s, a very similar way to count waves in the market using what he called the Fractal Wave Algorithm (FWA), and he traded futures breakouts from FWA-n magnitude highs and lows. Did quite well, but like all trend followers, it is a bumpy ride.

He also came up with the Choppiness Index, which sums the true ranges in the last n periods, and takes that as a ratio of the n-day range.

Jason Ruspini writes: 

This is the natural approach that I took as well. Ignoring the "correct" 1-5 definitions, I just looked for a run of higher such double-X highs and higher double-X lows identifiable with the necessary lag, with attention to what happens when you eventually get a lower major high/low, breaking the "wave" run count, which can keep going after 5. What I found wasn't very interesting, in-line with my previous comment. I'm still unclear if anyone is actually trading a tested (complicated) system or just applying versions of rules with discretion. If it is a tested system, why is it better than a simple long-term momentum system?

George Parkanyi writes:

I like to keep it simple. Many years ago, I read something written by Larry that said, when the commercials are generally substantially more net long or short than specs - that tends to stop trends and turn markets the other way. He admitted it was a rough rule of thumb - that it may take a while to turn the tanker - but I pay attention and time after time I've got to say it works. So right now two markets that fit that profile are coffee and to a little lesser extent sugar. (Oh yeah, VIX as well) I've been long both for a couple of weeks with modest starting positions, and just had a nibble at VIX. I don't know when the trends will turn and I may have to take a stop or two, but I like the chances for a good position-trade in these two markets - and VIX as a bet on a short-term post-Fed hang-over. I checked back to when coffee started this particular big decline - and it was within two weeks of when commercials were selling the crap out of it and their net-short positions had peaked. Gold and a number of other commodities did the same thing at the beginning of this rally that began in May - except that the commercials were the only buyers at the time. It may be a dumb-as-dirt perspective on my part, and will likely set off Anatoly - but its one thing that has stuck with me from reading a number of Larry's books.



 We did our refi at 3.5%. I keep hearing about a renaissance in the US housing market, with Toll claiming it has pricing power. Yet mortgage rates continue to drop. This makes no sense to me. If the market for homes is coming back, shouldn't mortgage demand be increasing –leading to higher rates, not lower ones?

Phil McDonnell writes: 

If mortgage demand is increasing and that is the only variable that has changed then mortgage rates should be rising. But that is not the only variable that has changed over the last couple of years.Helicopter Ben has been flooding the market with easy money via QEn. that is the dominant factor.

Steve Ellison writes: 

In Foreclosure City where I live, sales activity is very brisk at prices 60% off 2006 levels. Homes that are priced appropriately are selling very quickly, and inventory is very low since a new state law went into effect that required lenders to prove they actually held the mortgage before foreclosing.



(BN): "Obama Proves No Carter in Romney Linkage as Investors Favor U.S."

Let us expect many articles like this using ad hoc measures, selected starting and ending points, and forgetting that the market dropped 50% before Nov 2008 as investors anticipated victory by agrarians.

Phil McDonnell writes: 

This is a classic straw man argument. Take the worst performing President and show that Obama is only the second worst performing President.



I often ask about ways to test a system to know when to stick with it or abandon. Quality control/TCM is one of the ways people mention of knowing how far removed your model or process if from the expected. I thought of another semi related way borrowed from blackjack.

In blackjack counters use a system wherein certain cards are given a +1 value, others a -1, and then some receive 0. Idea behind this is low cards (2,3,4,etc.) benefit the dealer while high cards (10, j, q, k, etc) benefit the player. If a player sees a lot of low cards come out successively, the count goes up by +1 per low card and the odds go up. When the count gets high the players have a decided advantage.

I think an interesting way to apply this to markets, mainly via systematic models, would be to line up the overall stats/odds of a given model. Then one could paper trade it keeping a sort of count for high probability entry. So if paper trading and you see the model loses 6 straight trades and this has only happened <5% of the time over a large N and the historical info shows that the odds (in both frequency and magnitude terms) favor a win on trade 7, you go live. The "count" has given you a high probability entry within a high probability system.

An ultimate stop loss per model could be assigned. You could give the model maybe 10% total drawdown potential. Subdivide this into 4 parts of
2.5%. Enter when the odds or "count" go in your favor (as described above). If you start making money then great, let it ride. If however you lose 2.5% (even after entering at the high probability point) you stop trading, wait some predetermined amount of time, and try again with the approach above. If the model experiences a 10% drawdown after 4 attempts with the count approach then you shelf it.

The same could be applied to the winning side but I would be more inclined to just let it run if in the black. If playing with the house's money why not let it ride.

This logic could also be used to size trades, increasing size when the count gets high and decreasing when the count gets low.

Jim Sogi writes:

Since stops degrade performance, the alternative is to use trade size to prevent disaster. Yet smaller trade size decreases performance as well. Is there a study stop systems vs a trade size systems comparing the two with some sweet spot data on lower drawdowns, and ultimate returns? I think the long term historical optimum was 1.9 leverage. 2.1 leverage went bust long term in the big crashes.

Phil McDonnell writes: 

In my opinion trade size is the only reliable way to control risk. I am not sure why Mr. Sogi believes that reducing size reduces performance. If you have a stock picking method that gives you many stocks then the edge should be similar for each of them with no loss of edge. I suspect he is assuming something else.



Suppose there were 2 people in an economy. And they traded. The second lost a lot. The other did not. A central bank bought the asset that the second had to make him whole. The Treasury then spent the amount of the loss on better environmental things for government buildings. The money to pay for this would come from the first person in current taxes. What would happen? The total spending would not change as the second would have spent the money he was taxed or invested it with someone who would. The incentives of the second would decrease to zero so that there was no effort to improve any more. The situation would not be much different for 10 traders. The incentives would be ruined for the winners. The spending of the winners on voluntarily exchanged things would be replaced by political wasteful spending by the government. The economy would not grow. Jobs would not be created. Why is this not a reasonable model of what's happening now and what happened during the 30's when FDR tried similar government works?

T.K. Marks writes:

A creative academic sort might counter with a disingenuous application of Ramsey Theory, positing that unduly reducing the number of elements in the set strips it of the properties from which the desired outcome will emerge. According to such an approach, reducing the system to only 2 or 10 traders (i.e., dynamics easy to understand) would inherently alter the palliative effect of intervention models. Models which can only work on vast systems of millions of traders (i.e., dynamics extremely difficult to understand).

If somebody can sit before some House subcommittee on something-or- another and manage to keep a straight-face, the above can actually be pulled off. As a matter of fact, variants of it happen all day long in Washington.

"…Ramsey theory, named after the British mathematician and philosopher Frank P. Ramsey, is a branch of mathematics that studies the conditions under which order must appear. Problems in Ramsey theory typically ask a question of the form: "how many elements of some structure must there be to guarantee that a particular property will hold…"

Phil McDonnell writes: 

Rocky [see post below] makes some good points but at some point finesses the concept of (some?) politically wasteful spending into all government spending is wasteful. Personally I would posit that some government spending is always wasteful but not all is. On the other hand most government spending is uneconomic. I say this based on the fact that if the activity was economic then the private sector would probably have already done. it.



 Dailyspecs who like a good Indiana Jones adventure might want to check out the book The Mountain of Moses: The Discovery of Mount Sinai.

The book is a true story expedition to find the Mountain of Moses in the Arabian peninsula not Sinai.

It does not star Harrison Ford but rather features the site's own Larry Williams.

It is a great read.



 At one time the Chair recommended a 3 strikes and out rule. If your system has lost three times in a row it may be tired and needs a rest. Another way to monitor that is more sophisticated is to use the techniques of industrial quality control. Essentially you monitor your average expected gain via something like a moving average and then take the standard deviation around that. If your average ever wanders outside the 2 sigma band above or below then your process has failed and needs to be reviewed. The idea of Shewhart diagrams is similar to this.



 When we analyze data and find some sort of correlation either positive or negative what have we really found. Have we found cause and effect?

The simple answer is no. Proving correlation cannot demonstrate causation. The fallacy that is at the core of this is that even when two variables are correlated one does not necessarily cause the other. The real underlying cause could be a third unobserved variable that is moving both of observed variables.

An example of this might be that we observe that the stock market and bond market move together over a period of time. That does not mean that one is causing the other. In reality they may both be caused by the Fed's Permanent Open Market Operations (POMO). If that is a variable we have not considered then we are oblivious if it is removed from the economic landscape one day.

All of this begs the question as to whether or not we should be trading on past correlations. Is it just a fool's errand? I think it is not, especially of the correlation is strong enough. But it does expose us to the risk that the hidden real cause will evaporate someday without our being aware of it. That is the risk of speculation. We must be ready to give up a system or anomaly that has worked in the past if it suddenly stops working for us.

Yishen Kuik writes: 

I am far from qualified to speak with any authority on statistics, and my training in mathematics was only as an undergraduate focusing on number theory.

My only claim as to why my opinion on this matters is that I have been operating a statistical trading book for some years and have not yet been swallowed up by the market.

I find that I can get most of the answers I need with fairly basic statistical tools, as long as I ask the right questions with them. I have also found that most advanced tools have to used with care. I want to be able to rely on the results I get with tests, and advanced tools tend to have specifications and nuances that I find troublesome to be familiar enough with that I can use the tool with confidence.

I am surprised at how confident many people, especially those in academia, are in the results they get from using very involved statistical techniques. Even when using very simple tools, I find that I have to think very carefully about the range of explanations for results and how vulnerable they are to various quirky aspects of the data. The Chair's point about how fat tails can be the result of aggregated gaussians or how arc sine can lead to unexpected distributions of highs and lows are good examples of this. In practical usage, I find that such unexpected results are quite commonplace. With complex tools, I am concerned that I may be blindsided by unexpected results from the interaction of data attributes with the details of the implementation that renders my ability to interpret the results correctly. The non-stationary nature of financial time series, the single history, the memory, the regime based volatility and many other aspects of markets tends to really screw up many statistical tools. It is too hard for me to look through the details of the advanced tools and think about how the perversity of financial time series might affect the results in complex tools before I can even contemplate using them with any confidence.

I find that to get the right answers, it is more important to sit down and think and come up with the right list of questions to ask, the answers to which in total should reveal the bigger answer you want to find. For causality and correlation, I doubt if there is a "just add numbers" tool that will give you a worthwhile result.

My algorithm for answering such a question would be to draw a warm bath and sit in it for a while. Then in about 2 or 3 days, usually in the early morning for me, a list of questions will come to me, the combination of answers to which will address the correlation/causation issue, and then later at my office I can construct the tests necessary to express those questions in a few hours. 



 I have been looking at the "for sale" and "for lease" signs in the local area in Bali, where a lot of the deals are found "locally", ie not represented by agents, but marketed by side of the road signage.

I have found that the more permanent looking the sign, the less of a bargain there is, or some other type of deception is being presented on following up.

So there appears to be some expertise in getting this quite right.

A sign that's strong enough to withstand the storms and the wind and the rain of the wet season, but still have that look of, "I've just whipped this sign up quickly, for a quick sale, as I need money fast, as I just blew too much on a cock fight, come in you'll get a bargain."

No doubt other areas in business, which have got a bit too much spit and polish, like a "too well" dressed salesmen, get you thinking "caution ahead".

It's a fine line which pays for the representative to get it exactly right.

Phil McDonnell writes: 

I remember reading an academic paper many years ago that showed that annual shareholder reports without frills were the best stocks to own. If the company was not wasting money on hype and glossy materials then the stock probably was not over valued and they were running a lean machine internally as well. On the other hand companies with the glossy annual reports probably already had their run and were living high on the hog. I do not have a reference but others may recall the paper.



 In my experience the Next Big Thing (NBT) is often very obvious to everyone. It usually is not about being the first to market to achieve success. Rather it is often all about execution. Apple under Jobs has always executed well and that is their secret. Some examples I might cite would include Bowmar who delivered the first electronic calculator to the market. Where are they now? Instead HP has the high end and Texas Instruments and Casio split the rest.

Other obvious things include the PC, flat screen TV, smartphone, the Cloud, tablet computers etc. That coupon flipping idea is my son's company. That is his NBT idea. It is a synthesis of the current coupon rage and social networking. But ultimately it is execution that will determine who makes it in each of these areas.



 In Dec 2010, Daily Spec announced a contest for best investment ideas for 2011 at this link .  Several volunteered to judge the contest. And this seems necessary as there were many intricacies in judging. As a start to declare the winner, would those who feel they are in the running for the winner's prize, please alert me to their recommendations, the results, and why they feel they may be near the top. Thank you. Vic

Dan Grossman writes:

Vic, below is my contest-entry email, with the results indicated in italics. It should perhaps count in my entry's favor that my percentage gains were achieved without the use of derivatives or other form of leverage, and that they were very specific stock predictions, easy for anyone to implement and make money from.

As indicated, if I am lucky enough to win, I will donate my prize to a free market or libertarian nonprofit organization.

Trying to comply with and adapt the complex contest rules (which most others don't seem to be following in any event) to my areas of stock market interest:

1. The S&P will be down in the 1st qtr, and at some point in the qtr will fall at least 5%. S&P wasn't down for the quarter but second part of prediction was accurate in that S&P fell 6.4% from Feb 18 to Mar 16.

2. For takeover investors: GENZ will (finally) make a deal to be acquired in the 1st qtr for a value of at least $80; and AMRN after completion of its ANCHOR trial will make a deal to be acquired for a price of at least [corrected in followup email to $16]. GENZ (50.93 at contest date) was acquired early in the year for a then-current value of $74, but including a contingent right which could still bring total value to $80. AMRN (8.20 at contest date) was not acquired, but soon traded above 16 for some two months.

3. For conservative investors: Low multiple small caps HELE and DFG will be up a combined average of 20% by the end of the year. HELE and DFG had a combined price at contest date of 58.58, and a combined price at year-end of 75.00, for a combined average gain of 28%.

For my single stock pick, I am something of a johnny-one-note: MNTA will be up lots during the year — if I have to pick a specific amount, I'd say at least 70%. (My prior legal predictions on this stock have proved correct but the stock price has not appropriately reflected same.) MNTA was 14.97 at contest date and 17.39 at year-end, for a gain of 16.17%.

Finally, if I win the contest (which I think is fairly likely), I will donate the prize to a free market or libertarian charity. I don't see why Victor should have to subsidize this distinguished group that could all well afford an contest entrance fee to more equitably finance the prize.

Best to all for the New Year,


Yanki Onen writes: 

Dear Vic,

Once again I would like to thank all of the contributors to the daily spec word press for sharing their insight and wisdom. It is a never ending journey. Below were my ideas but to be quite frank I don't know if they were eligible for the contest. But if they were results should be alright

1) Going long csco and long put lost $2,18
2) Sell contango buy backwardation trade for cotton buy selling spreads
made a lot of money but I don't know how to quantify that cause it is trading call 3) Leveraged ETFs suckers play. This strategy was right in the money and made quite a sum.

Our lively hood depends on what we make of the beloved mistress, if you get a long she is quite charming. Thanks for the challenge. Also would like to use this opportunity to wish you all a great prosperous new year.

Phil McDonnell writes: 

My trade on the Silver ETF SLV was closed out when the ETF hit its target price of 40 as stated in the original instruction (at the bottom). On April 11, 2011 the trade was exited with the following post to the list in reply to a suggestion from Big Al:

Yes, they are short puts. Yes, you are right. In my original contest entry I said close out the 'entire position' if and when slv hits 40. So I think I need to go with that. I don't think we were allowed to change our original entries beyond fixed original. instructions.

So taking the SLV at this morning's open when silver broke 40 it went out for .12. The net on the calendar spread was 2.50 less .12 is 2.38 credit. On a cash investment of .50 this is a return of 376%. After a dismal January the Phoenix rises from the ashes.

Originally I wrote:

If 40 is not reached then exit on 2/31/2011 at the close.

Correction it should have been: 12/30/2011 instead of the nonsensical

And here is my corrected submission:

When investing one should consider a diversified portfolio. But in a contest the best strategy is just to go for it. After all you have to be number one.

With that thought in mind I am going to bet it all on Silver using derivatives on the ETF SLV.

SLV closed at 30.18 on Friday.

Buy Jan 2013 40 call for 3.45. Sell Jan 2012 40 call at 1.80. Sell Jul 25 put at 1.15.

Net debit is .50.

Exit strategy: close out entire position if SLV ETF reaches a price of 40 or better. If 40 is not reached then exit on 12/30/2011 at the close.

Brendan Dornan writes: 


Thank you very much for putting on the contest. The reason I started to write a blog is to document some picks, and hopefully build a reputation after a decade of being in isolation behind the screens. The contest enabled this goal. Thank you for the opportunity.

The contest entry updates earlier this year did not include my entries, probably because the access to quotes for the instruments added an extra degree of difficulty, so allow me:

1. Credit Default Swaps on:
· +99.44% : French Gov CDS
· +70.80% : German Gov CDS
· +99.88% : Italian Gov CDS :

2. Short the Euro + Far OTM put options near parity · +% : 1.3224 - 1.30469, not great: learned spot FX poor for tail event trades. 3. Long Put X-Warrants or CDS on any Hong Kong or Chinese Property Developer · +103.20% (20.64% X 5 for warrant use) Shanghai Property Index,

3a. or Credit Default Swaps Chinese 5 year Government Debt · +118.26%: China Gov CDS

Extra Credit: · + 214.25% : Short Copper:
o 4.4455-3.4695 NYMEX Copper HG
o ($111,375 - $86,725) = $24,650.00
· Short Iron Ore, Cement, similar declines (SWAPs would have done well) · + 52% : Short Japanese Industrials via CDS o Hugh Hendry's fund is up and can be a proxy · +32.96% peak, but plunged -60.80% below open : Cleveland Biosciences (CBLI) o Although unsuccessful, CBLI spiked higher amid the Japanese Nuclear Meltdown, serving its purpose as a hedge

Quotes :

Stanley Rowen writes: 

And the winners are…? I fortunately did not participate in last year's contest (my guesses turned out to be non-winners. But, I am indeed curious if there will be a major article posted to Daily Speculations dot Com with the winners? I'm looking forward to it.

Victor Niederhoffer comments: 

These entries from the contest for 2011 investments. These are the ones so far in the running. Would any like to add their selections to this list for judging.



 We perhaps have all heard about the following coin toss experiments on people. On each experiment, people have to choose either to play Game A or Game B.

Experiment 1): Game A: the player wins $1000 if head; wins $50 if tail. Game B: the player wins $500 regardless.

Experiment 2): Game A: the player loses $1000 if head; loses $50 if tail. Game B: the player loses $500 regardless.

With Experiment 1), people like to choose Game B.

With Experiment 2), people like to choose Game A.

While I understand this from psychological terms (humans have biases, are not rational etc.), I don't quite understand naturally or fundamentally about what really makes us do this. Hope someone can help explain.

An interesting thing I want to share here is the TED talk (July 2010) below shows that monkeys do in the same way.

Phil McDonnell writes: 

These sorts of thought experiments are played on student volunteers at college campuses. Students are notoriously impecunious. Assume a net worth of $300 or so and then calculate the log of the wealth ratio for each outcome. You will find that the most popular outcomes all follow the log utility function.

The mistake the experimenters make is to assume that $1000 is worth twice as much as $500 to a poor student. In fact it is worthless than twice as much. They assume a linear utility function when a non-linear log function is how humans really value things. 

Gary Rogan writes:

To understand why any of these biases work the way they do it's best to imagine hominids barely making it in terms of survival rather than even poor college students. There were long stretches where there were more than enough food or other resources, but there were also "funnels" where there were barely enough resources to make it through. We are all descended from the ones who made it through the "funnels". The ones who made the wrong bet left no survivors (or fewer as the case may be).

So if you've got just enough or almost enough to sustain yourself for the next few days but not after that, you realize that you need to do something soon or else you'll be history after those few days. You need to take a risk, but the weather is really bad, it's cold and stormy (or exceptionally hot, or whatever) and you can't venture out. To make matters worse though, a mildly menacing counterpart shows up and "asks" to share your meager resources. Losing half of what you have with great certainty may very well mean likely death, because you will probably be not in a position to "play" again after the weather gets better. If you calculate a 50/50% chance of winning the fight with your "friend" you will probably go for it, even if it means either a complete loss of your resources (and perhaps your life, but those are now equivalent anyway) or a mild injury.

And now a few days are gone, and your are out of resources anyway. The weather is a little better and you are now faced with walking towards a distant meadow where you are certain to find enough berries to sustain yourself for a few more days or pursuing a large but elusive prey (or trying to take something from a leopard resting in a tree with a fresh catch, or trying to fight it out with a different "friend" for his resources, but all of this uncertain), you go for the berries. You take a certain smaller gain vs. an uncertain larger one when getting enough resources means the difference between life and death.

As for how it comes about, we have neural networks in our brain specifically dedicated to evaluating rewards and costs. That's as proven of a fact as anything in neurobiology. Whatever biases worked based to get our distant (and not so distant) ancestors through the "funnels", that's pretty much what we have today.

Phll McDonnell adds:

I think one point that is overlooked in this discussion is that insurance companies do not prefer big bets. Instead they prefer to spread the risk and average out on many small bets. It is also the same reason that earthquake and hurricane insurance is so overpriced. They simply do not want highly correlated bets which increases the risk of serous capital impairment. If they write a lot of earthquake insurance in an area and the big one hits all policies come due at the same time.So they either ration the insurance by charging too much or they simply refuse to sell more than a certain number of policies in a given area.

In a way managing the insurance portfolio is a lot like managing a stock portfolio. You want to avoid bets with large possible negative outcomes and you want to avoid correlated bets. Rather you should take many smaller uncorrelated positions so no one position can wipe you out.

Leo Systrader comments: 

 Great points here. Many thanks for all the thoughts.

Question to Philip (maybe to everyone) about the non-linearity of human value. It is understandable, but I wonder if there is any scientific conclusion about it.

Let's see if we can use this theory to re-construct the experiment. Let's also assume the net worth of the players is $500. For simplicity, let's just try Experiment 1).

Experiment 1): Game A: the player wins $X if head; wins $Y if tail. Game B: the player wins $500 regardless.

We hope we can come up with an X value that is attractive enough for the players to choose Game A. Also we need to make sure that Game A does not have a significant favor of probability, so we choose Y in such a way that the expected value of Game A is not much more than that of Game B, which is $500. Apparently X will need to be much larger than 1000, so that means Y will have to be a negative number to balance out.

As the theory suggests, to make log(X) = 2 * log(500), X is about 25,000. Let's make the expected value be 600, we get Y to be -23800.

So then Game A becomes: the player wins $25000 if head; loses $23800 if tail.

Would that make people choose Game A? Not to me. Anything wrong in the above analysis?

On the other hand, we know that Kahneman has a theory saying something like "a person's magnitude of pain from losing amount D equals that of his joy from gaining amount 2.5*D".

So let's use this theory to reconstruct Game A.

Let's first decide for Y to be 300. Comparing with the 500 in Game B, the player considers a loss of 200 in Game A. So we need to make X a gain of 2.5 times 200 from 500, so we get X = 2.5*200 + 500 = 1000.

So now we have a new Game A: the player wins $1000 if head; wins $300 if tail.

I guess now it is very likely people would choose Game A over Game B. But we note that the expected value of Game A now is $650

If we make Y to be 50. It is a loss of 450 from Game B. So we make X =
2.5*450 + 500 = 1650.

Game A becomes: the player wins $1650 if head; wins $50 if tail.

Would they play it? Probably, right? In this case, the expected value is 837.5. 

Phil McDonnell responds:

Assume a starting net worth of 500.

Game A analysis: ln( (500+X) / 500 ) + ln( (500-Y) / 500 ) = expected utility.

Game B analysis: ln( (500 + 500 ) / 500 is the expected utility for both outcomes.

The thing is that we need to think in terms of wealth ration of the different outcomes. Take the natural logs of the wealth ratios. The wealth ratio is the wealth you start with before the bet divided by the wealth you end up with for the given outcome.

I took all the early propositions in the Kahneman and Tversky paper and calculated the logs of the expectations and found that in every case the participants were using log based utility function and were actually choosing quite rationally and correctly. It was the learned professors who were wrongly trying to analyze the problems using binomial probability analysis instead of utility theory.

In other ares of psychology there are various log based perceptions that have bee discovered. For example there is the concept of a just noticeable difference (jnd). For example you do not notice a sound is louder or softer until it changes by a certain amount governed by a log law. Same thing goes for brightness of light. One might add boiling live lobsters to that list.



In my area in the past year I have seen an increase of people holding signs that they are homeless and begging for money. I note more couples doing the same and note more women begging at intersections etc. Also note more men on foot with back packs that look "bummy" traveling through town. Most without gloves. I have given out several pairs now that it is colder in Southern Ohio.



Phil McDonnell writes: 

Every four years the number of highly visible 'homeless' people rises significantly in sync with the presidential election year. The number of real homeless people or residents of drug houses does not really change much but at this time certain unions and re-election committees hire low cost people to man the highly visible street intersections. In my area I have seen them change shifts at even hour intervals. When the replacement approaches about a half block away the one on the corner sees them and puts his or her sign down and casually walks in their direction and does not acknowledge the replacement in any way–as they pass–on the sidewalk. The replacement then picks up the hard luck sign and begins their shift.



 Lots of chatter yesterday about gold breaking through its 200-day moving average. Ron Griess says to consider the 300-day moving average instead. Has anyone done research on the benefits of using non-round-number moving averages, such as numbers slightly lower than 200 or 300?

Phil McDonnell writes:

I have tested them all from about 2 days to maybe 1000 days. Generally speaking there is little difference between two 'nearby' moving averages. If you think about it the 200 day has 190 terms in common with the 190 day average. Generally speaking they almost all work as long as the average is longer than about 100 days or so.

All such methods are weak at best. For example the 200 day yields about .04% per day if above the average. But adding a 50 day/200 day crossover reduces the yield to only .03%. In other words the so called golden cross does not really work.



 Real interest rates are back near their recent record lows (5 year TIP= negative 1.2%; 10 Year TIP= negative 0.15%); and gold's recent behavior is once again consistent with these facts. Riddle me this, Batman:

If I buy a 5-year TIP at a negative 1.2% real yield, and hold it to maturity, that means I am certain to lose 1.2% of purchasing power over the next five years. BUT: Were I instead to short a 5-year TIP at a negative 1.2% yield, and hold the short to maturity, does that mean I am certain to make 1.2% of purchasing power over the next five years? And, how can BOTH of these statements be false?

Private riddle for The Chair:

What do Galton, Batman, and Robin have in common?

The Riddler's False Notion:

Robin: Holy molars! Am I ever glad I take good care of my teeth!

Batman: True. You owe your life to dental hygiene.

Sushil Kedia writes: 

Logic Riddle is a misnomer for what is truly a contradiction. The presentation has a contradiction. In life, in markets there are no contradictions. Allow me to quote Ayn Rand from the Atlas Shrugged, "If there is a contradiction, check your premise".

Rocky, your logic is based on inflation remaining what it is right now the same also during the maturity and at the point of maturity of the 5 year TIPS! Market is not pricing that! Market is pricing inflation will come down! That's all. Check the premise, there are no contradictions.

Purchasing Power is a good term to help create this contradiction. Purchasing power will be Cash in your hand on day of maturity Divided by (1+inflation)^5 if I take the Annualized realized inflation readings. Realized Inflation readings five years from now will be known only then.

Rocky Humbert responds: 

Dear MisterMeanor:

1. You should check your bloomberg before you check your premise. These bonds are trading above 105 in price (even forgetting about the inflation adjustment).

2. That means it's possible to have not only a negative REAL YIELD but it's also possible to have a negative NOMINAL RETURN! (So much for the risk-less treasury market.

3. Your definition of purchasing power is unusual. Purchasing power has absolutely nothing to do with the cash in your hand. It's WHAT YOU CAN BUY with the cash in your hand. (Stefan — please elucidate this point).

4. Your statement "Market is pricing inflation will come down! That's all. Check the premise, there are no contradictions" is 100% UPSIDE DOWN. There is little justification for locking in a negative 1.2% compounded real yield UNLESS you have no alternative investment that does better. You need an inflation assumption of RISING INFLATION not falling inflation due to the way these seasoned bonds behave.

I reckon, back of the envelope, north of 3.8% compounded CPI…. is required to have these TIPS beat the bullet 5 year … and even then you still lose 1.2% of purchasing power (compounded) per year. If you want to bet on disinflation/deflation, you would short these bonds at 105 with an inflation factor of 226/220 with abandon, and buy 5 year bullet bonds to term.

Batman just ended. The Flintstones are on now.

Charles Pennington writes: 

That's a very nice riddle.

These bonds trade dearly I think because there aren't many other competing foolproof CPI inflation hedges.

Obviously if you short the bonds AND hold the short sale proceeds in cash, you are at risk of losing money. You short $1 million in bonds and hold the $1 million proceeds in cash. The bonds could go up in nominal terms by a factor of ten to $10 million. Meanwhile your short sale proceeds sit there in cash, still just $1 million, and when you cover, you lose $9 million. That's a loss in any terms.

Of course, if you could use your short sale proceeds to buy something that tracks the CPI without the built-in "negative carry" that the TIPS have, then you'd have a perfect arbitrage. But such a thing doesn't exist.

(Does it?)

Tyler Mcclellan comments:

A 1 year bond is four three month bonds.

A three month bond is a treasury bill financeable for cash as legally defined by the government at the rate set by the federal reserve.

If ex ante you knew that rate, let's say it would be zero for the next year, then if the one year note traded at 1 percent, there would be risk free arbitrage in buying the note (because the note is defined as acceptable collateral to get cash without exception at the overnight rate, it is perpetually fungible).

But all of this is true because arbitrage needs a unit that you're left with at the end, say for example cash, to make the calc.

I will not solve the last part of your riddle yet Rocky.

Let me ask, can the fair value of cash, the unit of account in arbitrage, which is merely the desire to lend known resources today for unknown future wants x years from now, change?

I don't want to lend at these rates.

I'd rather just have the money in the bank.

But if you know the money in the bank is guaranteed to earn zero shouldn't you buy the bonds and finance them at zero?

And if you know that the nominal bond is priced on the arbitrage condition above, and you believe that inflation will be three percent,t hen if you short the bond and earn the overnight rate risk free, and buy the tip and pay the over night rate risk free,and you hold these positions to maturity, since they are both fungible for cash, then you are guaranteed to earn the difference between future CPI and the ex ante break-even, which is an unknown variable free to take any value.

If you had an opinion on the future rate of inflation you could express that view only because of the other variable being priced to remove arb.And the riddle you speak of which seems to be, why would you commit ex ante to a negative real return can be answered by saying arbitrage of the other instruments demands that only the break-even and not the real rate is solved for by the buyers and sellers in the tips market.

Then What is the real rate set by? That is a very tricky question. The answer is in the above, but not obviously.

Duncan Coker writes:

I believe selling the 5 year Tip and buying the 5 year bond would do better than 1.2% (anti negative real rate) and would actually capture the inflation rate of around 2%. Empirically if you convert them to zero coupon for calculations then sell the 5 year tip around 105, buy the 5 year bond at 95, this makes for a compounded return of around 2%, 10 profit, holding to maturing. But then again there is a reason I don't trade bonds much.

Michael Cohn comments:

 I think of tips only in term of the real yield. It would take a very unusual set of circumstances to get me excited about investing in a situation where I can earn a negative real return. These bonds, if I recall all have CPI floors built into them so persistent deflation while sapping a bond of its built in inflation accretion can't turn the redemption figure below par. Each bond has a different sensitivity to the built up inflation component depending upon when issued. This is because the bond pays the same real coupon and the principal balance is adjusted by prior CPI (riding on a train so can't look up)

Certainly these bonds are one of the only high quality ways to hedge inflation. There are a number of global ways to do this but France, etc. Have bigger issues.

So what can happen when you short one of these. I wonder for those who can obtain info what the cost to borrow for the short is here. Obviously the overnight reinvestment is not a plus here.

Seems like I should expect to earn the real yield in this case which is a depreciation toward par but what is my short cost?

Tyler McClellan responds:

 I set up my example clearly.

The reason the thirty year bond cannot be arbitraged to short term rates is very simple. There is no way to credibly make the claim that short term rates will be X for thirty years. There is no institution that can impose the stick. I put very little weight on all the other things. Its the fact that short terms rates could be radically different in the future that generates the volatility not the other way around. Long bonds are very convex and thus this is a major reason they should have a lower yield, offsetting the term premium.

Your examples about LTCM and MF Global are meaningless. Their assets were never fungible at 100 percent leverage for the overnight rate. The Fed conducts monetary policy by making cash and bonds of certain maturities exchangeable for each other at certain overnight rates. To compare this to MF global where the bonds are explicitly not instantaneously fungible with cash (euros) is very odd.

Your example about RV strategies in fixed income is a good counterpoint to the limits of arbitrage. I agree that a one year rate 29 years forward is not subject to the same laws of arbitrage as other instruments. This is for a simple reason. The one year rate 29 years forward is not something that is dynamically set in the market by participants trading until equilibrium. It is an artifice of other things that are traded in this manner and thus it "falls out" of other asset prices.

In general arbitrage is the mechanism by which the sum of views in the market derive their equilibrium condition. You have to have a variable that reflects some view for arbitrage to do heavy lifting. I cannot arbitrage a one day interest rate 17.75 years forward for the simple fact that there are no views on that variable and thus it is merely an artifice that arises from the ecology of the market.

As for mingling "real and nominal". You do not understand your own analysis. The market already believes that we will have about 2% inflation and is nonetheless holding cash at 0%. So the accepting of negative real returns ex ante exists in many markets as a necessary fall out of accepting other variable. To say that this comes from the TIPS market is strange. All the tips market does is allow people to have differing views on the future rate of inflation. Everything else is determined by much more liquid (and therefore likely to be subject to arbitrage pricing) markets.

You will get negative real returns (your vaunted guaranteed decline in real wealth (a phrase that I dont understand)) ex ante in either the nominal or the TIPS market. If you reread what you wrote, you will understand this has nothing to do with TIPS.

As for your last question. You already understand the answer rocky. You get more than PAR day one for being short the TIP.

If you

1) take all those proceeds and reinvest them at the fed fund rate at the future path

2) and if inflation is equal to the breakeven-rate

3) then you will lose the real value of the capital lent to you at exactly the same rate that the market says the real value of the capital lent to you must go down ex ante.

Put another way,


1) you must earn the nominal return priced in the market,
2) experience the inflation rate priced into the market,
3) and deposit your funds at the monopoly price set by the FED,

then you are indifferent between the two outcomes and are guaranteed to earn the same negative return. Which is of course why there is a market. All of which i wrote a long time ago as a explanation for why it might make sense to be short tips but if an only if you could tell me why based on your estimate of the above three variables. Any speculation on the real rate is meaningless, it is not a variable one can have a view on outside of the above (if and this is a key assumption, cash money from the fed reserve is the unit of account you wish to sum all the steps across. Its very possible the real term structure of other commodities is different)

Rocky Humbert responds:

I will address your many points more specifically when I have some time. But I will make a very simple observation (which you ignored)….which has to do with the interactions between inflation and tax policy and the zero interest rate boundary problem.

Let's assume a simple Taylor rule and that the fed sets overnight funds at inflation+100 basis points. Let's further assume a marginal tax rate of 30%.

Case I) Let's assume that inflation is running at 5%. Then fed funds is 6%. Then my after-tax nominal return = 0.7x 6% = 4.2% and my after-tax real return is negative 0.8%.

Case II) Let's assume that inflation is 2%. Then fed funds is 3%…and my after-tax nominal return = 0.7×3%= 2.1% and my after-tax real return is positive 0.1%.

Case III) Let's assume that inflation is NEGATIVE 2%. Then fed funds is 0% … and my after-tax nominal return = 0%, but my after-tax real return is positive 2%.

This is a clear example where real after tax returns behave in counter-intuitive ways…. and so the apparent negative return on TIPS might have less to do with inflation expectations per se, and more to do with the tax effects…. (or more succinctly, an investor in Case III above would be willing to buy a tip that has a negative 2% real yield and would be indifferent to case II, where the same TIP has a +100 real yield.) Just a thought

Tyler McClellan writes:

Very true. I once worked with Paul McCulley on the tax implications of same. As you never posed that as a question I didn't address it.

I agree with your points and thing it is a modest contributor the the current equilibrium pricing.

 Philip J. McDonnell writes:

I think one point that has not really been made in this discussion is that TIPS are paid back at the greater of inflation adjusted value or par. This means that they have an implied deflation protector built in.

It is like a deflation put which has intrinsic value in and of itself. In many ways we are in a deflationary environment caused by the great credit bubble unwinding throughout the world economy.

Gary Rogan comments:

I just scanned the riddle discussion. It seems to me that the reason you can't make money shorting TIPS is like the obviously idiotic action of shorting dollars in dollars. Let's say you decide to short a million dollars, and sell it to someone for a million. That's what shorting is, and yet you are in exactly the same situation as you once were.

If TIPs are losing purchasing power against a basket of commodities, but dollars are losing it faster, if you short TIPS you get something that loses purchasing power even faster than TIPS, hence no gain. If you could find a way to get paid for your shorted TIPS with a basket of commodities, and there is high inflation, you can buy them back with fewer commodities, so you make a profit.



 A Spec notes: I have found that markets are moving in the direction of the announcement to an inordinate extent recently. And relates it to who knows what and the sneakers he sent the fake Doc and the book he sent to Patrick Ewing, the most sullen player to ever put on baggy long shorts, asking these two to change places. But Rocky is doubtful and demands to see the evidence.

Philip J. McDonnell comments:

Personally I am waiting for Occupy the White House. But that is not likely to come from the ACORN backed OWS movement. The Chair can use me as a human shield. But in a sense I agree with Rocky but for a different reason. I assume you are speaking of a significant correlation regarding such pre announcement movements. The practical problem is that all one can really assert is that someone figured it out in advance. For example the jobs number can be gamed by looking at the number of jobs posted on or even If the market moves in advance is it because someone leaked or someone legally gamed it using a little cunning. Personally I lean toward the conspiracy/leak theory as more likely but it fails the legal hurdle of proof.

The other problem is that legal standards require proof beyond a reasonable doubt, but we trade on mere correlations alone. We also know that correlation does not imply causation but it is usually good enough to trade on.



I call your attention to this article:

Risk on the rise as political leaders give in to mob rule

By Ray Dalio, President, Bridgewater Asssociates Inc.

[link requires registration]


We are in the midst of a deleveraging, we are nearly out of [fiscal and monetary] ammunition and we are at each other’s throats. … being at each other’s throats is our biggest problem.

[In such situations ] frustrations increase, the established ways of doing things come under attack and frustrations over the ineffectiveness of government creates the perceived need for someone to gain control of the mess. Plato spoke of this dynamic. It was the reason Hitler was elected in 1933.

Matthew adds:

Mr. Dalio recently appeared on Charlie Rose . [37 minutes].

Tim Melvin writes:

This much publicity is inevitably followed by "bad things".

Philip J. McDonnell comments:

I agree with Tim. The tone of Mr. Dalio's screed is strongly doom and gloom.

I am guessing he is bullish though because he urges cooperative action.




 The movie Moneyball is in theatres. This article by a leading sports economist looks back on the impact that Moneyball the book has had since publication in 2004.

It features an application of the point that I've often seen made by the Chair, that once an anomaly gets published it disappears:

We thought there was a decent chance that we could refute the economic claims in Moneyball, in particular that players with high OBP were under-priced in the labor market. Any card-carrying economist knows this is inconsistent with equilibrium in a well-functioning, competitive labor market, and were not baseball teams intensely competitive? But instead, Jahn and I found that high OBP players did come cheap, relative to the contribution of their skill to winning baseball games. Intriguingly however, we found that the "OBP discount" vanished in 2004, the year that Moneyball was published.

It makes one question the decision of the Oakland A's to cooperate with the book. Although it may have been a matter of time for the other teams to catch up anyway, it seems that sometimes vanity can be costly.

Stefan Jovanovich writes: 

I live in the SF Bay Area and am a thorough baseball addict. When I should have been attending law classes at Berkeley in the 70s, I was loitering at the Oakland Coliseum watching Dick Williams and Alvin Dark (one of the truly obscure great figures in the history of baseball) manage the A's to their championships.

Moneyball is complete hype. The theories of value - OBP, for example - are sound but hardly original. They are the substance of what Dark and Leo Durocher (another great figure) and Casey Stengel (the greatest of them all) knew from experience and observation. What Billy Beane missed (but none of those managers would have) is that the real "Moneyball" is putting the customers' butts in the seats. While Beane has been practicing his genius, the A's have become a chronically weak franchise (it remains in as poor financial condition as the Seattle Mariners and Kansas City Royals and, until this year, Pittsburgh Pirates). At the same time, across the Bay, the Giants went from being literally bankrupt (they were going to be sold and moved to North Carolina) to becoming the owners of the best stadium in the country (privately financed, no less) and the 5th most valuable franchise. How? They signed Barry Bonds. If Yankee Stadium is the House that Ruth (and then Reggie Jackson) built, AT&T Park is the stadium that Bonds built.

Phil McDonnell writes:

I agree with Stefan that one very rational reason to pay up for a Bonds or Willie Mays was that a home run is a lot more exciting than watching a guy walk. Home runs sell tickets and that is ultimately good business. On the other hand managers restricted to a below average budget can improve performance better by adhering to Moneyball principles.

Another often used strategy of small market teams is to bring along recruits, especially young rookie pitchers. Seattle uses that strategy. They are little more than a farm team for the Yankees. Any time they get a young rookie pitcher that shows any promise he is immediately sold off to a big market team, with the Yankees being the most likely buyer. A big part of their business model is to collect millions from the Yankees for selling off their low priced talent.




 Perhaps the Chair has not yet been apprised of (or, more likely, refuses to lower himself to comment on) Obama's new proposal to tax "millionaires" at a new and higher income tax rate, which Obama apparently plans to campaign on by terming it "the Buffett Rule" (cf "the Volcker Rule), based on the Sage's recent op ed piece to the effect that he should pay a higher tax rate to bring him up to the rate paid by his secretary.

In the course of attempting to explain to Elizabeth and other sensible but tax-unsophisticated family members why Buffet's op ed piece is fraudulent and self-serving, I have found the following the clearest and most effective explanation:

Buffett has a net worth of $70 billion. I have read that based on the fairly modest net capital gains he realizes each year (all he needs to live extremely well on) he pays income tax of about $7 million a year. Thus his yearly income tax represents about 1/10,000 (0.0001%) of his net worth.

The average young, single working stiff makes, say, $60,000 a year, and if he's lucky has a net worth of perhaps $20,000. He might pay almost $20,000 a year in income tax, which would mean his yearly income tax represents almost 100% of his net worth.

And let's take an older middle-class family with a hard-working husband and wife making a combined $250,000 a year, who have saved and purchased a house and have some other investments. If they have been highly successful in their house and other investments, they might have a net worth of perhaps a $1 million. If they pay approaching $100,000 in income taxes, this would mean that their yearly income tax represents almost 10% of their net worth.

To reprise each year's income tax payments at current rates:

Young working stiff, 100% of net worth.

Hardworking H& W with successful investments (well within Obama's "the wealthy"), 10% of net worth.

Buffett, 0.0001% of net worth.

So Buffett's unselfish proposal is: That the middle-class family paying 10% of their net worth each year pay significantly more. That perhaps even the young working stiff pay slightly more. And that Buffett himself pay a little more but since his relative income is so low, still close to 0.0001% of his net worth.

Yes, let Obama run his campaign by lauding Buffett for his unselfishness, and for Buffett's explaining tax fairness to the public in such clear and folksy way.

Phil McDonnell adds:

I agree with Dan that the Sage's comments on this are completely disingenuous. He will never get hit by the tax he proposes. He only makes a salary of $524k/yr because that is what he chooses to take. Rich people have a great deal of control over how they get their income. They can hide it in corporations that do not pay dividends. They can choose not to take capital gains in years with high taxes on such. Alternatively one can take capital losses as offsets. They can choose to pay themselves a dividend.

In Buffet's case the vast majority of his money will never be converted to capital gains because it will be donated to the Gates foundation to provide a nice future income for his kids and their kids. It will never see estate taxes either. The idea that the problem is all about the tax rate is a deceitful canard.



The scientific method has two parts. There is theory, which requires knowledge and intuition to posit a cause and effect, and there is testing, collecting data to determine whether the observations refute the theory. If I understand your point correctly, empiricism is necessary but not sufficient. There should be a theory that is not entirely based on the observed data. As an imaginary example, “The S&P 500 is likely to decline on Friday afternoon because day traders are biased to the long side and want to be out of the market before the weekend” is better than “The S&P 500 was down on 19 of the past 30 Friday afternoons”.

Ralph Vince responds: 

Steve, yes, but the premise, the cause, needs to be proven. “The S&P 500 is likely to decline on Friday afternoon because day traders are biased to the long side and want to be out of the market before the weekend” needs to be proven as causal, not merely posited as a possible cause.

Frankie Chui writes:

Yes, I always end up asking myself “why does it not work anymore after it has worked for so long?” when the moment I trade it the system stops working. It has also happened to me quite often where I backtest a strategy, everything seems ok, trade it for 2-3weeks and that’s the end of that system. Therefore, I am now experimenting with optimizing parameters in systems more frequently, perhaps once every two weeks on a rolling basis. Optimize two weeks of data, trade it for a week, optimize the past 2 weeks again, trade it for another week. Of course the 2 week/1 week time frame may not be the best (I just randomly chose it), but has anyone ever done anything with this kind if approach? I’m curious to see if this will work for day trading. I am new in mechanical trading, but I’m very curious to know if optimizing data fast enough will allow a trading system to work better and longer (for day trading).

Jeff Watson writes: 

Frankie, you’re running up against Bacon’s ever changing cycles, which tend to render systems obsolete.

Phil McDonnell adds: 

There is an insidious danger when you use optimization. The optimizer will fit the system to the data too well. It will never perform as well out of sample as in sample. It becomes especially important to use tests of statistical significance when you do optimizations.

The optimizer can actually create a multiple comparison problem in some cases. For example if you tested, looking for seasonality and wanted to find which month was the best to buy it would create a multiple comparison bias and any test for significance would have to have a much higher threshold than if you just tested September.

One way to judge a system and evaluate whether it will continue to work is to plot out the equity curve. If your testing assumes an equal sized investment each time then the system can be plotted on an ordinary arithmetic scale. If you compound it should be plotted on a log scale. Either way the most desirable system would be a system that looks like a smooth line going monotonically up to the right as time passes. If it starts to roll over then it may be a system about to fail.

Paolo Pezzutti writes: 

The system should be quite robust. It should work pretty well with a sufficiently wide range of values of parameters. There should also be few parameters avoiding curve fitting.




 In a survey of doctors on a website I follow, 80% of responding doctors answered no way would they allow their patients to email them.

This was the response I posted:

To the 80% of responding docs who say "No way": If you wonder why many patients develop major hostility to doctors' office procedures and to doctors themselves, and why the public is happy to stay silently on the sidelines while the government and insurance companies take over control of doctors' working lives, could it be that doctors (who for 100 years had control of their practices and refused to make them patient-friendly and efficient) have failed to enter into the 21st century? And regard it as perfectly acceptable to impose inefficiency, frustration and wasted time on patients by not letting them communicate with the doctor but requiring them to make an office appointment (probably 3 or 4 hours with travel to and fro, long office waits, etc) for every question or matter?

I see nothing wrong with a doc charging for email or telephone time. Those patients wishing to use email or telephone should be willing to pay the time charge, regardless of whether such charge is covered by insurance. But if our profession continues to lord it over patients by refusing to allow them what every other profession and all of modern life does, doctors will deserve what they get in the way of government and insurance oversight and regulation.

Charles Pennington writes: 

Chiming in, that is a pet peeve of mine. What other profession won't take email? Lawyers, dentists, accountants, etc. all communicate by email, of course. Doctors make it even worse by making you communicate with them only via a voice-mail maze that begins with "If you are a physician, press 1; otherwise, your call is very important to us so please remain on the line…"

Russ Herrold comments:

I'm with the doc's here.

When the tears are flowing, everyone says they are willing to pay, but without getting into the business of FIRST AND AT THE ONSET, having a Retainer Agreement, unilateral right to draw it down upon presentation of statement, Mandatory Arbitration clause, deposit for fees in the Trust Account, all one does is lay a background for a fee dispute complaint or malpractice counterclaim to a suit to collect those fees. It's not gonna happen as a general practice. The doc is caught between the rocks of patient desire for immediacy and convenience; the professional obligation 'not to miss' something that in hindsight seemed obvious; and the fact that insurer reimbursement for web and email oriented 'treatment' lag.

Having had poor service (breaches of patient confidentiality, outright prevarication by nursing staff, and failures of delivery of test results repeatedly and after specific instruction) in the care of a wound, all since May of this year, from the standpoint of the patient, I want there to be a formal paper trail (not email; not call center notes in some database, forgotten and closed; not some other ephemeral media) … a well drafted letter explaining the issue, a file CC, and a cc to the supervising agency (hospital system privacy officer, nursing board, 'authorized provider' certification entity), and an equally formal response (or in its absence, proper escalation on my part).

Unreasonable, I know, but progress is made on the backs of unreasonable people.

The same goes for lawyering. If a client cannot keep and will not pay for an office visit, or meeting at other venue of their choice, to permit the open-ended probing that proper representation requires, they won't be MY client very much longer, as I cannot properly represent them.

Alex Forshaw writes:

The fact stands that interacting with doctors is a pain in the ass from the second you enter the door. They do not face nearly enough competition. There is no bigger beneficiary of protectionism in the entire country. The lack of competition has meant they face no evolutionary pressure. I hate "socialized medicine" as much as anyone but US doctors are as much culprits in their own demise as the tort bar and all of doctors' other favorite bogeymen.

George Zachar adds: 

In my conversations with doctors, I've been told the potential legal and regulatory liabilities risked by patient email contact are vague and large, leading them to simply shun the practice.

Phil McDonnell writes: 

Regular email is not a secure medium. Privacy regs hamper a Doc's ability to use email. Most will call you on the phone and/or write a letter with results. That is why expensive software with encryption is required that often the smaller practices cannot afford.

Gordan Haave responds: 

Sure that's what they say. But it's BS. How is the fax or telephone somehow more secure than email?

If the issue is confidentiality, why is it that Lawyers will email you but not Doctors?

There is one other group that won't send emails: The IRS.

I am in the middle of a personal and business audit, and you can't email the IRS. It's very inefficient.

To me this is just further proof that Dr's collectively are not the saints they claim to be, but rather just a cartel that uses wildly inefficient systems to extract rent's from consumers.

Dan Grossman writes:

I am surprised that a few otherwise highly astute Speclisters so easily accept doctors' excuses for refusing to permit email. As a service to the medical profession and to our country (and in time for inclusion in the President's speech tonight as a new regulation under the Patient Protection and Affordable Care Act), I have drafted and present below a few simple groundrules that a doctor can require a patient to accept as a prerequisite for emailing him.

"A Patient wishing to email Doctor must indicate his acceptance of the following:

1. Complex or detailed matters require an office visit. This email is for minor procedural, scheduling and prescription renewal matters.

2. Doctor will attempt to look at reasonable numbers of emails as time permits but because of his busy schedule cannot commit to read or deal with every email. Any information Patient wishes to convey with certainty must be conveyed by other means.

3. Emails are not secure and should not include sensitive personal information. They will not necessarily be presevered or included in Patient's medical file or record.

4. Patient agrees to pay $20.00 for each ten minutes or part thereof Doctor spends reading or dealing with emails from Patient, regardless of whether the amount is reimbursable to Patient by his insurer. Medicare and Medicaid Patients unfortunately are not eligible to use this email since such programs do not permit email charges. (Doctor regrets this and asks that you please take up such inefficiency with the Government rather than with him.)"

With regard to 3, doctors or their office assistants can instead spend 15 minutes setting up free encryption, as others on the List have already pointed out.






I'm reading old posts on Daily Spec, specifically an interesting discussion on the topic of Stops, that took place in 2003.

At the end, Faisal mentioned a paper of Dr. Eric Berger on calculating the probability of hitting the barrier (stop or price of the knock-out option).

Could anyone share this paper?

And, any other improvements on the discussion?

P.S. What I find difficult in those answers about not using stops, "no stops required", "stops will double your probability of loss", etc, is the time horizon. We have to give profit to our clients every month, otherwise they will fly away to another firm. How does a "no-stop" policy deals with this? And… in the event of a year such as 2008, (or 2011, in Brazil), a no-stop approach isn't a sure path to greater loss?

And for those not using stops, what's the time horizon? Do they NEVER take a loss? When will the loss ever be taken? (They put that part of their portfolio in a box, never to look at it again?)

Phil McDonnell writes: 

In introductory Stat there is almost always a section on calculating the probability of a certain sized observation in a normal distribution. That calculation tells you the probability of being at or above a certain level after a fixed period of time. To calculate the probability of having touched that level at some time during the fixed period of time simply double the probability. The reason is the Reflection Principle. For every path which wound up past that level, there is an equal and opposite path that was 'reflected' back from the level.

The same thing applies to stops on the downside. Note that all of this does not assume an infinite time period, but rather a fixed period of time - kind of an investment planning window if you will. The reason for this is that the variance always grows as time is extended. Given large enough variance then almost any price will be hit eventually both up and down.

Newton Linchen replies:


This is the subject that I have read several times in your book, but still can't imagine how this would fit someone who must give monthly performance reports, instead of a well-capitalized investor who can stand some period in the red…

This approach doesn't seem to fit short-term trading (trading with less than 30 days), unless you exit the position until the end of the month, which would be your final "chance" for the position to work.

And in the time horizon of one month, one would have to ensure protection against the ineluctable downside.

Phil McDonnell adds: 

The main point is that stop losses will double the number of losing trades at your 'maximum loss' level. So you will report more losing months. Is that what you want? So if not stops then choosing a prudent position size for a trade is really the way to control risk.

Most of my comments are made on the theoretical basis based on what should happen. But in fact in my empirical tests, reality is worse. Using stops actually hurts expected returns in most cases. Theory says that should not happen. Theoretically expectation should remain unchanged if you use stocks but that is not the case.

Attached is a little table excerpted from Larry Connors and Cesar Alvarez's book Short term Strategies That Work. It shows that for a particular simple system the average P/L was .69 per trade. with 69.81% winners. But when you add a stop at the 1% level the return plummets to .19% and only 26.89% winners. For all stop levels tested up to the 50% level the returns were lower when one added stops to the strategy.

So looking at probability per trade and return per trade stops seems worse. But theory says that they may help by reducing variance. So far as I can see that is the only good thing about them.


Dave G writes: 

Hedging makes more sense than the antiquated and disgraced use of "stops".



 When we draw a typical line chart we connect the lines. The stock may have traded at 7.00 and the next trade was 7.01. But nothing happened in between. There was no trade. Nevertheless the line drawn gives the illusion that the price action was continuous and there was a smooth transition from 7.00 to 7.01. A former collaborator of the Chair, the late M.F.M. Osborne used to argue that charts should be drawn as dots -one dot for each transaction marking its price on the vertical axis and time on the X axis. There should be nothing in between because nothing happened — just a dot cloud.

Osborne was also the first modern author to demonstrate the log Gaussian distribution as a good model for stock prices. Naturally because he was a physicist, another Professor of Finance usually gets the credit.



Today I was asked when to use logs and when to use a linear growth model. My answer follows. Hopefully this is a meal for some.

The formula for continuous compounded growth is:

e^rt where e is Euler constant (2.72..) r is the rate t is time

If you are assuming a constant growth rate model then this is the correct model and not a linear model. In that case you would take the log (ln for financial work). The model then would be linearized by taking the logs. So you would regress:

ln next period sales = b * ln( last period sales) + a

Then to reverse ln( sales ) you would just take exp( ln(sales) ) to get the dollars or units. But the idea is to do the regression in log space because it is linear there and when you have your log answer convert back to the desired real world units.

the model could also be:

ln( sales ) = b * ln( t ) + a

The general rule is when you have arithmetic growth then a simple additive linear model is correct. when you have compound growth then the log linear model is the best.



 As specs we snicker at the lottery player, he is a sucker. We smile when we hear how the crowd is routing for the hometown favorite when we know odds favor the other side. We hopefully carry out the canes when the crowd is tossing down the tickets in disgust, we sniff for value when there is no value there–so says the financial press.

But what is our own attachment to this concept–catching a falling knife, holding a loser, getting involved in some fiasco stock since the market is beginning to bore, riding a coattail that turns into a skid, throwing in "just this once"? Why do we fail to follow our own good sense from time to time?

There must be a thrill or an ego impulse underneath this temptation to turn from the path and into the wind of long odds–"cause we can handle it".

Victor Niederhoffer writes:

Our own attachment should be based on quasi scientific study., not riding a coattail. 

Ken Drees writes: 

True, but do we fasten our own rickety reasons from study based on the past which has no real reason to work in the future other than past frequency, tendency and relationship, and thus delude ourselves into thinking that our proof more than compensates for the new speculation? And if finding tendency and causality can be negated by the speculative theme of ever-changing cycles, and also trumped by the unknowns –how do we believe this and thus risk capitol?

I think that the chair has outlined many great themes in speculation, almost like laws:

1. Methods must be tested in order to find relationships of validation.
2. The laws of ever changing cycles are present in the market at critical-mass moments.
3. There is a high degree of relationship between markets and natural systems. What can be said of the "unknown"? What is this speculative doomer, the whispy apparition above the pond at days end? What law can be attributed to this unknown force that seemingly has uncanny timing?

Ralph Vince writes: 


I think it's simpler than that.
-The past gives us a proxy for the distribution of what can happen.
-We can amend that distribution of what can happen based on how we foresee the future diverging from the past
-That very distribution can now be used to determine how aggressive we might want to be withing a given risk (drawdown) constraint.
-If we don't exceed that drawdown constraint, and our distribution is reasonable of the future, the profits accrue.

Gibbons Burke writes: 

 I wrote this in a previous thread about the difference between speculators and gamblers, and I think it holds true: "Gamblers are willing losers who occasionally win; speculators are willing winners who occasionally lose."

At bottom, and at one time or another, most of us are gamblers. It takes a very disciplined, brilliant, and perhaps unrealistic person to only play games where the odds are in our favor. The reasons many engage in knowingly losing propositions are greater than the stars in the night sky in rural flyover territories. Entertainment and division rank high among them, sociability, peer pressure, guilt about the money they are risking (unconsciously disposing of it), fear of success, self-disgust, compulsive addiction to the stimulus-response loop, adrenalin junkie.

But all these are all proxies for the thing everyone is really seeking, usually unconsciously: a desire to be in union with the godhead, the creator, the divine purpose. As St. Augustine wrote in the opening lines of his autobiographical "Confessions": "You made us for thee, Lord, and our hearts will be restless until we rest in thee."

Phil McDonnell writes: 

When I ask people why they do not invest in a guaranteed savings account or short term t-bills they usually respond that they are too boring. And they are, or at least used be because they could not lose. Most traders unconsciously seek to lose because it represents action and excitement. While I think the usual arguments that it takes assumption of risk to increase return have validity, at the sub-conscious level the desire is really no more complex than risk seeking for excitement.

Ralph Vince writes: 

I agree — this is what frightens me about individuals who are out investing their own money — no kid needs to relive the station wagon as home for awhile as a consequence of Dad's gambling proclivities.

I'm beginning to think institutions are just the individual lambs in the wolves clothing of trading with other's money.And the reason I say this is because, again, not only can they not articulate their criteria for being involved in this, most criteria involve the ultimate metric of "what is the probability of getting smacked x% in the coming y period(s)."

And I don't see ANY of them operating that way. Rather, their risk metrics are ones that don't really tell them anything, analgesic salves that do not stave off the infection. 

Russ Sears writes:

Personally, my record shows that I am more often guilty of trying to catch the falling knife on an individual stock and on an option trade, than I am on an allocation strateging or long term market timing basis. I believe this is because of two reasons, One reason is I am just to gullible for a single stock, and buy the story the more it goes down the more I am convinced it will pop, often averaging down. I believe most businesses as a whole are running honorable businesses, that is they are trying to do what is best for the long term. However, the exceptions happen and there are frauds/crooks and businesses that have agency problems (businesses run for the executives or employees short term interest) The second is that I am often guilty of believing that the studies timing is much more stable than it actually is. It may be that the market is over sold and will bounce back, this results is the crux of my "edge, but the time period is often part of the ever changing cycle.

I have helped this some by giving myself some boundaries or a do not buy or sell if held rules of:
1. If the market believes the board or leadership is not acting in the stockholders interest, based on key decisions they have made.

2. If there are union grievances making the press.

3. If there are rumors of fraud or accounting problems.On options buying time or gamma seems to work better. And in general I have learned to not do as many option trades as I am not as good at them as I think I am.

These rules are simply my adjustments for my own shortcomings.

Jim Sogi writes: 

The heuristic at work here is risk aversion where one would rather face a known small risk with bad odds of a big win, rather than a 51% favored odds with a risk of a large loss. It's very hard to overcome the natural tendencies.



 I don't know much about options, but can anyone explain to me why expiration days seem to have lower ranges and absolute volatility? I haven't quantified this but that's my impression and I read something about it. Are there figures for biggest option strike. I've heard stories of why this might have some sort of effect on underlying price. Thanks.

Sam Marx answers:

One of the reasons is what is called "pinning" where stocks close to their strike prices will trade around that strike price and get pinned to it. This is not true in all cases but occurs often enough to decreases stock swings.

There have been scholarly studies on this and you can read more about it in the book Trading Options at Expiration by Jeff Augen.

Phil McDonnell adds:

I do not actually know if expirations have lower volatility and reduced ranges or not. But IF it is true it may have something to do with pinning. Pinning has been identified in several academic studies as being a real phenomemon. Basically it involves the stock closing at or on a given nearby strike price which happens to have a large open interest. Essentially the stock gets stuck trading at the round number with greater likelihood than on other days.

Option strategies such as sold straddles, calendar spreads, butterflies all reap their maximum profit at a particular strike. So the incentive could be there for flexionic manipulation. Or it could simply be a product of all the competing cross currents which occur on those days.

Sam Marx replies: 

It has been tested and reported in academic studies.

As a starting point I refer you to Trading Options at Expiration by Jeff Augen.



 After 5 years or so, I finally got to the point of confidence in conducting basic quantitative studies. (Very basic…)

While reading again Philip's book "Optimal Portfolio Modeling", I got stuck in the following sentences:

"Professor Niederhoffer was just such a divergent thinker.

His help and guidance taught me to see things at their simplest. That is the essence of his approach. His enlightenment also helped me to learn how to avoid the numerous pitfalls that can arise in quantitative studies. *In fact, one of the things he taught me was what not to do on a quantitative study*."

I couldn't help to think what such advice would be…

And what the Specs thinks of what one should avoid while performing any counting studies.

Steve Ellison writes: 

Be very careful to consider only information that was known at the time. For example, when doing a study that uses the high price of the day, you cannot know that any price will be the high of the day until after the close. Similarly, you cannot act on the closing price or anything based on the closing price, such as a moving average, until the next day.

Beware of data mining bias. If you test the same set of data enough times, you will find some results that appear to have statistical significance, but occurred just by chance. For example, I analyzed the most favorable trading days of the year. There are an average of 252 trading days per year, so one would expect 12 days to have results with p<0.05 just by chance. You need to control for data mining bias either by setting a more stringent p threshold or testing out of sample. Any time you have considered multiple strategies and selected the one with the best results, you should assume that part of the good result was by luck and expect worse results going forward.

Statistical significance is not necessarily predictive. In an era of much quantitative analysis, a regularity may not last long. It has happened more often than I would expect by chance that I found a pattern that was bullish or bearish with statistical significance, and the out of sample results were statistically significant in the opposite direction.

Bruno Ombreux writes:

Data mining bias can be experienced in the most vivid manner with the new Google correlation engine. It can come up with some of the weirdest, actually impossible, correlations. Google correlation results are more illustrative and striking than any theoretical academic stuff about multiple comparisons.

Phil McDonnell writes:

An incomplete list of things NOT to do on a quantitative study:

1. Avoid retrospective data. Many fundamental data bases have retrospectively adjusted data. sometimes the data is adjusted years after the fact and could not possibly be known at the time.

2. Avoid retrospective price data. Many so called quants pat themselves in the back for 'correcting' their data after the fact. Any valid study must include the data as it was known at the time.

3. Avoid the part whole fallacy. There is more on this in the Chair and collab's book Practical Speculation.

4. Use non-parametric/robust statistics to avoid fat tail issues.

5. Simplify your studies to a very small number of variables.

6. Avoid looking at simultaneous relationships. They are descriptive and not tradeable. Instead concentrate on predictive relationships.

7. Avoid indexes, rather use prices that actually trade.

This list is only some of the pitfalls and traps to avoid in doing a proper quantitative study.

Newton Linchen writes:

It has happened more often than I would expect by chance that I found a pattern that was bullish or bearish with statistical significance, and the out of sample results were statistically significant in the opposite direction.

Isn't that annoying?

Doesn't it pushes us to the other side of the coin, of pure "tape reading", etc?



 Looking for some stats to put on the table for Basketball I found this analysis of actual to predicted wins in hockey.

Ties occur more than predicted. It does not appear the method is adjust to consider the power play at the end raise the chance that a tie occurs than the poisson distribution would. That is more goals are scored at the end of a 1 point difference game than throughout the rest of the game.

Other low scoring games like baseball do not follow the poisson distribution. In Baseball for example the time is unknown and each team takes same number of chances to reach a base. The more on base you have the more chances you have to score. (the past events effect your chance of scoring.

After reading this blog, the question I asked was how would you best simulate a model of a basketball game. I suspect those that control the ball and control the pace, (the time) the best win more than the teams have a good night shooting, because the law of large numbers smooths out the out come.

What is the W/L stats for those teams that steal the ball first?

Phil McDonnell writes:

We have discussed the arc sine distribution here before. It is that U shaped distribution where the major probability of occurrence is in the tails. But it can apply to the question of how often the first team to score wins as well. The idea is that a surprisingly large proportion of the time in a random walk the walk will go positive or negative and never look back The arc sine distribution comes into play in looking at how many times you will cross a given level (including the zero level).

The idea would be to look at the first team to score as creating a point differential of +n. Then the arc sine predicts that a surprisingly many games will turn out with the point differential never going below zero.




The Winners of the least effort contest were jointly in a tie. Mr. Gary Rogan and Mr. Steve Ellison. I will split the prize between them. The creative and physical ideas of Mr. Rogan were very excellent and best of all, but there was no testing. Mr. Ellison gave a great test, and a complete answer, but Rogan can't be denied his place either. vic

I'll give a prize of 1000 to the person or locus of his choice that comes up with the best way to test the principle of least action or a related principle of least effort.

It's in honor of my grandfather. Whenever I'd ask him which way he thought the market would go he'd say, "I think the path of least resistance is down" starting with Dow 200 in 1950. We need some more quantification around here.

You might consider max to min or a path through a second market back to home. Or round to round? Or amount of volume above or blow. Or angle of ascent versus angle of descent. Or time to a past goal versus the future? Or some mirror image or least absolute deviation stuff?

Sushil Kedia writes:

With utmost humility and clearly no cultivated sense of any derision for the Fourth Estate, I would submit that since it is the public that is always flogged and moves last, the opinions of all media writers, tv anchors are the catalysts, the penultimate leg of the opinion curve. A test of the opinions of the fourth estate on the markets would provide the most ineffective wall of support or so called resistances. Fading the statistically calculated opinion meter (if one can devise one such a 'la an IBES earnings estimate a media estimate of market opinion) and go against it consistently over a number of trades, one is bound to come out a winner. Can I test it? Yes its a testable proposition, subject to accumulation of data.

Alston Mabry writes:

The following graph (attached and linked) is not an answer but an exploration of the "least effort" idea. It shows, for SPY daily since August last year, the graph of two quantities:

1. The point change for the SPY over the previous ten trading days.

2. The rolling 10-day sum of the High-Low-previous-Close spread, i.e., "max(previous Close, High) minus min(previous Close, Low)". This spread is a convenient measure of volatility.

Notice how these quantities move in tight ranges for extended periods. These tight ranges are some measure of "least effort", i.e., the market getting from point A to point B in an efficient fashion. As one would expect, the series gyrate when the market takes a temporary downturn. Also note how when one of the quantities swings above or below it's mean or "axis", it seems to need to swing back the other way to rebalance the system.

Bill Rafter writes:

 This nicely illustrates how relative high volatility is bearish on future price action.

Jim Sogi writes:

The path of least resistance would be the night session. Low liquidity allows market mover to move market. Every one is asleep. Dr. S did a study some years ago. Updating shows total day sessions yielding 94 pt, but night session yielding 232 points. Don't sleep…stay up all night or move to Singapore. Recent action is in line with hypothesis.

Bill Rafter writes:

Haugen's "The Beast on Wall Street" (i.e. volatility) came to the conclusion that if you want less volatility in the markets, keep them closed more, to essentially force the liquidity into specified periods. That is, 24 hour markets promote volatility. Or a corollary was that a market is never volatile when it is closed. [this is from memory and I may also be regurgitating from a personal conversation with him]. An oft cited example is the period in the summer of 1968 when equities were closed on Wednesdays to enable the back offices to get up to date with their paperwork and deliveries. During that time the Tuesday close to Thursday opening was less volatile than expected (twice the daily overnight vol).

One could take this thought and stretch it to say that the periods of least resistance would be those without heavy participation. One could easily compare the normalized range (High/Low) of those periods versus the same of the well-participated periods.

Craig Mee writes: 

Hi Bill,

You would have to think that in 68 there was sufficient control of price and news dissemination. In these times of high speed everything, that this could create bottlenecks and add to the volatility. No doubt a bit of time to cool the heels i.e limit down and up for the day restrictions, is a reasonable action, even if it goes against "fair open and transparent markets" but unfortunate it seems little is these days.

Bill Rafter replies:

I should have been more specific about the research: take the current normalized range for those periods of high liquidity (when the NY markets are open) and compare that to the normalized range of the premarket and postmarket periods. Do it for disjoint periods (but all in recent history) so you don't have any autocorrelation. My belief is that you will find there is less volatility intra-period during the high liquidity times. While you are at that you can also check to see during which period you get greater mean-reversion versus new direction.

If that research were to show that (for example) you had greater intra-period volatility during the premarket and postmarket times, and that those times also evidenced greater mean-reversion, you could then conclude that those were the times of least resistance. That would answer Vic's question. Okay, now what? Well you could then support an argument that with high volatility and mean reversion you should run (or mimic running) a specialist book during those times. That's not something I myself am interested in doing as it would require additional staff, but those of you with that capacity should consider it, if you are not yet doing so.

Historical sidebar: '68 was a bubble period caused in part by strange margin rules that enabled those in the industry to carry large positions for no money. The activity created paper problems as the back offices were still making/requiring physical delivery of stock certificates. The exchanges closed trading on Wednesday to enable the back offices to have another workday to clear the backlog. The "shenanigan index" was high during that time.

Phil McDonnell writes:

Bill, you said "During that time the Tuesday close to Thursday opening was less volatile than expected (twice the daily overnight vol)."

For a two day period and standard deviation s then the two day standard deviation should be sqrt(2)s or 1.4 s. So the figure of twice the volatility would seem higher than expected.

Or am I missing something? 

Steve Ellison submits this study:

The traditional definition of resistance is a price level at which it is expected there will be a relatively large amount of stock for sale. 
Starting from this point, my idea was that liquidity providers create resistance to price movements. If a stock price moved up a dollar on volume of 10,000 shares, it would suggest more resistance than if the price moved up a dollar on volume of 5,000 shares.

To test this idea, I used 5-minute bars of one of my favorite stocks, CHSI. To better separate up movement from down movement, for each bar I calculated the 75th and 25th percentiles of 5-minute net changes during the past week. If the current bar was in the 75th percentile or above, I added the price change and volume to the up category. If the current bar was in the 25th percentile or below, I added the price change and volume to the down category.

Looking back 200 bars, I divided the total up volume by the total up price change to calculate resistance to upward movement. I divided total down volume by the total down price change to calculate resistance to downward movement. I divided the upward resistance by the downward resistance to identify the path of least resistance. If the quotient was greater than 1, the past of least resistance was presumed to be downward; if the quotient was less than 1, the path of least resistance was upward.

For example:

                           Previous 200 bars
   Date     Time     Up Points Volume  Down Points Volume Resistance

3/25/2011   15:50   53   6.49  99431    61  -7.38  149867     15311

   Down       Resistance     Actual
Resistance      Ratio      net change
     20310       0.754       -0.03

Unfortunately, the correlation of the resistance ratio to the actual
price change of the next bar was consistent with randomness.



Who is hero for day today? I want to say something about the world's second biggest faker taking "bold steps" but one must find a hero to counterbalance.

Phil McDonnell writes: 

Here is the internal memo from the West Virginian:

He could be a hero too. He was a co-developer of S, the statistical programming language that many of us use. Conceptually it is very similar to the open source R.




Samuel Smiles. His great self help book is great for children and parents who wish to teach self esteem and self reliance in their kids.

Phil McDonnell adds: 

The book itself is available here from Project Gutenberg.



 We have discussed the role of government in the economy and during crisis many times on this site. Greenspan writes about this topic with the paper "Activism" that I recently read. He writes:

The current government activism is hampering what should be a broadbased robust economic recovery, driven in significant part by the positive wealth effect of a buoyant U.S. and global stock market.

Equity values, in my experience, have been an underappreciated force driving market economies. Only in recent years has their impact been recognized in terms of 'wealth effects'. This is one form of stimulus that does not require increased debt to fund it. I suspect that equity prices, whether they go up or down from here, will be a major component, along with the degree of activist government, in shaping the U.S. and world economy in the years immediately ahead."

Considerations about the wealth effect are in my view interesting, but well known to those who tried (and managed) to steer a recovery from the crisis.

The wealth effect has supported the economy so far. How much compared to the "stimulus" is hard to say however. "Manipulation" of markets in order to favor a continued move to the upside concerted by strong hands was (and is) in the interest of many forces who have a prominent role.

Victor Niederhoffer writes:

The wealth effect was very big in the 1960s and before, and Latane had good papers on it. Everyone at the Fed has believed in it for 70 years, to the exclusion of looking at interest rates themselves. And Bernanke often times his qualitative announcements with market lows or highs. A good way to trade. 

Phil McDonnell writes:

Most of the so called wealth effect is really artificially induced by the QE programs. If the price of your stock rises but the value of the dollars the stock will fetch falls then are you really wealthier? How rich do the folks in Zimbabwe feel? 

Jeff Watson writes:

One only has to look at the Weimar to see how the business class in Rhodesia feel. In 1913, the German stock market was at 126. Fourteen years later, the German stock market was at 26,890,000. At the index peak, the value of the Daimler company was only worth 327 of its cars. Interest rates were 900% and the exchange rate went from 4-5 marks per dollar in 1913 to 4+trillion marks per dollar in 1923. 

Ian Brakspear writes in:

My portfolio in 1994 was worth aprox ZIM$10 million in 2005 worth ZIM $ 44 billion.

Victor Niederhoffer comments:

What they did to the farmers makes one cry. Brakspear is the guy that posted the funniest spec post ever. He ordered 2 beers for lunch. It was 10 million Zimbabwe. Then by the time he finished lunch, he ordered two more. The price had risen to 15 million Zimbabwe.

Kim Zussman asks:

So does inflation illusion work? What does it feel like to be a billionaire?

Ian Brakspear comments: 

I have in my wallet 2 fifty billion dollar notes, a one hundred billion dollar note and one ten trillion dollar note-worthless.

Today the main currency in the streets of Zimbabwe is the US$– how all these US$ notes got here is anyone guess.

They are cleaned regularly in washing machines to prevent the spread of diseases– and hung out to dry on washing lines– always with someone on guard.



 Does the orbit of the Moon trigger earthquakes ? If so then March 16 through the 22nd could be interesting. The Moon makes its closest approach Mar 19 during the new Moon.

Here is something from Nolle's web site: his March forecast.

On a more interesting note my research showed that the stock market performs better from the new Moon to the full Moon than during the waning half of the cycle.

Jon Longtin comments: 

I wouldn't lose sleep over it.

The stress that the moon produces on the earth by constantly darting from one side to the other every day is orders of magnitude greater than the small variation in its distance to earth.

Put another way, high tide maybe a few thousandths of an inch higher when the moon is closest to the earth, on top of a several foot swing in sea level that day.

(But such events do make lovely fodder for the doomsayers…)

Peter Grieve writes:

The mixture of explicitly stated science with implied superstition seems to becoming an art form.

Jupiter and Saturn have a combined mass of less than .002 solar masses. And tidal effects vary like the inverse cube of distance. Which means that Jupiter's tidal effect is reduced by another factor of 1/64, since at its nearest it is 4 times further from us than the Sun is.

Putin will undoubtedly be pleased with dire predictions for the West.

Kim Zussman writes:

This kind of prediction is old news: see The Jupiter Effect .

As recalled, at the time astronomers estimated the net tidal pull of the 1982 planetary alignment on the sun (which, in turn, was to effect solar radiation and subsequently interact with earth's magnetic field) of ~1mm. The sun is about 864,000 miles in diameter.

Eventually with enough of these they'll get one right.

Pitt T. Maner III writes: 

Here is a good video on "pseudo-predictions" for this weekend from down under. Multiple, vague predictions debunked by scatter graphs.

I would guess, however, that there will be a resurgence of interest in the writings of catastrophists– Velikovsky being considered one of the last of the old time breed…

Phil McDonnell comments:

Speaking of Velikovsky a version of his theory is now the most favored theory for the formation of the Moon. The exception being that he thought the Moon was formed during historical times and used Biblical references to date it. For example he claimed the parting of the Red Sea was a giant Moon tidal effect. Instead current thinking dates the Mars sized Earth impact at about 300 million years after the formation of the solar System.

More on Moon formation theory:

Giant impact hypothesis

I also ran a test looking at all the earthquakes > 7.0M in 2010. I found that the number that were 'predicted' by Nolle's super Moon windows was 19%. But the number of days covered by the windows was only 10% of the year. On its face it seems like modest support, but the sample size of correct hits was only 4, so the jury is still out.



 A few months back David Aronson and I were talking about identifying markets as bullish or bearish prior to selecting strategies or parameters for various strategies. The conversation ended up taking a back seat to trading, family, etc., but I think now that markets are showing an increase in volatility it might be a good time to resume these talks.

Below I've included three links to a series of blog posts from Frank Hassler, who created (and explains) his own metric for identifying regimes, and how short term mean-reversion strategies work during different periods. What I find particularly interesting is his use of four possible regimes, whereas I use only two.

1. mefliter

2. using a market environment filter to decide how to trade

3. impact of a market environment filter

I've also found that many traders use simple metrics such as whether the broad market is above of below its 200ma when testing various strategies. My personal preference is to use fundamentals to predict longer term swings in equities.

Phil McDonnell writes:

There are a number of quirky things in the papers but overall the logic is interesting.

One quirk, for example is that he wants to use both rate of change and the slope of the moving average as indicators. Mathematically they are the same thing. Remember that a 200 day ma changes each day by lopping off the price level 200 days ago and adding in the current price. The daily difference (slop) is:

(current price - 200 days ago) / 200

But the rate of change per day is given by: (price - 200 days ago) / 200 Same thing!

We have received the following clarification from Frank Hassler:

I’m fully aware that slope = ROC.

The post isn’t about my trading, it’s rather an example what people should consider. Depending on the type of the system one should consider a different type of market environment filter. 



One thing that should be mentioned in any discussion of dollar cost averaging is that it really only works if you have an independent source of income to add to the investment kitty. Without that it pretty much devolves into just reinvesting dividends. Reinvesting dividends does work too. Studies have shown that about half of all Triumphal Optimists 100 year long return came from reinvestment of dividends. This incremental return was greater than the average dividend rate. Thus part of the overplus came from the timing effect of dollar cost averaging the dividends.



 I am sorely tempted, having bought a far out of the money position expiring in October, to offset the cost by selling nearer term options in the coming months. Were it a blitz chess game I would play this move immediately. But as I am resolved to stay within a rigorous preset plan, I am sitting on my hands.

Phil McDonnell adds:

One strategy you could think about is calendar rolls. Sell the March, let it expire, then the Apr and so on. If the underlying reaches the strike price, dump it all. That will be your peak profit.

Laurence Glazier responds:

After thinking more I've realized it is probably best not to sell nearer term calls against the one I hold. A good job I sat on my hands.

My positions are carefully selected to have a chance of doubling in value, and if this happens I close them.

I imagine that converting to a calendar spread would not be compatible (the short call would weigh against the profits). But selling a call expiring at the same date but more out of the money would, I suspect, make doubling more likely and might increase my choice of candidate positions - though there would be more commission charges.

Of 10 positions I have thus far closed since starting this strategy in November, 5 doubled– so I think it worth keeping the plan going. 



What a way for the new seasonatarian fund to start, thereby giving its holders a nice 3% deficit if they did start already, and how guaranteed it was to happen, and how consistent this is with rational expectations.

Jim Lorie and Milton Friedman (there is no such thing as a free lunch) will rest peacefully from above tonight.

Phil McDonnell writes:

Here is a link to a Ziemba paper which updates the research on seasonality. There are a few choice comments regarding the Almanaterians in the intro and F@m@ & Fr3nch on pg. 4.



 Back in 1992 I read Peter Lynch's book "Beating the Street". It's a fun book to read; he explains how he came to recommend ~20 stocks in that year's Barron's "Roundtable". As the years passed though I kept noticing that stocks that he had recommended were falling by the wayside. One of them, Sun TV and Appliance, was a retailer in Columbus, Ohio, where I was living at the time, and not too many years after the recommendation, Sun crashed and burned. Similarly I noticed bad things happening to Supercuts, which he recommended, and more recently Fannie Mae and GM both fell to zero-ish levels. So I've long suspected that overall his picks might have been sub-par, or a disaster, even.

Today I finally got had the time and energy to test it. I know this is breaking the rules, but please refer to the attached spreadsheet, only 10 kB. The spreadsheet shows Lynch's 18 stocks (I excluded one stock because it traded in London and another because it was a "Class B" share, and I couldn't figure out what ticker to use in my database) and their tickers as of 1/31/1992.

Many, actually most, of the stocks did not continue as going concerns until today; they were either acquired, bankrupted, or whatever. I believe that my database (MarketQA) does a reasonably good job of giving my a terminal value, but beyond that I didn't attempt to find out what happened to each stock.

So the spreadsheet has a column for "months as a going concern", i.e. how long the stock lasted after 1/31/1992 until it was acquired, bankrupted, or whatever. Stocks that survived until now have lived for 229 months. The next column, "$1 grew to" tells you how much money you'd have if you invested $1 and held until the firm ceased as a going concern. The last column gives the compound return over the period as a going concern.

Lynch didn't do badly at all. The average stock grew $1 into $4.24. On average the stocks "lived" for 141 months as going concerns, and I did not give Lynch any credit for reinvesting the moneys after stocks died off. However there was an enormous variation among the stocks. Five of the 18 stocks lost more than 90%, but four multiplied your money by a factor of 10 or more.

The big winners were in the thrift / S&L stocks–on average they grew $1 into more than $8, and without them the average performance of the remaining stocks is not impressive.

Lessons? I guess these results give a pretty good feel for the wide variation in returns of individual stocks over long periods. It may also be surprising that stocks have such finite lifetimes, even when they work out well–e.g. First Essex turned your $1 into $20 before it fell off the radar about ten years ago, presumably after being acquired. Lynch himself always emphasizes that the occasional "ten bagger" can make up for a lot of sins elsewhere in the portfolio, and that definitely played out with his picks.

(If you can't handle spreadsheets, here it is as text, but I have no idea whether it will format properly for you.)

ticker as of 1/31/1992    company name    months as a going concern    $1 grew
to    compound annualized return while a going concern
GH    General Host    72    $0.80    -3.6%
PIR    Pier 1 Imports    229    $2.88    5.7%
SBN    Sunbelt Nursery    74    $0.03    -44.7%
CUTS    Supercuts    57    $0.72    -6.7%
SNTV    Sun TV and Appliance    82    $0.03    -40.0%
EAG    Eagle Financial    75    $6.34    34.4%
FESX    First Essex Bancorp    145    $19.57    27.9%
GSBK    Germantown Savings Bank    35    $3.67    56.1%
GBCI    Glacier Bancorp    229    $12.70    14.2%
LSBX    Lawrence Savings Bank    229    $10.54    13.1%
PBNB    People's Savings Financial    66    $3.97    28.5%
SVRN    Sovereign Bancorp    204    $1.03    0.2%
TLP    Tenera L.P.    139    $0.00    -42.8%
GM    General Motors    226    $0.01    -23.7%
PD    Phelps Dodge    182    $10.64    16.9%
CMS    CMS Energy    229    $1.74    2.9%
FNM    Fannie Mae    229    $0.04    -15.5%
COGRA    Colonial Group    38    $1.67    17.6%

       average    $4.24

Steve Ellison writes:

The median stock turned $1 into $1.70 and had a 4.4% CAGR. I got similar results when I checked stocks suggested by Jim Collins in Good to Great. A small number of big gainers made the portfolio as a whole above average. Maybe there is a lesson here.

Tim Melvin comments: 

If you study Mr. Lynch's results much of his success was a result of playing the mutual thrift conversion game. His fund had deposts in just about every mutual thrift in the country so he could buy the conversion offering. Almost universally these stocks were HUGE winners. That game is very much back to life today as new regs are pretty much forcing many thrifts to convert…..most can be bought after the offering at a still sizable disocunt to tangible book value.

Charles Pennington writes: 

Of the four "ten baggers", two would have gotten stopped out at very disadvantageous (roughly break even) prices…

I would have guessed that those conversions had limits on how much stock a customer could buy, and with those limits in place, how could they make a dent in the performance of a large fund?

According to the Cramer book ("Confessions.."), which is very entertaining, much of the good performance of his fund was also due to holding thrifts, but he almost went under when redemptions threatened to force him to sell those very illiquid stocks.

Apart from the initial "pop" after a conversion, I don't see why thrift stocks would continue being cheap. Isn't this a very well-known idea, given that I've heard of it?

Victor Niederhoffer writes:

Now the professor is going to compute the market value of the individual stocks and tell me that the average market value of the ones that went down 100% at inception was not different from the average market value of the ones that were 10 baggers and kept him from reading books. 

Charles Pennington responds: 

The Chair's point is that most of the 10 baggers mostly started out as impossibly-small-to-buy stocks, and that is correct. Here are the 10-baggers and their market caps in January 1992:

First Essex (FESX) $21 million
Glacier Bancorp (GBCI) $32 million
LSBX $12 million
Phelps Dodge (PD) $2.6 billion

The only non-micro cap is Phelps Dodge.

Here are the January 1992 market caps of the stocks that lost nearly 100%:

SBN $60 million
SNTV $109 million
TLP $30 million
GM $19.9 billion
FNM $17.7 billion

George Coyle writes: 

Food for thought since I don't have access to data, certain funds and firms have size restrictions on what they can buy due to position sizing, liquidity, etc. It would be interesting to see if stocks which crossed over a given level in market cap ($100mm, $500mm, $1bb) subsequently saw inflows or outflows by virtue of qualifying as new investments for bigger buyers or being kicked out by virtue of falling below an acceptable cap level. Also, there are legal filing consequences of holding positions over certain sizes so I imagine patterns exist which are very real as firms alter position sizing to avoid regulatory filings (and ultimately position size disclosure on a non-quarterly basis). It is a bit of a momentum study meets the analysis below but with a legal/fund guideline slant. I believe Factset tracks historical cap sizes with some reasonable degree of accuracy/frequency but I no longer have access.

Phil McDonnell writes:

To throw a few stats on the table I am posting links to some work done by Eric Crittenden. He is a momentum quant with BlackStar Funds. He argues that trend following must work because long term stock distributions have very fat tails. He also argues that the negative fat tail implies that stop losses must work. One of the charts shows a huge right tail of three baggers or better. Another shows that all gains come from 20% of the stocks.
I have had the chance to review several of his studies in progress and Crittenden seems to do it right. He uses total returns and avoids obvious pitfalls like survivor bias etc.

Charles Pennington responds:

It seems kind of silly that they take this indirect route — "lots of big gainers and lots of big losers, therefore use stop losses". Why don't they just test the performance of some simple stop-loss rule? Jason proposed a trailing stop of 50%. That sounds ok to me. Then, whenever you're stopped out, use the proceeds to buy an equal weight (cap weighted) of the remaining stocks. Does that outperform or under-perform the equal-weight (or cap weighted) index?



 Can anyone comment on how Python compares to R as it pertains to trading testing/analysis? I already know R and am not seeing a lot of added benefit to learning Python vs becoming more proficient in R but I am probably missing something.

Phil McDonnell writes:

You could probably do almost anything you need in R. So adding Python not much of an improvement. I would say that the two languages are very different in how you approach a problem. R is much more oriented to telling it to operate on a vector of numbers or a times series or matrix object. You can do those types of operations very easily and efficiently with only a line or two of code. but if you try to write your own FOR loop to write up a procedure to do the same thing it will run shockingly slowly– something like 30 times slower. But usually there is a way to write the code up as a vector operation without a loop.

Python is more designed to be a procedural language where you write your own loops and procedures. It is designed to be efficient at that and gives you more low level control but at the cost of more lines of code and more detail from the programmer.. 



The Grandmaster has opened my eyes to the wonder of the Guardian. Also from them is an article that I would dub the Phallic Subliminal Suggestion effect: "Mobile Phone Masts Birth Rate".



You can get as-reported earnings for the S&P 500 from 1988 on at Standard & Poor's website.

Using 12-month trailing earnings for each year's September quarter (the last that would be known by Dec. 31) to calculate an E/P ratio for the S&P 500 as of Dec. 31, I get a somewhat positive correlation of trailing E/P to year-ahead returns with t=1.10, R sq=0.057, p=0.29, and N=22.

Larry Williams writes:

My model for the DOW suggests a 12.25% growth for the year, slightly above the long term average growth.

For the S&P, I get 10.6 % barely above the long term average.

Bruno Ombreux writes:

There are two things I don't like in P/E or E/P studies.

1) Your regression is in the form:

-1 + P(t)/P(t-1) = f[P(t-n)/E(t-n)] + e we have the same variable on both sides, and even if it is lagged I am not sure standard regression is OK to handle this type of formula. Just to give you an idea, multiplying both sides by P(t-1), it is actually P(t) = P(t-1) + P(t-1)* f[P(t-n)/E(t-n)] + P(t-1)*e

This is certainly amenable to study, but not with the standard regression toolbox.

2) Price is more volatile than earnings. There is a subtle bias introduced by the fact that over the estimation sample, high P/E will be naturally followed by lower P/E, and vice-versa. This is a bit like regression to the mean but more subtle. This can lead to spurious mean-reversion.

Phil McDonnell adds:

The issue is not really the dependent variable. It is using the Shiller variable with its serial correlation. One way to use the Shiller variable would be to take every tenth month. That might work but you would have one tenth the data. You still might have the Holbrook Working flaw because of the averaging. The averaging also leads to the Slutsky-Yule effect which creates spurious sinusoidal artifacts in the adjusted variable when no such sinusoidal effect is actually present in the original data..



UPDATE 1/31/2011:

Contestants Summary:

- 31 Spec-listers contributed to the 2011 Investment Contest with "specific" recommendations.

- Average 4 recommendations per person (mean of 4.2, median and mode of 4) came in.

- 6 contestants gave only 1 recommendation, 3 gave only 2 and thus 9 out of the total 31 have NOT given the minimum 3 recommendations needed as per the Rules clarified by Ken Drees.

- The Hall of Fame entry for the largest number of ideas (did someone say diversification?) is from Tim Melvin, close on whose heels are J. T. Holley with 11 and Ken Drees with 10.

- The most creatively expressed entry of course has come from Rocky Humbert.

- At this moment 17 out of 31 contestants are in positive performance territory, 14 are in negative performance territory.

- Barring a major outlier of a 112.90% loss on the Option Strategy of Phil McDonnell (not accounting for the margin required for short options, but just taking the ratio of initial cash inflow to outflow):

- Average of all Individual contestant returns is -2.54% and the Standard Deviation of returns achieved by all contestants is 5.39.

- Biggest Gainer at this point is Jared Albert (with his all in single stock bet on REFR) with a 22.87% gain. The only contestant a Z score greater than 2 ( His is actually 4.72 !!)

- Biggest Loser at this point (barring the Giga-leveraged position of Mr. McDonnell) is Ken Drees at -10.36% with a Z Score that is at -1.45.

- Wildcards have not been accounted for as at this point, with wide
deviations of recommendations from the rules specified by most. While 9
participants have less than 3 recommendations, those with more than 4
include several who have not chosen to specify which 3 are their primary recommends. Without clarity on a universal measurability wildcard accounting is on hold. Those making more than 1 recommendations would find that their aggregate average return is derived by taking a sum of returns of individual positions divided by the number of recommends. Unless specified by any person that positions are taken in a specific ratio its equal sums invested approach.

Contracts Summary:

- A total of 109 contracts are utilized by the contestants across bonds, equity indices (Nikkei, Kenyan Stocks included too!), commodities, currencies and individual stock positions.

- The ratio of Shorts to Longs across all recommendations, irrespective of the type of contract (call, put, bearish ETF etc.) is 4 SELL orders Vs 9 Buy Orders. Not inferring that this list is more used to pressing the Buy Button. Just an occurence on this instance.

- The Average Return, so far, on the 109 contracts utilized is -1.26% with a Standard Deviation of 12.42%. Median Return is 0.39% and the mode of Returns of all contracts used is 0.

- The Highest Return is on MICRON TECH at 28.09, if one does not account for the July 2011 Put 25 strike on SLV utilized by Phil McDonnell.

- The Lowest Return is on IPTV at -50%, if one does not account for the Jan 2012 Call 40 Strike on SLV utilized by Phil McDonnell.

- Only Two contracts are having a greater than 2 z score and only 3 contracts are having a less than -2 Z score.

Victor Niederhoffer wrote:

One is constantly amazed at the sagacity in their fields of our fellow specs. My goodness, there's hardly a field that one of us doesn't know about from my own hard ball squash rackets to the space advertising or our President, from surfing to astronomy. We certainly have a wide range.

May I suggest without violating our mandate that we consider our best sagacities as to the best ways to make a profit in the next year of 2011.

My best trades always start with assuming that whatever didn't work the most last year will work the best this year, and whatever worked the best last year will work the worst this year. I'd be bullish on bonds and bearish on stocks, bullish on Japan and bearish on US stocks.

I'd bet against the banks because Ron Paul is going to be watching them and the cronies in the institutions will not be able to transfer as much resources as they've given them in the past 2 years which has to be much greater in value than their total market value.

I keep wondering what investments I should make based on the hobo's visit and I guess it has to be generic drugs and foods.

What ideas do you have for 2011 that might be profitable? To make it interesting I'll give a prize of 2500 to the best forecast, based on results as of the end of 2011.

David Hillman writes: 

"I do know that a sagging Market keeps my units from being full."

One would suggest it is a sagging 'economy' contributing to vacancy, not a sagging 'market'. There is a difference. 

Ken Drees, appointed moderator of the contest, clearly states the new rules of the game:

 1. Submissions for contest entries must be made on the last two days of 2010, December 30th or 31st.
2. Entries need to be labeled in subject line as "2011 contest investment prediction picks" or something very close so that we know this is your official entry.
3. Entries need 3 predictions and 1 wildcard trade prediction (anything goes on the wildcard).

4. Extra predictions may be submitted and will be judged as extra credit. This will not detract from the main predictions and may or may not be judged at all.

5. Extra predictions will be looked on as bravado– if you've got it then flaunt it. It may pay off or you may give the judge a sour palate.

The desire to have entries coming in at years end is to ensure that you have the best data as to year end 2010 and that you don't ignite someone else to your wisdom.

Market direction picks are wanted:

Examples: 30 year treasury yield will fall to 3% in 2011, S&P 500 will hit "x" by June, and then by "y" by December 2011.

The more exact your prediction is, the more weight will be given. The more exact your prediction, the more weight you will receive if right and thus the more weight you will receive if wrong. If you predict that copper will hit 5.00 dollars in 2011 and it does you will be given a great score, if you say that copper will hit 5.00 dollars in march and then it will decline to4.35 and so forth you will be judged all along that prediction and will receive extra weight good or bad. You decide on how detailed your submission is structured.

Will you try to be precise (maybe foolhardy) and go for the glory? Or will you play it safe and not stand out from the crowd? It is a doubled edged sword so its best to be the one handed market prognosticator and make your best predictions. Pretend these predictions are some pearls that you would give to a close friend or relative. You may actually help a speclister to make some money by giving up a pearl, if that speclister so desires to act upon a contest–G-d help him or her.

Markets can be currency, stocks, bonds, commodities, etc. Single stock picks can be given for the one wildcard trade prediction. If you give multiple stock picks for the wildcard then they will all be judged and in the spirit of giving a friend a pearl–lets make it "the best of the best, not one of six".

All judgments are the Chair's. The Chair will make final determination of the winner. Entries received with less than 3 market predictions will not be considered. Entries received without a wildcard will be considered.The spirit of the contest is "Give us something we can use".

Bill Rafter adds: 

Suggestion for contest:

"Static" entry: A collection of up to 10 assets which will be entered on the initial date (say 12/31/2010) and will be unaltered until the end data (i.e. 12/31/2011). The assets could be a compilation of longs and shorts, or could have the 10 slots entirely filled with one asset (e.g. gold). The assets could also be a yield and a fixed rate; that is one could go long the 10-year yield and short a fixed yield such as 3 percent. This latter item will accommodate those who want to enter a prediction but are unsure which asset to enter as many are unfamiliar with the various bond coupons.

"Rebalanced" entry: A collection of up to 10 assets which will be rebalanced on the last trading day of each month. Although the assets will remain unchanged, their percentage of the portfolio will change. This is to accommodate those risk-averse entrants employing a mean-reversion strategy.

Both Static and Rebalanced entries will be judged on a reward-to-risk basis. That is, the return achieved at the end of the year, divided by the maximum drawdown (percentage) one had to endure to achieve that return.

Not sure how to handle other prognostications such as "Famous female singer revealed to be man." But I doubt such entries have financial benefits.

I'm willing to be an arbiter who would do the rebalancing if necessary. I am not willing to prove or disprove the alleged cross-dressers.

Ralph Vince writes:

A very low volume bar on the weekly (likely, the first of two consecutive) after a respectable run-up, the backdrop of rates having risen in recent weeks, breadth having topped out and receding - and a lunar eclipse on the very night of the Winter Solstice.

If I were a Roman General I would take that as a sign to sit for next few months and do nothing.

I'm going to sit and do nothing.

Sounds like an interim top in an otherwise bullish, long-term backdrop.

Gordon Haave writes: 

 My three predictions:

Gold/ silver ratio falls below 25 Kenyan stock market outperforms US by more than 10%

Dollar ends 10% stronger compared to euro

All are actionable predictions.

Steve Ellison writes:

I did many regressions looking for factors that might predict a year-ahead return for the S&P 500. A few factors are at extreme values at the end of 2010.

The US 10-year Treasury bond yield at 3.37% is the second-lowest end-of year yield in the last 50 years. The S&P 500 contract is in backwardation with the front contract at a 0.4% premium to the next contract back, the second highest year-end premium in the 29 years of the futures.

Unfortunately, neither of those factors has much correlation with the price change in the S&P 500 the following year. Here are a few that do.

The yield curve (10-year yield minus 3-month yield) is in the top 10% of its last 50 year-end values. In the last 30 years, the yield curve has been positively correlated with year-ahead changes in the S&P 500, with a t score of 2.17 and an R squared of 0.143.

The US unemployment rate at 9.8% is the third highest in the past 60 years. In the last 30 years, the unemployment rate has been positively correlated with year-ahead changes in the S&P 500, with a t score of 0.90 and an R squared of 0.028.

In a variation of the technique used by the Yale permabear, I calculated the S&P 500 earnings/price ratio using 5-year trailing earnings. I get an annualized earnings yield of 4.6%. In the last 18 years, this ratio has been positively correlated with year-ahead changes in the S&P 500, with a t score of 0.92 and an R squared of

Finally, there is a negative correlation between the 30-year S&P 500 change and the year-ahead change, with a t score of -2.28 and an R squared of 0.094. The S&P 500 index price is 9.27 times its price of 30 years ago. The median year-end price in the last 52 years was 6.65 times the price 30 years earlier.

Using the predicted values from each of the regressions, and weighting the predictions by the R squared values, I get an overall prediction for an 11.8% increase in the S&P 500 in 2011. With an 11.8% increase, SPY would close 2011 at 140.52.

Factor                  Prediction      t       N    R sq
US Treasury yield curve      1.162    2.17      30   0.143
30-year change               1.052   -2.28      52   0.094
Trailing 5-year E/P          1.104    0.92      18   0.050
US unemployment rate         1.153    0.90      30   0.028

Weighted total               1.118
SPY 12/30/10               125.72
Predicted SPY 12/30/11     140.52

Jan-Petter Janssen writes: 

PREDICTION I - The Inconvenient Truth The poorest one or two billion on this planet have had enough of increasing food prices. Riots and civil unrest force governments to ban exports, and they start importing at any cost. World trade collapses. Manufacturers of farm equipment will do extremely well. Buy the most undervalued producer you can find. My bet is
* Kverneland (Yahoo: KVE.OL). NOK 6.50 per share today. At least NOK 30 on Dec 31th 2011.

PREDICTION II - The Ultimate Bubble The US and many EU nations hold enormous gold reserves. E.g. both Italy and France hold the equivalent of the annual world production. The gold meme changes from an inflation hedge / return to the gold standard to (a potential) over-supply from the selling of indebted nations. I don't see the bubble bursting quite yet, but
* Short gold if it hits $2,000 per ounce and buy back at $400.

PREDICTION III - The Status Quo Asia's ace is cheap labor. The US' recent winning card is cheap energy through natural gas. This will not change in 2011. Henry Hub Feb 2011 currently trades at $4.34 per MMBtu. Feb 2012 is at $5.14. I would
* Short the Feb 2012 contract and buy back on the last trading day of 2011.

Vince Fulco predicts:

 This is strictly an old school, fundamental equity call as my crystal ball for the indices 12 months out is necessarily foggy. My recommendation is BP equity primarily for the reasons I gave earlier in the year on June 5th (stock closed Friday, June 4th @ $37.16, currently $43.53). It faced a hellish downdraft post my mention for consideration, primarily due to the intensification of news flow and legal unknowns (Rocky articulated these well). Also although the capital structure arb boys savaged the equity (to 28ish!), it is up nicely to year's end if one held on and averaged in with wide scales given the heightened vol.

Additional points/guesstimates are:

1) If 2010 was annus horribilis, 2011 with be annus recuperato. A chastened mgmt who have articulated they'll run things more conservatively will have a lot to prove to stakeholders.

2) Dividend to be re-instated to some level probably by the end of the second quarter. I am guessing $1.00 annualized per ADS as a start (or
2.29%), this should bring in the index hugging funds with mandates for only holding dividend payers. There is a small chance for a 1x special dividend later in the year.

3) Crude continues to be in a state of significant profitability for the majors in the short term. It would appear finding costs are creeping however.

4) The lawsuits and additional recoveries to be extracted from the settlement fund and company directly have very long tails, on the order of 10 years.

5) The company seems fully committed to sloughing off tertiary assets to build up its liquid balance sheet. Debt to total capital remains relatively low and manageable.

6) The stock remains at a significant discount to its better-of breed peers (EV/normalized EBITDA, Cash Flow, etc) and rightly so but I am betting the discount should narrow back to near historical levels.

Potential negatives:

1) The company and govt have been vastly understating the remaining fuel amounts and effects. Release of independent data intensifies demands for a much larger payout by the company closer to the highest end estimates of $50-80B.

2) It experiences another similar event of smaller magnitude which continues to sully the company's weakened reputation.

3) China admits to and begins to fear rampant inflation, puts the kabosh to the (global) economy and crude has a meaningful decline the likes of which we haven't seen in a few years.

4) Congress freaks at a >$100-120 price for crude and actually institutes an "excess profits" tax. Less likely with the GOP coming in.

A buy at this level would be for an unleveraged, diversified, longer term acct which I have it in. However, I am willing to hold the full year or +30% total return (including special dividend) from the closing price of $43.53 @ 12/30/10, whichever comes first. Like a good sellside recommendation, I believe the stock has downside of around 20% (don't they all when recommended!?!) where I would consider another long entry depending on circumstances (not pertinent to the contest).

Mr. Albert enters: 

 Single pick stock ticker is REFR

The only way this gold chain wearing day trader has a chance against all the right tail brain power on the list is with one high risk/high reward put it all on red kind of micro cap.

Basic story is this company owns all the patents to what will become the standard for switchable glazings (SPD smart glass). It's taken roughly 50 years of development to get a commercialized product, and next year Mercedes will almost without doubt use SPD in the 2012 SLK (press launch 1/29/11 public launch at the Geneva auto show in march 2011).

Once MB validate the tech, mass adoption and revenues will follow etc and this 'show me' stock will rocket to the moon.

Dan Grossman writes:

Trying to comply with and adapt the complex contest rules (which most others don't seem to be following in any event) to my areas of stock market interest:

1. The S&P will be down in the 1st qtr, and at some point in the qtr will fall at least

2. For takeover investors: GENZ will (finally) make a deal to be acquired in the 1st qtr for a value of at least $80; and AMRN after completion of its ANCHOR trial will make a deal to be acquired for a price of at least $8.

3. For conservative investors: Low multiple small caps HELE and DFG will be up a combined average of 20% by the end of the year.

For my single stock pick, I am something of a johnny-one-note: MNTA will be up lots during the year — if I have to pick a specific amount, I'd say at least 70%. (My prior legal predictions on this stock have proved correct but the stock price has not appropriately reflected same.)

Finally, if I win the contest (which I think is fairly likely), I will donate the prize to a free market or libertarian charity. I don't see why Victor should have to subsidize this distinguished group that could all well afford an contest entrance fee to more equitably finance the prize.

Best to all for the New Year,


Gary Rogan writes:

 1. S&P 500 will rise 3% by April and then fall 12% from the peak by the end of the year.
2. 30 year treasury yields will rise to 5% by March and 6% by year end.
3. Gold will hit 1450 by April, will fall to 1100 by September and rise to 1550 by year end.

Wildcard: Short Netflix.

Jack Tierney, President of the Old Speculator's Club, writes: 

Equal Amounts in:

TBT (short long bonds)
YCS (short Yen)
GRU (Long Grains - heavy on wheat)
CHK (Long NG - takeover)

(Wild Card)
BONXF.PK or BTR.V (Long junior gold)

12/30 closing prices (in order):


Bill Rafter writes:

Two entries:

Buy: FXP and IRWD

Hold for the entire year.

William Weaver writes:

 For Returns: Long XIV January 21st through year end

For Return/Risk: Long XIV*.30 and Long VXZ*.70 from close today

I hope everyone has enjoyed a very merry holiday season, and to all I wish a wonderful New Year.



Ken Drees writes:

Yes, they have been going up, but I am going contrary contrary here and going with the trends.

1. Silver: buy day 1 of trading at any price via the following vehicles: paas, slw, exk, hl –25% each for 100% When silver hits 39/ounce, sell 10% of holdings, when silver hits 44/ounce sell 30% of holdings, when silver hits 49 sell 60%–hold rest (divide into 4 parts) and sell each tranche every 5 dollars up till gone–54/oz, 59, 64, 69.

2. Buy GDXJ day 1 (junior gold miner etf)—rotation down from majors to juniors with a positive gold backdrop. HOLD ALL YEAR.

3. USO. Buy day 1 then do—sell 25% at 119/bbl oil, sell 80% at 148/bbl, sell whats left at 179/bbl or 139/bbl (whichever comes first after 148)


Happy New Year!

Ken Drees———keepin it real.

Sam Eisenstadt forecasts:

My forecast for the S&P 500 for the year ending Dec 31, 2011;

S&P 500       1410

Anton Johnson writes: 

Equal amounts allocated to:

EDZ Short moc 1-21-2011, buy to cover at 50% gain, or moc 12/30/2011

VXX Short moc 1-21-2011, buy to cover moc 12/30/2011

UBT Short moo 1-3-2011, buy to cover moc 12/30/2011

Scott Brooks picks: 


Evenly between the 4 (25% each)

Sushil Kedia predicts:


1) Gold
2) Copper
3) Japanese Yen

30% moves approximately in each, within 2011.

Rocky Humbert writes:

(There was no mention nor requirement that my 2011 prediction had to be in English. Here is my submission.) … Happy New Year, Rocky

Sa aking mahal na kaibigan: Sa haba ng 2010, ako na ibinigay ng ilang mga ideya trading na nagtrabaho sa labas magnificently, at ng ilang mga ideya na hindi na kaya malaki. May ay wala nakapagtataka tungkol sa isang hula taon dulo, at kung ikaw ay maaaring isalin ito talata, ikaw ay malamang na gawin ang mas mahusay na paggawa ng iyong sariling pananaliksik kaysa sa pakikinig sa mga kalokohan na ako at ang iba pa ay magbigay. Ang susi sa tagumpay sa 2011 ay ang parehong bilang ito ay palaging (tulad ng ipinaliwanag sa pamamagitan ng G. Ed Seykota), sa makatuwid: 1) Trade sa mga kalakaran. 2) Ride winners at losers hiwa. 3) Pamahalaan ang panganib. 4) Panatilihin ang isip at diwa malinaw. Upang kung saan gusto ko idagdag, fundamentals talaga bagay, at kung ito ay hindi magkaroon ng kahulugan, ito ay hindi magkaroon ng kahulugan, at diyan ay wala lalo na pinakinabangang tungkol sa pagiging isang contrarian bilang ang pinagkasunduan ay karaniwang karapatan maliban sa paggawa sa mga puntos. (Tandaan na ito ay pinagkasunduan na ang araw ay babangon na bukas, na quote Seth Klarman!) Pagbati para sa isang malusog na masaya at pinakinabangang 2011, at siguraduhin na basahin kung saan ako magsulat sa Ingles ngunit ang aking mga saloobin ay walang malinaw kaysa talata na ito, ngunit inaasahan namin na ito ay mas kapaki-pakinabang.

Dylan Distasio comments: 

Gawin mo magsalita tagalog?

Gary Rogan writes:

After a worthy challenge, Mr. Rogan is now also a master of Google Translate, and a discoverer of an exciting fact that Google Translate calls Tagalog "Filipino". This was a difficult obstacle for Mr. Rogan to overcome, but he persevered and here's Rocky's prediction in English (sort of):

My dear friend: Over the course of 2010, I provided some trading ideas worked out magnificently, and some ideas that are not so great. There is nothing magical about a forecast year end, and if you can translate this paragraph, you will probably do better doing your own research rather than listening to the nonsense that I and others will give. The key to success in 2011 is the same as it always has (as explained by Mr. Ed Seykota), namely: 1) Trade with the trend.

2) Ride cut winners and losers. 3) Manage risk. 4) Keep the mind and spirit clear. To which I would add, fundamentals really matter, and if it does not make sense, it does not make sense, and there is nothing particularly profitable about being a contrarian as the consensus is usually right but turning points. (Note that it is agreed that the sun will rise tomorrow, to quote Seth Klarman) Best wishes for a happy healthy and profitable 2011, and be sure to read which I write in English but my attitude is nothing clearer than this paragraph, but hopefully it is more useful.

Tim Melvin writes:

Ah the years end prediction exercise. It is of course a mostly useless exercise since not a one of us can predict what shocks, positive or negative, the world and the markets could see in 2011. I find it crack up laugh out loud funny that some pundits come out and offer up earnings estimates, GDP growth assumptions and interest rate guesses to give a precise level for the year end S&P 500 price. You might as well numbers out of a bag and rearrange them by lottery to come up with a year end number. In a world where we are fighting two wars, a hostile government holds the majority of our debt and several sovereign nations continually teeter on the edge of oblivion it's pretty much ridiculous to assume what could happen in the year ahead. Having said that, as my son's favorite WWE wrestler when he was a little guy used to say "It's time to play the game!"

Ill start with bonds. I have owned puts on the long term treasury market for two years now. I gave some back in 2010 after a huge gain in 2009 but am still slightly ahead. Ill roll the position forward and buy January 2012 puts and stay short. When I look at bods I hear some folks talking about rising basic commodity prices and worrying about inflation. They are of course correct. This is happening. I hear some other really smart folks talking of weak real estate, high jobless rates and the potential for falling back into recession. Naturally, they are also exactly correct. So I will predict the one thing no one else is. We are on the verge of good old fashioned 1970s style stagflation. Commodity and basic needs prices will accelerate as QE2 has at least stimulated demand form emerging markets by allowing these wonderful credits to borrow money cheaper than a school teacher with a 750 FICO score. Binds go lower as rates spike. Our economy and balance sheet are a mess and we have governments run by men in tin hats lecturing us on fiscal responsibility. How low will they go Tim? How the hell do I know? I just think they go lower by enough for me to profit.

 Nor can I tell you where the stock market will go this year. I suspect we have had it too good for too long for no reason so I think we get at least one spectacular gut wrenching, vomit inducing sell off during the year. Much as lower than expected profits exposed the silly valuations of the new paradigm stocks I think that the darling group, retail , will spark a sell-off in the stock market this year. Sales will be up a little bit but except for Tiffany's (TIF) and that ilk margins are horrific. Discounting started early this holiday and grew from there. They will get steeper now that that Santa Claus has given back my credit card and returned to the great white north. The earnings season will see a lot of missed estimates and lowered forecasts and that could well pop the bubble. Once it starts the HFT boys and girls should make sure it goes lower than anyone expects.

Here's the thing about my prediction. It is no better than anyone else's. In other words I am talking my book and predicting what I hope will happen. Having learned this lesson over the years I have learned that when it comes to market timing and market direction I am probably the dumbest guy in the room. Because of that I have trained myself to always buy the stuff that's too cheap not to own and hold it regardless. After the rally since September truly cheap stuff is a little scarce on the ground but I have found enough to be about 40% long going into the year. I have a watch list as long as a taller persons right arm but most of it hover above truly cheap.

Here is what I own going into the year and think is still cheap enough to buy. I like Winn Dixie (WINN). The grocery business sucks right now. Wal mart has crushed margins industry wide. That aside WINN trades at 60% of tangible book value and at some point their 514 stores in the Southeast will attract attention from investors. A takeover here would be less than shocking. I will add Presidential Life (PLFE) to the list. This stock is also at 60% of tangible book and I expect to see a lot of M&A activity in the insurance sector this year and this should raise valuations across the board. I like Miller Petroleum (MILL) with their drilling presence in Alaska and the shale field soft Tennessee. This one trades at 70% of tangible book. Ill add Imperial Sugar (IPSU), Syms (SYMS) and Micron tech (MU) and Avatar Holdings (AVTR) to my list of cheapies and move on for now.

I am going to start building my small bank portfolio this year. Eventually this group becomes the F-you walk away money trade of the decade. As real estate losses work through the balance sheet and some measure of stability returns to the financial system, perhaps toward the end of the year the small baileys savings and loan type banks should start to recover. We will also see a mind blowing M&A wave as larger banks look to gain not just market share but healthy assets to put on the books. Right now these names trade at a fraction of tangible book value. They will reach a multiple of that in a recovery or takeover scenario. Right now I own shares of Shore Bancshares (SHBI), a local bank trading at 80% of book value and a reasonably healthy loan portfolio. I have some other mini microcap banks as well that shall remain my little secret and not used to figure how my predictions work out. I mention them because if you have a mini micro bank in your community you should go meet then bankers, review the books and consider investing if it trades below the magical tangible book value and has excess capital. Flagstar Bancorp(FBC) is my super long shot undated call option n the economy and real estate markets.

I will also play the thrift conversion game heavily this year. With the elimination of the Office of Thrift Services under the new financial regulation many of the benefits of being a private or mutual thrift are going away. There are a ton of mutual savings banks that will now convert to publicly traded banks. A lot of these deals will be priced below the pro forma book value that is created by adding all that lovely IPO cash to the balance sheet without a corresponding increase in the shares outstanding. Right now I have Fox Chase Bancorp (FXCB) and Capital Federal Financial(CFFN). There will be more. Deals are happening every day right now and again I would keep an eye out for local deals that you can take advantage of in the next few months.

I also think that 2011 will be the year of the activist investor. These folks took a beating since 2007 but this should be their year. There is a ton of cash on corporate balance sheets but lots of underperformance in the current economic environment. We will see activist drive takeovers, restructures, and special dividends this year in my opinion. Recent filings of interest include strong activist positions in Surmodics(SRDX), SeaChange International (SEAC), and Energy Solutions. Tracking activist portfolios and 13D filings should be a very profitable activity in 2011.

I have been looking at some interesting new stuff with options as well I am not going to give most of it away just yet but I ll give you one stimulated by a recent list discussion. H and R Black is highly likely to go into a private equity portfolio next year. Management has made every mistake you can make and the loss of RALs is a big problem for the company. However the brand has real value. I do not want town the stock just yet but I like the idea of selling the January 2012 at $.70 to $.75. If you cash secure the put it's a 10% or so return if the stock stays above the strike. If it falls below I' ll be happy to own the stock with a 6 handle net. Back in 2008 everyone anticipated a huge default wave to hit the high yield market. Thanks to federal stimulus money pumping programs it did not happen. However in the spirit of sell the dog food the dog will eat a given moment the hedge fund world raised an enormous amount od distressed debt money. Thanks to this high yield spreads are far too low. CCC paper in particular is priced at absurd levels. These things trade like money good paper and much of it is not. Extend and pretend has helped but if the economy stays weak and interest rates rise rolling over the tsunami f paper due over the next few years becomes nigh onto impossible. I am going take small position in puts on the various high yield ETFs. If I am right they will explode when that market implodes. Continuing to talk my book I hope this happens. Among my nightly prayers is "Please God just one more two year period of asset rich companies with current payments having bonds trade below recovery value and I promise not to piss the money away this time. Amen.

PS. If you add in risk arbitrage spreads of 30% annualized returns along with this I would not object. Love, Tim.

I can't tell you what the markets will do. I do know that I want to own some safe and cheap stocks, some well capitalized small banks trading below book and participate in activist situation. I will be under invested in equities going into the year hoping my watch list becomes my buy list in market stumble. I will have put positions on long T-Bonds and high yield hoping for a large asymmetrical payoff.

Other than that I am clueless.

Kim Zussman comments: 

Does anyone else think this year is harder than usual to forecast? Is it better now to forecast based on market fundamentals or mass psychology? We are at a two year high in stocks, after a huge rally off the '09 bottom that followed through this year. One can make compelling arguments for next year to decline (best case scenarios already discounted, prior big declines followed by others, volatility low, house prices still too high, FED out of tools, gov debt/gdp, Roubini says so, benefits to wall st not main st, persistent high unemployment, Year-to-year there is no significant relationship, but there is a weak down tendency after two consecutive up years. ). And compelling arguments for up as well (crash-fears cooling, short MA's > long MA's, retail investors and much cash still on sidelines, tax-cut extended, employee social security lowered, earnings increasing, GDP increasing, Tepper and Goldman say so, FED herding into risk assets, benefits to wall st not main st, employment starting to increase).

Is the level of government market-intervention effective, sustainable, or really that unusual? The FED looks to be avoiding Japan-style deflation at all costs, and has a better tool in the dollar. A bond yields decline would help growth and reduce deflation risk. Increasing yields would be expected with increasing inflation; bad for growth but welcomed by retiring boomers looking for fixed income. Will Obamacare be challenged or defanged by states or in the supreme court? Will 2011 be the year of the muni-bubble pop?

A ball of confusion!

4 picks in equal proportion:

long XLV (health care etf; underperformed last year)

long CMF (Cali muni bond fund; fears over-wrought, investors still need tax-free yield)

short GLD (looks like a bubble and who needs gold anyway)

short IEF (7-10Y treasuries; near multi-year high/QE2 is weaker than vigilantism)

Alan Millhone writes:

 Hello everyone,

I note discussion over the rules etc. Then you have a fellow like myself who has never bought or sold through the Market a single share.

For myself I will stick with what I know a little something. No, not Checkers —

Rental property. I have some empty units and beginning to rent one or two of late to increase my bottom line.

I will not venture into areas I know little or nothing and will stay the course in 2011 with what I am comfortable.

Happy New Year and good health,



Jay Pasch predicts: 

2010 will close below SP futures 1255.

Buy-and-holders will be sorely disappointed as 2011 presents itself as a whip-saw year.

99% of the bullish prognosticators will eat crow except for the few lonely that called for a tempered intra-year high of ~ SPX 1300.

SPX will test 1130 by April 15 with a new recovery high as high as 1300 by the end of July.

SPX 1300 will fail with new 2011 low of 1050 before ending the year right about where it started.

The Midwest will continue to supply the country with good-natured humble stock, relatively speaking.

Chris Tucker enters: 

Buy and Hold


Wildcard:  Buy and Hold AVAV

Gibbons Burke comments: 

Mr. Ed Seykota once outlined for me the four essential rules of trading:

1) The trend is your friend (till it bends when it ends.)

2) Ride your winners.

3) Cut your losses short.

4) Keep the size of your bet small.

Then there are the "special" rules:

5) Follow all the rules.

and for masters of the game:

6) Know when to break rule #5

A prosperous and joy-filled New Year to everyone.



John Floyd writes:

In no particular order with target prices to be reached at some point in 2011:

1) Short the Australian Dollar:current 1.0220, target price .8000

2) Short the Euro: current 1.3375, target price 1.00

3) Short European Bank Stocks, can use BEBANKS index: current 107.40, target 70

A Mr. Krisrock predicts: 

 1…housing will continue to lag…no matter what can be done…and with it unemployment will remain

2…bonds will outperform as republicans will make cutting spending the first attack they make…QE 2 will be replaced by QE3

3…with every economist in the world bullish, stocks will underperform…

4…commodities are peaking ….

Laurel Kenner predicts: 

After having made monkeys of those luminaries who shorted Treasuries last year, the market in 2011 has had its laugh and will finally carry out the long-anticipated plunge in bond prices.

Short the 30-year bond futures and cover at 80.

Pete Earle writes:

All picks are for 'all year' (open first trading day/close last trading day).

1. Long EUR/USD
2. Short gold (GLD)

MMR (McMoran Exploration Corp)
HDIX (Home Diagnostics Inc)
TUES (Tuesday Morning Corp)

PBP (Powershares S&P500 Buy-Write ETF)
NIB (iPath DJ-UBS Cocoa ETF)
KG (King Pharmaceuticals)

Happy New Year to all,

Pete Earle

Paolo Pezzutti enters: 

If I may humbly add my 2 cents:

- bearish on S&P: 900 in dec
- crisis in Europe will bring EURUSD down to 1.15
- gold will remain a safe have haven: up to 1500
- big winner: natural gas to 8

J.T Holley contributes: 


The Market Mistress so eloquently must come first and foremost. Just as daily historical stats point to betting on the "unchanged" so is my S&P 500 trade for calendar year 2011. Straddle the Mistress Day 1. My choice for own reasons with whatever leverage is suitable for pain thresholds is a quasi straddle. 100% Long and 50% Short in whatever instrument you choose. If instrument allows more leverage, first take away 50% of the 50% Short at suitable time and add to the depreciated/hopefully still less than 100% Long. Feel free to add to the Long at this discretionary point if it suits you. At the next occasion that is discretionary take away remaining Short side of Quasi Straddle, buckle up, and go Long whatever % Long that your instrument or brokerage allows till the end of 2011. Take note and use the historical annual standard deviation of the S&P 500 as a rudder or North Star, and throw in the quarterly standard deviation for testing. I think the ambiguity of the current situation will make the next 200-300 trading days of data collection highly important, more so than prior, but will probably yield results that produce just the same results whatever the Power Magnification of the Microscope.

Long the U.S. Dollar. Don't bother with the rest of the world and concern yourself with which of the few other Socialist-minded Country currencies to short. Just Long the U.S. Dollar on Day 1 of 2011. Keep it simple and specialize in only the Long of the U.S. Dollar. Cataclysmic Economic Nuclear Winter ain't gonna happen. When the Pastor preaches only on the Armageddon and passes the plate while at the pulpit there is only one thing that happens eventually - the Parish dwindles and the plate stops getting filled. The Dollar will bend as has, but won't break or at least I ain't bettin' on such.

Ala Mr. Melvin, Short any investment vehicle you like that contains the words or numerals "perpetual maturity", "zero coupon" and "20-30yr maturity" in their respective regulated descriptions, that were issued in times of yore. Unfortunately it doesn't work like a light switch with the timing, remember it's more like air going into a balloon or a slow motion see-saw. We always want profits initially and now and it just doesn't work that way it seems in speculation. Also, a side hedge is to start initially looking at any financial institution that begins, dabbles, originates and gains high margin fees from 50-100 year home loans or Zero-Coupon Home Loans if such start to make their way Stateside. The Gummit is done with this infusion and cheer leading. They are in protection mode, their profit was made. Now the savy financial engineers that are left or upcoming will continue to find ways to get the masses to think they "Own" homes while actually renting them. Think Car Industry '90-'06 with. Japan did it with their Notes and I'm sure some like-minded MBA's are baiting/pushing the envelopes now in board rooms across the U.S. with their profitability and ROI models, probably have ditched the Projector and have all around the cherry table with IPads watching their presentation. This will ultimately I feel humbly be the end of the Mortgage Interest Deduction as it will be dwindled down to a moot point and won't any longer be the leading tax deduction that it was created to so-called help.


Short Gold, Short it, Short it more. Take all of your emotions and historical supply and demand factors out of the equation, just look at the historical standard deviation and how far right it is and think of Buzz Lightyear in Toy Story and when he thought he was actually flying and the look on his face at apex realization. That plus continue doing a study on Google Searches and the number of hits on "stolen gold", "stolen jewelery", and Google Google side Ads for "We buy Gold". I don't own gold jewelery, and have surrendered the only gold piece that I ever wore, but if I was still wearing it I'd be mighty weary of those that would be willing to chop a finger off to obtain. That ain't my fear, that's more their greed.

Long lithium related or raw if such. Technology demands such going forward.


Long Natural Gas. Trading Day 1 till last trading day of the year. The historic "cheap" price in the minds of wannabe's will cause it to be leveraged long and oft with increasing volume regardless of the supply. Demand will follow, Pickens sowed the seeds and paid the price workin' the mule while plowin'. De-regulation on the supply side of commercial business statements is still in its infancy and will continue, politics will not beat out free markets going into the future.

Long Crude and look to see the round 150 broken in years to come while China invents, perfects, and sees the utility in the Nuclear fueled tanker.

Long LED, solar, and wind generation related with tiny % positions. Green makes since, its here to stay and become high margined profitable businesses.


Short Sugar. Sorry Mr. Bow Tie. Monsanto has you Beet! That being stated, the substitute has arrived and genetically altered "Roundup Ready" is here to stay no matter what the Legislative Luddite Agrarians try, deny, or attempt. With that said, Long MON. It is way more than a seed company. It is more a pharmaceutical engineer and will bring down the obesity ridden words Corn Syrup eventually as well. Russia and Ireland will make sure of this with their attitudes of profit legally or illegally.

Prepare to long in late 2011 the commercialized marijuana and its manufacturing, distribution companies that need to expand profitability from its declining tobacco. Altria can't wait, neither can Monsanto. It isn't a moral issue any longer, it's a financial profit one. We get the joke, or choke? If the Gummit doesn't see what substitutes that K2 are doing and the legal hassles of such and what is going on in Lisbon then they need to have an economic lesson or two. It will be a compromise between the Commercial Adjective Definition Agrarians and Gummit for tax purposes with the Green theme continuing and lobbying.

Short Coffee, but just the 1st Qtr of 2011. Sorry Seattle. I will also state that there will exist a higher profit margin substitute for the gas combustible engine than a substitute for caffeine laden coffee.

Sex and Speculation:

Look to see go public in 2011 with whatever investment bank that does such trying their best to be anonymous. Are their any investment banks around? This Boxxx will make Red Box blush and Apple TV's box envious. IPTV and all related should be a category that should be Longed in 2011 it is here to stay and is in it's infancy. Way too many puns could be developed from this statement. Yes, I know fellas the fyre boxxx is 6"'s X 7"'s.


This is one category to always go Long. I have vastly improved my guitar playin' in '10 and will do so in '11. AAPL still has the edge and few rivals are even gaining market share and its still a buy on dips, sell on highs empirically counted. They finally realized that .99 cents wasn't cutting it and .69 cents was more appropriate for those that have bought Led Zeppelin IV songs on LP, 8-track, cassette, and CD over the course of their lives. Also, I believe technology has a better shot at profitably bringing music back into public schools than the Federal or State Gummits ever will.


Long - Your mind. Double down on this Day 1 of 2011. It's the most capable, profitable thing you have going for you. I just learned this after the last 36 months.

Long - Counting, you need it now more than ever. It's as important as capitalism.

Long - Being humble, it's intangible but if quantified has a STD of 4 if not higher.

Long - Common Sense.

Long - Our Children. The media is starting to question if their education is priceless, when it is, but not in their context or jam.

Short - Politics. It isn't a spectator sport and it has been made to be such.

Short - Fear, it is way way been played out. Test anything out there if you like. I have. It is prevalent still and disbelief is rampant.

Long - Greed, but don't be greedy just profitable. Wall Street: Money Never Sleeps was the pilot fish.

I had to end on a Long note.

Happy New Year's Specs. Thanks to all for support over the last four years. I finally realized that it ain't about being right or wrong, just profitable in all endeavors. Too many losses led to this, pain felt after lookin' within, and countin' ones character results with pen/paper.

Russ Sears writes:

 For my entry to the contest, I will stick with the stocks ETF, and the index markets and avoid individual stocks, and the bonds and interest rates. This entry was thrown together rather quickly, not at all an acceptable level if it was real money. This entry is meant to show my personal biases and familiarity, rather than my investment regiment. I am largely talking my personal book.

Therefore, in the spirit of the contest , as well as the rules I will expose my line of thinking but only put numbers on actual entry predictions. Finally, if my caveats are not warning enough, I will comment on how a prediction or contest entry differs from any real investment. I would make or have made.

The USA number one new product export will continue to be the exportation of inflation. The printing of dollars will continue to have unintended consequences than its intended effect on the national economy but have an effect on the global economy.. Such monetary policy will hit areas with the most potential for growth: the emerging markets of China and India. In these economies, that spends over half their income on food, food will continue to rise. This appears to be a position opposite the Chairs starting point prediction of reversal of last year's trends.

Likewise, the demand for precious metals such as gold and silver will not wane as these are the poor man's hedge against food cost. It may be overkill for the advanced economies to horde the necessities and load up on precious metals Yet, unlike the 70's the US/ European economy no longer controls gold and silver a paradigm shift in thinking that perhaps the simple statistician that uses weighted averages and the geocentric economist have missed. So I believe those entries shorting gold or silver will be largely disappointed. However in a nod to the chair's wisdom, I will not pick metals directly as an entry. Last year's surprise is seldom this year's media darling. However, the trend can continue and gold could have a good year. The exception to the reversal rule seems to be with bubbles which gain a momentum of their own, apart from the fundamentals. The media has a natural sympathy in suggesting a return to the drama of he 70's, the stagflation dilemma, ,and propelling an indicator of doom. With the media's and the Fed's befuddled backing perhaps the "exception" is to be expected. But I certainly don't see metal's impending collapse nor its continued performance.

The stability or even elevated food prices will have some big effects on the heartland.

1. For my trend is your friend pick: Rather than buy directly into a agriculture commodity based index like DBA, I am suggesting you buy an equity agriculture based ETF like CRBA year end price at 77.50. I am suggesting that this ETF do not need to have commodities produce a stellar year, but simply need more confirmation that commodity price have established a higher long term floor. Individually I own several of these stocks and my wife family are farmers and landowners (for full disclosure purposes not to suggest I know anything about the agriculture business) Price of farmland is raising, due to low rates, GSE available credit, high grain prices due to high demand from China/India, ethanol substitution of oil A more direct investment in agriculture stability would be farmland. Farmers are buying tractors, best seeds and fertilizers of course, but will this accelerate. Being wrong on my core theme of stable to rising food/commodity price will ruin this trade. Therefore any real trade would do due diligence on individual stocks, and put a trailing floor. And be sensitive to higher volatility in commodities as well as a appropriate entry and exit level.

2. For the long term negative alpha, short term strength trade: I am going with airlines and FAA at 49.42 at year end. There seems to be finally some ability to pass cost through to the consumer, will it hold?

3. For the comeback of the year trade XHB: (the homebuilders ETF), bounces back with 25% return. While the overbuilding and vacancy rates in many high population density areas will continue to drag the home makes down, the new demand from the heartland for high end houses will rise that is this is I am suggesting that the homebuilders index is a good play for housing regionally decoupling from the national index. And much of what was said about the trading of agriculture ETF, also apply to this ETF. However, while I consider this a "surprise", the surprise is that this ETF does not have a negative alpha or slightly positive. This is in-line with my S&P 500 prediction below. Therefore unless you want volatility, simply buying the S&P Vanguard fund would probably be wiser. Or simply hold these inline to the index.

4. For the S&P Index itself I would go with the Vanguard 500 Fund as my vehicle VFINXF, and predict it will end 2011 at $145.03, this is 25% + the dividend. This is largely due to how I believe the economy will react this year. 

5. For my wild card regional banks EFT, greater than IAT > 37.50 by end 2011…

Yanki Onen writes:

 I would like to thank all for sharing their insights and wisdom. As we all know and reminded time to time, how unforgiven could the market Mistress be. We also know how nurturing and giving it could be. Time to time i had my share of falls and rises. Everytime I fall, I pick your book turn couple of pages to get my fix then scroll through articles in DSpecs seeking wisdom and a flash of light. It never fails, before you know, back to the races. I have all of you to thank for that.

Now the ideas;

-This year's lagger next year's winner CSCO

Go long Jan 2012 20 Puts @ 2.63 Go long CSCO @ 19.55 Being long the put gives you the leverage and protection for a whole year, to give the stock time to make a move.

You could own 100,000 shares for $263K with portfolio margin ! Sooner the stock moves the more you make (time decay)

-Sell contango Buy backwardation

You could never go wrong if you accept the truth, Index funds always roll and specs dont take physical delivery. This cant be more true in Cotton.

Right before Index roll dates (it is widely published) sell front month buy back month especially when it is giving you almost -30 to do so Sell March CT Buy July CT pyramid this trade untill the roll date (sometime at the end of Jan or begining of Feb) when they are almost done rolling(watch the shift in open interest) close out and Buy May CT sell July CT wait patiently for it to play it out again untill the next roll.

- Leveraged ETFs suckers play!

Two ways to play this one out if you could borrow and sell short, short both FAZ and FAS equal $ amounts since the trade is neutral, execute this trade almost free of margin. One thing is for sure to stay even long after we are gone is volatility and triple leveraged products melt under volatility!

If you cant borrow the shares execute the trade using Jan 12 options to open synthetic short positions. This trade works with time and patience!

Vic, thanks again for providing a platform to listen and to be heard.


Yanki Onen

Phil McDonnell writes: 

When investing one should consider a diversified portfolio. But in a contest the best strategy is just to go for it. After all you have to be number one.

With that thought in mind I am going to bet it all on Silver using derivatives on the ETF SLV.

SLV closed at 30.18 on Friday.

Buy Jan 2013 40 call for 3.45.
Sell Jan 2012 40 call at 1.80.
Sell Jul 25 put at 1.15.

Net debit is .50.

Exit strategy: close out entire position if SLV ETF reaches a price of 40 or better. If 40 is not reached then exit on 2/31/2011 at the close.

George Parkanyi entered:

For what it's worth, the Great White North weighs in ….
3 Markets equally weighted - 3 stages each (if rules allow) - all trades front months
3 JAN 2011
BUY NAT GAS at open

BUY SILVER at open

BUY CORN at open
28 FEB 2011 (Reverse Positions)
SELL and then SHORT NAT GAS at open

SELL and then SHORT SILVER at open

SELL and then SHORT CORN at open
1 AUG 2011 (Reverse Positions)
COVER and then BUY NAT GAS at open

COVER and then BUY SILVER at open

COVER and then BUY CORN at open
Hold all positions to the end of the year

3 JAN BUY PLATINUM and hold to end of year.


. Markets to unexpectedly carry through in New Year despite correction fears.

. Spain/Ireland debt roll issues - Europe/Euro in general- will be in the news in Q1/Q2

- markets will correct sharply in late Q1 through Q2 (interest rates will be rising)

. Markets will kick in again in Q3 & Q4 with strong finish on more/earlier QE in both Europe and US - hard assets will remain in favour; corn & platinum shortages; cooling trend & economic recovery to favour nat gas

. Also assuming seasonals will perform more or less according to stats

If rules do not allow directional changes; then go long NAT GAS, SILVER, and CORN on 1 AUG 2011 (cash until then); wild card trade the same.

Gratuitous/pointless prediction: At least two European countries will drop out of Euro in 2011 (at least announce it) and go back to their own currency. 

Marlowe Cassetti enters:

FXE - Currency Shares Euro Trust

XLE - Energy Select

BAL - iPath Dow Jones-AIG Cotton Total Return Sub-Index

GDXJ - Market Vectors Junior Gold Miners

AMJ - JPMorgan Alerian MLP Index ETN

Wild Card:


VNM - Market Vectors Vietnam ETF

Kim Zussman entered: 

long XLV (health care etf; underperformed last year)
long CMF (Cali muni bond fund; fears over-wrought, investors still
need tax-free yield)
short GLD (looks like a bubble and who needs gold anyway)
short IEF (7-10Y treasuries; near multi-year high/QE2 is weaker than



A little chart gazing I was doing showed the following:

Not sure if it's statically significant i.e 14 years only set, and 2 month window, but I can hear a strangle coming up, and maybe even a small backpocket outright short,

March –April Turning Points in U.S. SP500


5 out of 14 years, the March/April month has seen a turn that has resulted in the price closing the year at the inverse extreme.

11 out of 14 years has seen the market not break the March/April extreme in price for at least the following 3 month period.

Note: Bill Gross of Pimco has suggested that in the past 15 years, every time the fed funds rate was higher than thenominal GDP growth rate, assets such as stocks and/or housing always fell. He even suggested that the best way to price the fed funds rate would be 100 basis points below the nominal GDP growth rate.

This is not a situation at the moment.

Phil McDonnell writes: 

Remember that extrema are only known in hindsight. Also remember that extrema are governed by the ArcSine distribution which is counter intuitive once you get the normal distribution wired in your head. One of the corollaries of this is that extrema occur early or late in the given time frame but not so much in the middle time period. Also be aware that the ArcSine is a U shaped distribution. This means that ALL of the distribution is in the tails, little in the middle. So you need much larger samples than for a normal distribution.

This is not meant to throw cold water on Craig's interesting line of thought, but more an explanation of why I try to avoid extrema lines of inquiry. Ultimately you would need to test this using a randomized bootstrap simulation to see where it lies. I suspect n=14 is too small though, but might be fine for a normal dist..



USPS, from Phil McDonnell

December 20, 2010 | 1 Comment

At our local post office, at the morning opening the line was 37 deep. They only had 1 person at the desk and some customers took as much as 20 minutes to complete their orders. The institution should be closed. It is obsolete and not cost effective. It is fundamentally customer antagonistic. UPS and Fed Ex do a better job.

Victor Niederhoffer comments:

As Nock pointed out, the first thing a govt does is to establish a
postal service so that they can collect the service benefits.

Stefan Jovanovich writes:

Our political parties take their origin from Jefferson's wanting to take the Post Office away from Hamilton's Treasury Department and give it to his Department of State. As Nock observed, the argument was about patronage: Hamilton already had the customs officers. Jefferson wanted the postmasters. The Whiskey Rebellion was hardly the great blow for freedom that Jefferson's orations have led people to think. He and Madison were upset by Washington (and Hamilton's) success in establishing the excise because it meant rewards for the Federalists/Whigs patronage constituency. That arguments about the national bank had the same origin. It is hardly surprising that the first thing Jefferson and Madison each did as President was try to establish an embargo that would starve the customs officers while at the same time embarking on a program of expanded postal roads.



Does anyone have good thoughts or conventions on how to factor entry/exit slippage in futures markets? I am trying to find a general rule and google searches of academic papers result in not a lot and what I do find is a bit in excess for my needs.

My thought was to assign a rule such as when my entry/exit sizes combined total <0.50% of the average daily volume it would be safe to assume 1 tick worth of slippage per side. Ex. bid/ask 500/500.25 then assume sell/buy price at 499.75/500.50 (assuming a market that trades in 0.25 increments). Granted this would not happen in all instances but very likely not all fills would be at disadvantageous levels so the average slippage over time of this magnitude seemed fair. The scale could be increased as the percentage of average daily volume increased (i.e. <1.5% assume 2 ticks, <3% 3 ticks, etc.). A time of day factor might also be useful (i.e. pit vs electronic hours) as the liquidity is certainly better at peak trading times. Without very robust data this is difficult to test/determine so I wanted to see what the specs think.

Larry Williams comments:

It depends on the market and also on news of the day. Sometimes there's no slip at all other times it's massive so a decent trader would factor such things into his or her trading style; the problem is mechanical systems have trouble doing that which an individual can do.

Phil McDonnell writes:

There is no slippage with limit orders. Either you get your price or do not trade. If your testing can make a decision based on previous time periods. Then a simulated limit order can be placed. If the low for the next period is below the limit then you got filled on a buy. If the high is above the limit then you know you got filled. The tricky case comes in where the limit is exactly equal to the respective extrema. In that case I would suggest two ways of testing.
1. Assume 50:50 chance of a fill, take them at random.
2. Assume no fills at the exact bottom tick or top tick.

I recommend doing both tests. The 50:50 is probably realistic, but the no fills scenario tells you if the system might depend heavily on getting these top and bottom tick trades.

Larry Williams writes:

Phil's point is why I buy a small partial position on stop, then rest on a limit. This has helped my short term trading a great deal.

Jim Lackey comments: 

One should always be a gentleman here. How to trade is the easy part. How much to trade, when to trade and when to exit a trade are the difficult questions.

You can get partial fills, sub penny or fractional orders. Your limit is like a big round number for order sniffers HFT's other traders once made public. Everyone knows we should scale into positions.

When volatility is very low and liquidity is very high it's much easier to enter with out slippage.

The original mechanical question should be adjusted for volatility. I remember 2 times in year 2000 and again in the fall crash of 2008 where I used basically market orders with a price limit. Simply bidding through the current price to start + X ticks to start a scale or to end one. Back in those days the markets might rally 3% in an afternoon so you had to get some on.

Opens and closes are best to use at the market orders. However for the mechanics market at open or closes can be the best or the worst price of the day then your in either deep trouble all in on the high tick, a trend down or lucky you caught a trend day up.

The problem has been that since the markets have become more mechanical its the big up opens that continue to go up and the down opens that have gone straight down. These are order ladders and the moves are over by 10am. It was confusing to see the markets gap big and the entire day over by 10 or 11am. Now we are used to it…perhaps time for a change.

What is wild is to see the govie bond markets move a couple percent a day and the SNP move 1% and the ebbs and flows between stocks bonds and those indexing commodity etf's for investment over the next 100 years are guaranteed to lose.

Chris Cooper writes:

I often have the problem called "adverse selection" with my limit orders, in forex or futures. This is not a problem with small orders, but when your order is larger, you may (frequently) see a partial fill, then the market turns around in your favor and you make a profit. But the profit is not as large as it would be if your order had been filled to completion. The times when your order is completely filled, the market has moved through your price point and past it, usually. You are sitting on a loss if marked to market, and that loss is for your entire size. In other words, you get the bad fills when you really want to be filled, and the good fills when you don't want them (in retrospect). It's a big problem for short term trading.

Similarly, in markets with a long order queue such as ES, by the time your order is filled the market has pretty much moved past you and you are sitting on a loss. Unless you can play games with pre-positioning your order in the queue, you will always see this slippage with limit orders.

Jonathan Bower writes: 

You "could" avoid posting your limit order for bots, hfts, etal especially if it is of consequence (size) by working it semi-"silently" in an attempt to not get "screwed". One of the earliest execution algorithms was the "iceberg" where a limit order could be placed in (user defined) pieces, once taken out another one will replace it until your order is filled. Of course this is easy for those who want to to sniff it out. More recently you can add variance to your lot size firing in somewhat random orders as part of an iceberg. Or you could set a timed order to release a limit order (or combination of orders) based on a print, bid, or ask with what/if OCO ammendments, etc etc etc.

The bottom line if you need to be and can be creative with order execution especially in illiquid markets. Of course being right about the trade idea is still the hardest part…

Chris Cooper adds:

GLOBEX does not have liquidity that is as good as the forex interbank market, especially in the Asian hours. If you are trading smaller quantities, in New York hours, then futures are a better choice than forex.

If you are not getting filled when you should be, then your forex broker probably has what is called a "last look" provision in their system. This allows the liquidity providers a chance, say for 30 seconds, to decide not to fill your limit order. This has been an annoying problem for me in the past. The solution is to switch to a broker without this provision. It could also happen if your broker is not an ECN, and in that case you should find a new broker.

Jeff Watson adds:

There were (and still are) some people in the pit who made an excellent living with just the ability to tell when the market is going from quarter bid to quarter sellers. That, in itself is a huge edge.




 "Apple sold 4.19 million iPads last quarter, may have trouble hitting some analysts' estimates of 6 million sold in the fourth quarter".

Apple drop following to the news (may be this is an appetizer for what is going to happen this Christmas?) found new buyers at lunch time. If you read stocktwits or twitter now you can find Apple's fans brag about buying today's low. An indicator could be built using social networks' posts. The users normally are positively biased toward the stock they follow. They represent the "herd". Depending how large the group is, you could model their strength and ability to influence price in the short-term. Top trending tickers are AAPL, SPY, ES_F, GOOG, GLD. Does anyone know if this has already been tested?

Phil McDonnell comments:

A Googler did a research paper on the most searched ticker symbols on their engine and found that the top searches tended to go up for a few days. I do not have the link.



As far as I have ever been able to ascertain, Larry Williams was the first to attempt to apply the Kelly Criterion to outright position trading, and the first to openly discuss it. His pursuit in this regard not only was my initial immersion to the ideas, but he funded those attempts. Whatever I've uncovered along the way is a product of that — Larry's unquenchable curiosity, fearlessness regarding risk, and willingness to fund pursuits others would never touch.

A couple of points further in the post worth mentioning here because I think the other interested members deserve to have light shed on some misconceptions, some of which are a little dangerous to ascribe to, but are widely held.

"One "plays" forever, or practically forever."

But no one does and no one can, and it is this very notion of there being a finite "horizon," that changes not only the calculation of a growth optimal fraction, but every other metric related to it, giving rise to an entirely new discipline in and of itself.

"If one is somewhat risk averse, one can establish a half Kelly criterion, essentially betting half one's full Kelly bet. This results in a lower probability of one's bankroll halving."

But why "half?" Why this arbitrary number? (Or any other arbitrary dilution for that matter?) Remember, we're dealing with a function that has an optimal point, implying a curve, and it is the nature of this curve that is important to us. Being at different points on the curve has vastly different implications to us. Further, the various and important watershed points almost all are a function of that "horizon" mentioned earlier, i.e. the points migrate about this curve as a function of that horizon. Advocates of a "Half Kelly," or other arbitrary point along this chronomorphic curve (with respect to the horizon and events transpired) are seemingly unaware of the implications of their arbitrarily-chosen points.

"The criterion is to maximize the expected value of the logarithm of one's bankroll."

Yes, that is the Kelly Criterion which, in trading, does NOT result in the growth optimal fraction but a far more aggressive (and dangerous, without growth-commensurate benefit) number. No one seems to understand this.. The number returned in determining the value that satisfies the Kelly Criterion can be converted into a growth optimal number (which I call the optimal fraction. or optimal f) but in and of itself, the value that satisfies the Kelly Criterion is NOT the growth optimal fraction in trading. Incidentally, the so-called Kelly Formulas (put forth by Thorp I believe, and market applications attempted by Larry Williams in the mid-1980s) do NOT satisfy the Kelly Criterion in trading applications, but DO in gambling ones (that is, in trading applications they will not yield the same results as the value which satisfies the Kelly Criterion. The Kelly Formulas do, for dual-outcome situations, return the growth optimal fraction). For more on this I can only refer those interested to the most recent Journal of the International Federation of Technical Analysts 11 (available at admin at ifta dot org) or the 2-day course on Risk-Opportunity Analysis I am having in Tampa Nov 13 & 14 see

"The biggest issue of application is that one makes many assumptions about statistical distributions, correlations, returns, etc. that are all wrong."

I agree. In a strange, ironic twist to my modest participation to this story, it was (again, but some decades later) Larry Williams (rather recent) insistence of a way to apply what I know of growth maximization in a robust way. As a result of the pollenization of these ideas by Larry, I can state unequivocally that there are clear, simple, mathematical solutions to these impediments — in short, if someone wishes to apply a growth optimal approach to their future trading, these impediments ARE readily surmountable. But be certain your criterion is growth optimality, and be sure you really want to get into the cage and fight the gorilla. Most just want to sit and watch Dancing with the Stars.

Nick White comments:

Dancing with the stars….brilliant and well said.

We're all fortunate beneficiaries of Mr. Vince's investigations into the intricacies of these issues.

Phil McDonnell writes:

Kelly originally wrote his paper based on race track examples with binary outcome. You won or lost with assumed probabilities and you knew the wager size and payoff. So strictly speaking his formula only applies to wagers with two outcomes. Even a blackjack hand has at least five possible outcomes (win, lose, blackjack, double down, split) and not just two so strictly speaking Kelly's formula does not apply. Some people have erroneously tried to modify the binary Kelly formula by using average win size and average loss size to compute. All such formulas are dead wrong. The reason is that, in general, the average log does not equal the log of the average.

As Larry Williams pointed out most people do not feel comfortable using the optimum log approach even if the math is done correctly. I believe there is a simple reason for this. Most people do not have a simple logarithmic utility function. Rather they seek to maximize ln( ln w), where w is wealth. This is an iterated log function and results in a much more conservative ride. I talk about this distinction toward the end of my book. Ralph Vince also has written extensively on this subject using his term optimal f.

There is another issue with simply maximizing returns and that is it may not really take into account risk in a proper manner. It is true that the log function weights the largest loss the most in a non-linear manner and reduces the weights of gains so that the largest gains are weighted sub-linearly. But that may still not be enough to satisfy one's real risk aversion. That is part of my argument for the iterated log form but it may be that an explicit metric such as standard deviation is still needed.

Larry Williams writes:

Optimal or Maximum Wealth (possible gain) only comes with Maximum Risk; therein lies the problem. Not loosing…risk…is more important than gain in the art of speculation business.

Chris Cooper writes:

More important, as far as my practical experience goes, is that one's estimate of the edge is always subject to uncertainty. The reasons have been discussed on this list before, but certainly include changing regimes, limited history for the models, curve fitting, flexionic machinations, scaling nonlinearity, etc. I relied on the Kelly formula extensively in the mid-'70s when gambling, and uncertainty in your edge was no less important then. The problem arises because overestimating your edge is so destructive to your terminal wealth.

It might be interesting academically to consider an approach, such as Bayesian, where your estimate of the edge is not stationary, but in fact must decrease when you hit a losing streak.

James Arveson writes:

I am a newbie on this site, but I can assure y'all that any finite amounts of outcomes can easily be handled by maximizing the expected value of the logarithm of one's fortune. I have also executed these theoretical outcomes for many years in AC and LV in BJ, and yes, in Bethlehem, PA in Texas Hold 'Em. See Mathematics of Poker for a better exposition of these issues than I could ever present.

Remember that each bet is a single bet, and one can bet forever. Leo Breiman has actually proved that (in the most general cases) that this approach DOMINATES all other strategies.

Now, IMHO, this approach is irrelevant to the market. NO ONE can get all the statistical assumptions correct-statistical distribution, EV, correlation, return, s.d., etc.

Have fun until we get to the next level. Same goes for Markowitz. Check out I have no piece of their puzzle but wish I did (I might be able to get a write-off ski trip to Lake Tahoe where they are located).

Actualizing all of this crap may be the next Nobel Prize in Econ, but it will probably not help schlepers make money in the markets.

Ralph Vince replies:


Pursuing awards is for schlepers like Krugman or other academic dweebs –it's an award voted upon by dweebs for dweebs, and its pursuit bridles and constrains the mind (as *any* political pursuit will. Usually, the truth lies with things that - people off). To-wit, the lack of challenge to the notion that Kelly presents on p925 in the conclusion of his now-famous paper wherein he asserts that geometric growth is maximized by the gambler betting a fraction such that "at every bet he maximizes the the expected value of the logarithm of his capital."

This is accepted by the gambling community, and, by extension (falsely, mistakenly) accepted by the trading community. HOWEVER, a critical analysis of this notion reveals that it does NOT result in the growth optimal fraction, but rather in a multiplier of one's account to risk (the two are different indeed, the latter being less than or equal to the former, resulting often in over-wagering). In fact, the multiplier on one's stake equals the optimal fraction to risk only in certain, specific instances which manifest in gambling, but are rare still in trading (e.g. only on long positions, etc.). I would gladly go into this in depth put I cannot publicly do so as the paper on this has been publish in a current issue of a journal, and I have agreed to refer those interested to the article instead. The upshot is, that the Kelly Criterion, as specified above, is not what Kelly and others thought it was except in the special case I just mentioned — it is NOT the growth-optimal fraction, but something different, equal to the growth-optimal fraction only in the special case — a case that manifests in gambling with ubiquity, and oddly, in trading very rarely.

Again, the gambling community has accepted it for reasons mentioned –because it does give you the same answer for the optimal fraction to bet as the formulations for the optimal fraction in the gambling situations. But just because it gives you he same answer as the optimal fraction in special situations does not mean it is the formulation for the optimal fraction –it isn't.

Secondly, even the "optimal fraction"it is never optimal. Suppose you are playing a game with a 50% probability and odds of 2 to 1. Your optimal fraction is .25 (if you were to play forever). However, after the first pay, the phone rings, it;s your wife, and she informs you of an emergency and you have to bolt the game (with your winnings from the one play, make you a popular guy). If you knoew beforehand you were going to only play for 1 play, you should have bet 100% of your stake to maximize your gain. If the call came after two plays in this game, you should have bet .5.

Tomorrow, you come back to this game — and you bet .25, reconciling yourself that yesterday you bet .25. (so….the game possesses memory?)

Wait, it gets worse in trading, where we see that each individual bet is, in fact, NOT a bet. Let's say you trade only XYZ stock, and you put on 300 shares. Let's say you have a stop below your buy price but it;s a different level for each of 100 shares, so you have three stops below the proce for 100 shares each at different levels. Now, let's say onyl the closest stop, for 100 shares, gets hit, resulting in a loss on 100 of the three hundred shares. Weeks later, you sell out 100 shares at a profit, and, a few weeks after that, another 100 shares at a price higher than that.

But these are NOT three separate trades. This is ONE trade, one wager for the purposes of growth-optimal calculations. And the reason is because you are ONLY trading XYZ — there has been NO recalculation of positions to put on until the entire thing has been closed out. IF, on the other hand, you were having other trades throughout the course of your aggregate position in XYZ, then you WOULD consider each of these a separate trade.

Trading is not the same as gambling. There are similarities, but don't make the assumption that because you risk something and gain something that it is the same. There are things which are proxies for truth, that asymptotically appear to be truth, but they are only proxies (such as the Kelly Criterion) as well as the widely-held (in the gambling community, and hence the trading one as well) but incorrect notion that a wager should be assessed based on it's asymptotic mathematical expectation. This too is a mere proxy and an incorrect one that can, in extreme cases, lead one to accept bad wagers and reject favorable ones.

Again, critical thinking has been absent and trumped by the acceptance of industry catechism.

Finally, you speak of SD's and EV (mean-variance is dead incidentally, as dead as dead can be everywhere BUT academia) correlations, and Chris mentions the (valid) problems of assessing the edge in the future and the problem of non-stiationarity.

The solution to growth optimality in the markets, lies in NOT accepting the Kelly Criterion, but instead accepting what IS the growth optimal fraction– because that then reveals (in the simplest of ways!) how to address the problem of non-stationarity in the future and it doesn't require any of these parameters, or even a computer, it's really THAT simple if you want to attempt growth optimality in the future.

Phil McDonnell comments:

Ralph raises a lot of interesting philosophical questions. On some points I disagree, so let me elaborate. For the purposes of this piece I will assume one is entirely risk averse and seeks only to maximize expected wealth on a compounded growth basis.

First he raises the point that there is no guarantee that a game or investment opportunity will continue. Certainly a true statement. However it is also true that there will be a succession of such opportunities available in one's lifetime. Thus some rational basis for choosing bet size each time should include consideration of expected logs of the outcomes.

Philosophically I disagree with Ralph's analysis of bet it all on the last bet. His math is correct, in that it will maximize the expected dollar outcome. But there will always be other bets, so one's lifetime objective should still be to maximize the expected log not simply the arithmetic expected value. I believe Kahneman and Tversky made the same error in their Nobel winning papers.

I have an alternate take on Ralph's argument that it is hard to define a trade because you can put on 300 shares and exit 3 times at different prices, unknowable in advance. Rather than look on each trade as the basic metric one should look on the portfolio as the metric and a basic unit of time as the portfolio re balancing decision point. For example if you invested .25 of your wealth in a trade that doubled you know have .50 of your 1.25 wealth in the trade. That is too much if you want to maintain the .25 ratio so you need to sell .1875 to get back to your optimal ratio. But the simplest way to look at it is to look at the investment portfolio in each time period, be it a day, week or whatever.

One of the reasons the mean covariance model is in disfavor is that it seems to fail when everything hits the fan. In fact the model is incomplete in the sense that EV and COV are stochastic variables and vary over time. (I am implicitly including VAR here.) You need to explicitly include the correlations somehow in order to take into account how an entire portfolio will vary together. Using the formulas for optimal bet size on a trade level will always lead to serious over trading if there are multiple trades put on at the same time except in the case of a negative correlation between the trades. So it is misleading to calculate an optimal trade size for one system or one trade without consideration of any others that might be on at the same time. At best it is a dangerous upper bound for any single trade size. But it will almost always be an estimate too high. Optimization of expected log of wealth can only be done at the portfolio level.

Ralph Vince responds:


I am not raising ANY "philosophical questions." Just because people may have to think about them doesn't make them philosophical questions as opposed to facts:

1. The value that satisfies the Kelly Criterion is NOT the (growth) optimal fraction of ones stake to risk (although, in special circumstances which we find ubiquitously in gambling and not in trading, it is an equivalent value to the value that IS the optimal fraction). And the pervasive mistake by those attempting growth maximization in the marketplace of using the Kelly Criterion result puts then OVER exposed, to their unwitting peril. They are NOT growth optimal. In fact, the value that satisfies the Kelly Criterion NEVER returns the growth optimal fraction. This was a mistake on the part of Kelly and Shannon. The very fact that it is still accepted by others is testimony to the absence of critical thinking in this matter.

2. Further, what IS the growth optimal fraction is a function of the horizon of the game — and all games have a horizon, including the game of evolution on earth. Further, all metrics, including the analysis of drawdowns (including VAR where a horizon of 1 is implicit), even the analysis of whether a wager should be accepted or not, are a function of horizon. Disregarding the horizon leads us to incorrect conclusions at every turn in risk-opportunity analysis. In fact, it is the necessary introduction of "horizon" that gives rise to this entire burgeoning discipline.

3. Once we accept points 1 and 2 above, the obvious solution to solving for the non-stationarity of the distribution of outcomes we are dealing with becomes obvious. Growth-maximization, unlike attempts at it in the past, now CAN be performed with informed assessments of what the best growth optimal fraction value to use in the future will be.



 The National Enquirer to file for bankruptcy.



 While natural gas has been the butt of jokes after 50 out of 50 winners…The one loser on my screen was the bank index bkx & BAC. It may be too early to call a trend, but I have noticed that 6 days so far in Oct the bank index has been down while the S&P has been up. Most of these have been since Oct 13th when the markets started hammering the banks over servicing mbs and foreclosures.

Looking at each quarter, the S&P was highly correlated with the bank index from 2003 late 2008. In hindsight it seems so clear that the banks index switching from low or average beta to a high beta correlation to the S&P index was a sign of the impending explosion before Lehman hit the beta for the 3rd quarter 2008 was 2.70 according to my regression. This is after a fairly stable Beta hovering around 1.0 .

Looking back during the 90s when tech not banks were driving the market, the beta of the bank index on any given quarter would bounce around and the correlation would also, but in general was much lower (the bank index data I had only went back to March 1993).

Of course with banks were issuing those IPO's back in the 90s where as by aughts they were switching to securitization and financial engineering to manfacture their edge.

But do banks still matter? With the government effectively backstopping their balance sheet, do they really have a reason to exist? (aside from the political gains do they havea wealth creation reason?) If not, does "too big to fail" still apply if they do not fit the political agenda?

What are the new numerical disconnect saying?

S&P r        BKX r        correl      Beta        Alpha  quarter          Year
0.0381     -0.0150     0.58344     1.16939     -0.0035    oct     2010
0.1018     0.00173     0.93421     1.64995     -0.0026     3     2010
-0.126     -0.1199     0.92693     1.42600      0.001      2     2010
0.0475     0.19681     0.69486     1.18386      0.0023     1     2010
0.0534     -0.0999     0.84697     1.64582     -0.0029     4     2009
0.1396     0.25845     0.78197     1.62397      0.0005     3     2009
0.1416     0.25874     0.84468     2.78847     -0.0022     2     2009
-0.124     -0.4542     0.84269     2.43938     -0.0025     1     2009
-0.255     -0.4237     0.81996     1.23216     -0.0017     4     2008
-0.092     0.15255     0.91565     2.57134      0.0061     3     2008
-0.032     -0.3060     0.75759     1.54808     -0.004      2     2008
-0.104     -0.1154     0.85674     1.68488      0.001      1     2008
-0.038     -0.1793     0.86751     1.50680     -0.0019     4     2007
0.0154     -0.0629     0.85999     1.23968     -0.0013     3     2007
0.0564     -0.0085     0.83763     1.00614      -0.001     2     2007
0.0018     -0.0316     0.91944     1.09838     -0.0006     1     2007
0.0576     0.03269     0.75834     0.83588     -0.0002     4     2006
0.0482     0.04607     0.83727     0.98334      0          3     2006
-0.021     0.01923     0.77312     0.89102      0.0006     2     2006
0.0407     0.02143     0.79510     0.95712     -0.0003     1     2006
0.0166     0.07061     0.78553     0.91498      0.0009     4     2005
0.0229     -0.0276     0.84186     0.99538     -0.0008     3     2005
0.0161     0.02979     0.84171     0.89760      0.0002     2     2005
-0.026     -0.0753     0.85131     0.98382     -0.0008     1     2005
0.0837     0.06477     0.90318     1.02108     -0.0003     4     2004
-0.023     0.00936     0.85927     0.85178      0.0005     3     2004
0.0162     -0.0401     0.82188     1.02596     -0.0009     2     2004
0.0114     0.03282     0.91278     0.92618      0.0004     1     2004
0.0974     0.09482     0.87883     0.89619      0.0001     4     2003
0.0323     0.03224     0.88914     1.07428      0          3     2003
0.1388     0.19254     0.93348     1.10238      0.0006     2     2003
-0.036     -0.0558     0.96863     1.01468     -0.0003     1     2003
0.0761     0.07047     0.92250     1.30637     -0.0005     4     2002
-0.193     -0.1740     0.93277     1.12174      0.0007     3     2002
-0.146     -0.0743     0.87331     1.00450      0.0011     2     2002
-0.001     0.03820     0.89408     1.26995      0.0008     1     2002
0.0979     0.08147     0.78028     1.05444     -0.0004     4     2001
-0.163     -0.1527     0.89156     0.97725      0.0001     3     2001
0.0723     0.13445     0.80468     0.89475      0.0011     2     2001
-0.136     -0.1037     0.79788     1.19917      0.001      1     2001
-0.103     0.03487     0.71966     1.05525      0.0023     4     2000
-0.002     0.12468     0.54630     1.03989      0.0022     3     2000
-0.032     -0.0248     0.58095     0.88924     -0.0001     2     2000
0.0285     0.01104     0.70553     1.24602     -0.0001     1     2000
0.1301     0.04747     0.73276     1.53207     -0.0025     4     1999
-0.027     -0.1303     0.74732     1.10596     -0.0018     3     1999
0.0197     -0.0155     0.77527     1.11365     -0.0003     2     1999
0.0506     0.05411     0.81441     1.17468     -0.0001     1     1999
0.1621     0.16835     0.82698     1.52850     -0.0013     4     1998
-0.077     -0.2254     0.90935     1.33349     -0.0019     3     1998
0.0255     0.00949     0.71068     1.12551     -0.0003     2     1998
0.1616     0.15019     0.81421     1.14996     -0.0006     1     1998
-0.001     0.03142     0.91399     1.11496      0.0005     4     1997
0.0535     0.08639     0.88248     1.10622      0.0004     3     1997
0.1174     0.08028     0.81751     1.23158     -0.001      2     1997
0.0435     0.07625     0.83011     1.37483      0.0003     1     1997
0.0984     0.15136     0.77470     1.36041      0.0003     4     1996
0.0318     0.10855     0.86728     1.10377      0.0011     3     1996
0.0173     -0.0125     0.83779     1.40889     -0.0006     2     1996
0.0613     0.09627     0.78498     1.11939      0.0005     1     1996
0.0553     0.04865     0.62770     1.22768     -0.0003     4     1995
0.0645     0.12961     0.49631     0.92225      0.0011     3     1995
0.0794     0.14789     0.67762     1.12278      0.0009     2     1995
0.0911     0.10919     0.76762     1.71786     -0.0008     1     1995
-0.006     -0.0715     0.72703     1.11738     -0.001      4     1994
0.0406     -0.0271     0.80706     1.00491     -0.0011     3     1994
-0.002     0.07169     0.75132     1.07790      0.0012     2     1994
-0.043     -0.0368     0.77869     1.18102      0.0002     1     1994
0.0089     -0.0698     0.47082     1.12801     -0.0013     4     1993
0.0269     0.05376     0.48552     0.84299      0.0005     3     1993

Gary Rogan writes:

The upcoming change in the political reality and some dangers to the biggest protectors of TBTF, the servicing/foreclosure controversy coupled with the possibility of a Countrywide mortgage putback made the group a lot more risky. Who is to say whether another balance sheet shock will be met by bailing out the bondholders again? TBTF may become redefined as just full protection of deposits vs. every stakeholder. There will certainly be less appetite for the latter after Nov. 2. Plus if on Nov. 3 QE2 is really modest and limited to Treasuries as opposed to the recent speculations of everything under the sun due the "shortage" of new issue treasuries, coupled with possible Fanny/Freddy uncertainty again due to the change in the political reality the naked truth staring in the face of MBS and plain old mortgage holders, and even CRE doesn't look too good. 

Phil McDonnell comments:

Thanks to Russ for a counting tour de force. I have a few questions which I shall pose as assumptions.

I assume:

1. S&P r is the daily serial correlation of S&P changes at lag 1.

2. BKX r is the daily serial correlation of daily serial BKX changes at lag 1

3. correl is the daily coincident correlation between S&P and BKX

4. Beta is the beta of a regression of BKX changes on S&P changes on a daily basis5. Alpha is the alpha for the same regression

Correct me where I am wrong.

Russ Sears writes:

S&P r is S&P return for the quarter on lognormal basis. likewise for BKX



I have been intrigued by recent discussions of ETFs by List members, in particular the UNG and UNL ETFs. Not long before this discussion, there was a discussion indicating that UNG got gamed every time that it needed to roll over the futures that provided the underlying asset for the ETF. Finally, there was a mention by Rocky that UNG had lost 78% of its value since inception while the nominal underlying asset had lost 37%.

Is the relatively greater loss in the value of the ETF a product of this gaming? If not, what alternative theories have been posed?

Other ETFs dealing in commodity futures where there are expenses associated with taking delivery would seem to also be subject to similar manipulation. Have the values of these ETFs experienced similar erosion? Isn't any such commodity ETF bound to erode away given enough time?

Finally, it seemed that today most ETFs were down significantly more than their underlying components. Did any news come out that would appear to be distinctly unfriendly to ETFs in general?

Gary Rogan writes:

This ubiquitous article explains enough about the storage costs and their effect on performance. I came across an additional explanation that the predictable patterns of buying and selling on certain days depress/inflate the prices enough in the wrong direction for the holder to matter as well.

Phil McDonnell comments:

I think it is useful to separate the concepts of 'gamed' and 'carry cost due to contango'. Having contango in the related futures market induces a roll cost every time the fund rolls forward into a new month. That would seem to be an unavoidable structural flaw in many of these funds that will eventually lead to their demise. But the gaming aspect is somewhat different. Specifically I mean that gaming is due to the actions of other market participants who front run the roll periods making it more expensive for the fund to perform its roll operations. That activity simply adds to the roll costs that already exist from contango. 

Michael Cohn asks:

Should I be thinking any differently about the deferred option contracts on these products such as VXX (Barclays Volatility Futures ETF or for that matter the UNG discussed here? How do I think about the changing nature of the basket with respect to these term options that are outside of the existing futures basket for the current composition of the ETF and at their own delivery subject to a new basket? I am convincing myself that I need to learn about basket options influenced by the passage of time.  

Rocky Humbert comments:

The VXX currently has some similar roll phenomenons — however, because it is not a physical commodity, it is not bounded by the same physical supply/demand characteristics of things like natgas, crude, wheat, etc. Rather, volatility is a second-order derivative with no physical delivery — and so the roll can swing wildly and remain in a positive carry condition for very extended periods of time. For example, during the 2008/2009 period, VXX experienced the exact opposite condition — and the rolls were very profitable (because short-term volatility was higher than long-term volatillity expectations).

I want to be clear on an important point: If a speculator is bullish on natgas and believes that prices will rise sharply (in a relatively short time frame), then the UNG is a perfectly reasonable vehicle to express this bet. Natgas periodically doubles and triples in a short period of time. However, if you want a long-term exposure to the nat gas market, then this is a horrible vehicle.

Similarly, having a longterm short of the VXX to pick up the rolls is somewhat analagous to selling far out of the money puts on the S&P. You'll make money most of the time. But you will also occasionally wake up and have a dismal mark-to-market and perhaps give back more than you've ever made. Some may argue that this risk can be managed — but that's as much art as science.



 One wonders if by considering the distances and weight of one market from another one would create a gravitational attraction possibly related to square of distance. Would this be even better way to explain recent market moves than twitter? So many markets are up that they pull stocks with it. Every day the crude and the gold and the grains and the metals exert their gravitational attraction on stocks and it's hard for stocks to go down when gravity of everything else is pulling them up?

Ken Drees comments:

Attraction theory may also pull monies from undervalued sectors-like nat gas for example– keeping these sectors starving for investment.

Anatoly Veltman writes:

My take is the former recent relationship has been more a product of U.S. dollar's daily devaluation. Thus the commodity part of it was only a further derivative.

Phil McDonnell writes:

Imagine we are on an island with only two things to trade stocks and gold. Naturally we use sea shells for money. At any given time there is only so much money M. So the total price of stock and gold is proportional to that. In fact we can visualize the possible prices as a circle with radius M and the X and Y axis are the prices of gold and stock respectively. The locus of possible points they can lie on is given by:

M^2 = G^2 + s^2

where I have changed the x and y to g for gold and s for stock.

Since M^2 is a constant at any given time we can just call it c and then we have.

s^2 = c - g^2

showing the relationship. This is all very pretty theory but does it stand up empirically?

The coincident correlation base on daily percent changes between gld and spy for the last 105 days was about 1%, so not much linear going on. but when we look at the relationship between spy^2 and gld^2 we get a 42% correlation consistent with the formula above. When we rewrite the formula for m and not m^2 we get:

m = ( g^2 + s^2 ) ^ .5

which is just the distance formula from high school.

Thought question: What happens when the Fed adds Q to M during QE 2?

Sushil Kedia writes:

The House Money effect works the same way. There is more valuable collateral, there is a larger amount of mental wealth, there is a larger appetite for risk. Akin to the rabbit coming out of an empty hat, money grows in the minds of the market players, when things are moving up.

As one large down move comes in a widely betted asset it gravitationally sucks away the value of the collateral utilized for playing other assets. Like the invisible forces of gravity the various contracts naturally move by in varying proportions broadly in similar directions, mostly together.

I would be inclined to recognize the effect of the varying amount of bets inside different pits and the varying spread of those bets across hands of differing strengths. With that in place any static relationships in assets or contracts is less than likely to be existent for any periods of prediction worthy time horizons. The ever changing cycles are likely originating from this varying nature of the spread of the bets. The vector sum total of all current and past and future bets may indeed by hypothesized as zero. Yet the similar sum at the present moment is not zero. Every changing tick hurts or rewards different sets of people simultaneously.

So, without so much as trying to invoke my limited numeracy skills before the mighty minds, I lay a case, that the pursuit of discovering constant relationships in the markets is the innate desire of men to find a constant while knowing fully well that the meal for a lifetime indeed is the knowledge of ever changing cycles.

Ralph Vince comments:

I lay a case, that the pursuit of discovering constant relationships in the markets is the innate desire of men to find a constant while knowing fully well that the meal for a lifetime indeed is the knowledge of ever changing cycles.

What could be more true than that statement?

We build models of the market– some, with ever-increasing complexity.

Take the stochastic differential equation for price changes in continuous time, where the second term is the Weiner process:

S0 = u S1 dt + dX

Involved math for many of us– but, as a model for how prices change, …it too is pathetically lacking. Our models are not reality, just little peepholes on it's behavior at times.

Sushil Kedia replies:

To add, one early school beginner's physics question:

If gravity works the same way on a feather as well as on a stone, then why does the stone drop sooner to the ground?

Well, the air that provides so much of rest to the feather that it takes longer to come down.

Likewise, the "air" inside the markets that is the varying size of bets of any individual participant as well as the varying size of the total bets present in a market bring by the gravitational pulls to still carry wide and varying variances.



Does anyone know whether the samples of data IB uses to display their charts and trades in order to keep up with fast markets is representative and proportionate on either side of market or where that info might be researched?

Phil McDonnell replies: 

My understanding from list member Chris Cooper is that IB skips trades to maintain real time numbers. The way to test for bias would be to get hold of some real tick data and compare for anomalies or bias.



It's generally accepted that large electric utility stocks are interest rate sensitive. They also have earnings growth based on a regulator-sanctioned "acceptable return on capital." The stocks are considered cheap when they are trading near book value (not now), and also when their yields are relatively high versus treasuries and bonds (yes now). There's some economic sensitivity to electric demand of course– but the stocks are still very low beta.

I posit that at their current relative prices, a basket of quality utility stocks should outperform TIPS… with similar risk and reward. The reason is not that utility stocks are particularly cheap, but rather because many TIPS have trivial and/or negative real yields. In a rising inflation environment, utilities should be able to get regulator approval to raise prices [to maintain their statutory ROE]– and in the current status quo environment, the stock yields will exceed the TIP yield.

At this moment, the 5yr Treasury has a 1.1% nominal yield, the 5 year TIP has a -0.50 real yield, and the UTY has a 4.34% nominal yield.

What am I missing here? Other than regulatory risks, in what environment will the UTY significantly underperform a 5-year TIP held to maturity?

Mr Krisrock comments:

In his book on theory, Ray Dalio of Bridgewater theorized that "stress testing" an investment theme by asking other unsuspecting traders their views, in effect is a surreptitious poll, as we note here in this textbook case of pedestrian "street begging".

Rocky Humbert responds:

Perhaps Mr. Krisrock will be so kind as to put a penny in this beggar's cup with an insight using all of his over-sized frontal lobe (and not just the amygdala).

I thank the speclisters who kindly pointed out (offlist):

1) During the 1930's depression, utility stocks held their dividends… And people who paid their bills saw higher rates to compensate for the people who did not pay their bills.

2) The TIPS will return par at maturity — there is no similar guarantee for utility stocks.

3) Because TIPS are currently trading at a premium to par, outright deflation can be injurious to their returns.

4) Utilities are taxed as corporations — and are also subject to the risks of cap&trade etc. However, the state rate-setting boards may/may-not compensate for the increased costs of cap&trade with rate hikes.

The daily and weekly statistical correlations between utes and tips are quite poor. But as the attached chart shows, they do seem to move in the same directions.Perhaps foolishly, I'm least worried about technological innovation– because the primary motivation for investing in a regulated utility is that they set rates based on a statutory ROE….

Jeff Watson writes:

Wireless electrical power transfer has been around since Leyden, Franklin, van de Graaf, and Tesla, just to name a few. Radio waves are a wireless electrical transmission system….just ask me, as a ham radio operator I have gotten many very nasty RF burns when my system wasn't properly grounded, or I stood directly in front of a beam antenna when someone keyed up the transmitter putting 2KW through the antenna. Further back was the study of charged amber by the ancient Greeks and the ability to turn static electrical potential into kinetic energy. The thermoelectric effect has reputedly been described since the middle ages. Now, the newest commercial application of wireless electrical transfer is with those new cellphone and iPod chargers where you just lay them on the pad and it magically charges the batteries with no electrical circuit. One might expect for more practical applications as time goes by and the market demands the convenience.  

Mr. Krisrock adds:

In India, for example, there are many rural areas without electricity or the likelihood of same. Some years ago we partnered with Reliance and built cell towers with solar panels that allowed locals to plug in their mobile phones into the cell towers to recharge them. Until we did this they had to send them back to the cell phone company to recharge them…clearly some pennies for the beggars cup…. 

Tyler Mclellan comments:

You're missing this. The future nominal rates are the sum of the short rates (at least to some point on the yield curve). If you finance the position at overnight money (which many marginal buyers do), you cannot lose money if the sum of the short rates is less than the yield. I repeat, no matter what happens to inflation etc…you cannot lose money so long as the short rates one finances at are less than the yield. Through one more iteration, TIPS work the same way.

So i suspect the answer to your question has to do with the nature of "return".

David Hillman adds:

Once we could not imagine a wheel nor a printing press nor telescopes nor electricity, nor steamships, nor the camera, nor the radio, nor the automobile, nor the incandescent light, nor telephones, nor submarines, nor television, nor computers, nor endoscopic surgery, nor nanotechnology.

The 4 ounce, 4.75"x2.5"x0.5" device clipped to my belt is a GPS, a voice recorder, an 8MP camera, a calendar, an alarm clock/stopwatch, a music/video/tv player, a language translator, a dictionary, an encyclopedia, a library, an internet browser, it allows remotely operating a computer half-way across the globe, it connects to gmail, to WiFi, it recognizes touch commands and voice commands, it will both convert the spoken word to text and vice versa, and oh, yes…'s a telephone, too. The cost of entry is $99 + $55/mo. Such a device was not imaginable as recently as 20 years ago.

A world without a power grid depends upon a collective will to have it, vision, investment, R&D, innovation, efficient production, practicality, affordability, and profitability.There are many individuals moving "off the grid" now, some adopting current [no pun intended] technology, wind, solar, water, other renewable, that allows same, others eschewing that technology in favor of more basic passive and mechanical means, horsepower and elbow grease.

But while basic technology exists, instead of pursuing advancement in earnest, we persist in taking the easy, short-sighted, petroleum-based way out, screwing ourselves in the process.Still, given the history of technological advancement, one might suggest somewhat optimistically that, someday, we will will it and the question is less "could there be?" than it is "when?" Until then, we'll just plod along from crisis to crisis as we humans are wont to do. Plus ca change….. 

Jeremy Smith comments:

You wrote, "It's generally accepted that large electric utility stocks are interest rate sensitive. They also have earnings growth bas…"

"Generally accepted" is statistically incorrect, at least since 1994, which is a long time. Correlation to bond prices is actually negative. Utility dividends also increase. They can estimate 3-4% increase for an index of these, more for the better companies. Of course the longer you hold a higer yielding stock with dividend growth, the more hopeless fixed income is by comparison, especially with regard to income generated. As income rises it forces higher the value of the instrument producing the income, all other things being equal.

Phil McDonnell comments:

I do not think that it is generally accepted that utilities are negatively correlated with bonds but that appears to be the case. I picked idu for utils, tlt for 20+ treasuries and shy 1 yr treasury. For last 105 days of daily net changes we have the following co-terminal correlations:

idu    tlt idu
tlt    -59
shy - 54 74

Perhaps the utility– interest rate connection is more complicated than upon first reflection. 1. They are heavy borrowers for their capital equipment financing so one would think they are hurt by higher rates. 2. Their are regulated, so when their regulators are convinced that rates have risen they will often give them rate relief which means higher rates are eventually mitigate. 3. The stocks sell in competition for investment dollars with other income producing assets such as bonds etc. So they must be priced to yield competitive returns. 

Steve Ellison writes:

Could it be that there is little interest rate sensitivity when rates are very low? Or that the correlation was arbed away when everybody knew about it? Last year, I noted a similar regime change in the correlation of stock prices and interest rates.

Tyler McLellan writes:

Look, stocks and bonds have been Correlated negatively in price terms since 1999/2000, I would bet that utilities have been correlated enough to the market as a whole that they've been at least partially along for the ride.

One reason to suspect this? Maybe if equity price are set my marginal preferences of equity investors if tech stock a goes down and that makes people want to sell some ute b to buy more, it might not matter that bonds are twenty bps lower, especially when the bond buyers don't care about either.

Rocky Humbert writes:

I played with the data a bit more, and it looks like the Tyler and Steve's observations account for most of the the regime change. The Ute's stock market beta/correlation dwarf their bond market beta/correlation (notwithstanding the low stock mkt beta of Utes.) Since stocks versus bonds have gone their separate ways over the past 12 years– the ute's regime change riddle is mostly solved.

There is one last data point worthy of mention: more than 65% of the UTE's total return is due to their dividends…and the attached chart graphically illustrates investor preference for utility dividends versus bond market dividends. This chart highlights the fact that the mean dividend yield for utes is 69% of the bond yield … and we are currently 3 sigma cheap…on a yield comparison basis. But that's true of many stocks…

My intuition remains that Ute's will probably outperform 5-year TIPS from these relative prices, but it appears that this intuition is a restatement of my bias that stocks overall should outperform bonds from these relative prices. If Ute's get whacked because of a hike in dividend tax rates, this may provide an attractive entry point for Ute's on their own absolute-return merits.

I'd like to thank everyone for contributing their thoughts (especially when they disagree with my thesis). It's a pleasure and privilege to interact with a group of such intelligent, independent-thinking people.

Jim Sogi comments:

Undistributed power using local generation, solar, wind, battery, water will be what undermines the monopoly just as cell phone undermined the phone land grid. 

Stefan Jovanovich replies:

I think it is an exaggeration to argue that the cell phone has "undermined" the phone land grid. The "land" grid is, in fact, the backbone that now connects all the cell towers; if wireless were truly able to handle the data rates, the towers would be off the grid. They are not; and the "wholesale" wireless technology– microwave– has been the greatest single casualty so far during this wireless revolution. 



 Exiting trades is always the toughest part of the game for me on a speculative basis, especially wanting to book trades to protect P and L, after taking a few hits. But what I find interesting is some trades are easier to let run than others with the same risk on the board. And it will come as no surprise to all that these are the low volatility plays… but what is it? Realistically the high volatility are the trader's saviors, and can turn a 3 bagger into a 8 bagger in a heartbeat. These are precisely the ones we should be putting on the risk and shutting down the screen. But hey the risk of scratching in a heartbeat is only too real as well, and there lies the trade off.

Alan Millhone writes:

The late Tom Wiswell said, "keep the draw in sight" at the Checker board. Knowing when to execute a trade at the board certainly carriers over to stock trading and knowing when to liquidate your position on the board or at the big board.

I spent this past week in Medina,Ohio as referee for a world title "Free Style" Checker match of 24 games between reigning Champion , Ron "Suki" King of Barbados and challenger Dr. Richard Beckwith of Ohio. I know a little about Checkers and watching these two Grandmasters all week was quite a treat.

Games one through twelve were all drawn and the players knew when to liquidate their position and make effective trades to exist the game. Suki "changed up" in game 13 and won as Dr. Beckwith stuck around too long and got into trouble by not having an effective exit strategy and lost.

I sat and witnessed game 22 as Dr. Beckwith improved on an ending that Suki and the late Derek Oldbury of England played off another opening that transposed into the line of play that was used in game 22. After 4 hours and 22 minutes Dr. Beckwith emerged as the victor after a hard fought ending that Suki could not escape. Dr. Beckwith had previously studied this ending that arose in game 22 and knew how to win the ending. Hand held notes as the Chair admonishes at the Checker board or the big board are critical to survive.

Suki drew game 22 and won the final game with an odd line of the "Tillcoultry" opening that Dr. Beckwith failed to meet correctly and did not trade out early enough and lost on a ending bind that he could not escape.

"Knowledge is power" on both boards. I was a first hand eye witness to this all last week watching these two greats do battle over the checkered squares.

As Chair points out, there are direct correlations to board games and stock trading and stock exit strategies that will help keep you unscathed.

Phil McDonnell writes:

One strategy I use with certain option spreads is something I call stop profit exit. I talked about it in my book. For strategies such as butterflies and calendar spreads the profit peaks out at a certain definable point relative to the underlying asset. For many ratio spreads there is a peak profit but that point changes dynamically with time. The point is that deciding to get out at the peak profit is a no brainer. Once it hits that point you will give money back if it goes up or down from there. The exit can and should be should be mechanical.

The probability of touching a price target is governed by our old favorite the arc sine distribution. Because of the Reflection Principle the probability of the target being touched is twice that of it being above (or below) that target at the end of a given time period.



The distribution of income is bounded on the low end by zero, but unbounded on the high end. This resembles the distribution of stock returns, and is better described by log-normal distribution.

Presumably humans evolved to anticipate something like normal distributions bounded by zero and bounded on the high end; height or weight for example. If heights were distributed like income, most of the time you would encounter normal-looking people, but occasional 20 footers. Of course tribes of average folk would to try hard to befriend the big guys.

Phil McDonnell writes:

I think there is a statistical quirk. Namely the quintiles are reconstructed every year with new individual members. Thus the 2009 top quintile contains different people than the 2010 top quintile. To understand how this creates a bias we need to look at how new people enter and leave the top quintile and what that process does to the 'average' of the quintile. To enter the top quintile the individual can only come from below. Thus he lowers the average of the quintile below and possibly raises the one above. No one can leave the top quintile by rising out of it. Thus there is an upward bias in the sense that they are retained no matter how high they go. On the other hand they are eliminated if they fall in income.

In the bottom quintile the reverse is true You cannot leave by going to zero, you are still in the bottom quintile. But if you make too much you will move up to the next quintile and thus reduce the average in the bottom quintile.

The middle three quintiles have less bias in this sense because individuals who leave can either go up or down to the next quintile resulting in more of a wash. In the same fashion new entrants to a given quintile can come either from above or below again resulting in more a a net wash effect.

The comparison of the top quintile to the bottom inevitably results in a biased and distorted comparison because of this effect. It would be better if they compared the second from the top and second from the bottom quintiles to reduce the bias. Reducing the bias is probably not the goal of those who calculate such statistics.

Rudy Hauser comments:

This is a different question that relates to what the statistics represent and will be used for. What Phil writes is certainly correct. What the quintiles show is the income distribution at any one point in time. It does not tell you anything about lifetime income or the ability to better one's self over time, that is upward mobility in the quintiles, or the fact that some of the well off become less so over time. For that you would need other measures. The movements between the groups will create the biases described. But to say that the bottom fifth only earn so much over time x and the top fifth earn so much need not have an upward bias to what these statistics actually measure as such movement happens all the time to varying degrees over time and by country. The top fifth are still the best off and the bottom fifth the worst off. Were they stand an any one time is what it is and that is all this statistical approach shows. There is no need to correct this bias but one does have to develop other measures to answer the sort of questions that seem to concern those who point to bias. There is no statistical reason why the growth rates have to favor the top group. That tendency to the extent it exists is due to political economic factors, cultural factors, social factors, etc.




Summiting mount kenyaI have been learning about ski mountaineering and climbing. One aspect of safety is setting anchors and belay points called protection. When starting up a steep pitch where falling and injury or death is possible in case of a mistake, the climber creates an anchor by tying a loop around a rock or putting pitons or nuts in a crack which will hold the rope tied to the climber to limit how far he can fall. As the climber climbs higher, the rope is shortened, and new protection is placed limiting the fall length. In case of a fall, there is some give in the system to avoid too hard a shock.

In climbing there are other "stops". One is the summit…goal reached, or back home. The other stop is time. If the climber has not reached the summit by enough time to return home by dark or before bad weather hits, its time to stop and turn around.

The trading applications are obvious, and in both cases it appears to be an art. Phil has stated that stops do not improve performance, but merely lower deviation of return. Senator has always advocated using stops. What is unclear to me is some scientific way to determine the optimum stop. Time stops seem common. Profit stops are too common. The difficult question is the use to trailing stops and the distance or adjustment and size. I've never seen a satisfactory analysis. Adjustment for volatility seems a must. Chair has advocated adjusting or limiting leverage, rather than stops as "protection".

Advice sought.

George Parkanyi writes:

This is very timely, because I just set three rows of stops in August trying to catch the down-leg (short) while keeping my risk low, and I got taken out of the meat of my position all three times– FOMC fake-out, sheared right before the 20-point drop, and sheared again this morning before the market settled down again. Arggh. Luckily still made a little something on the scraps, but basically managed to completely miss the move. (Please feel free to point and laugh.)

Sometimes taking a larger position (and risk) and commensurately narrowing your stops can pay off big, but there's something to be said for taking smaller positions and more forgiving stops (and a longer holding period to adjust reward to risk). While I was frantically trying to catch the equities just so, my relatively smaller short oil position (whose stop I had not touched) was plodding along building up nicely, looking over now and then going "What's YOUR problem?" Maybe you do a hybrid. I don't know.

So, what looks good on the long side then? Bargain-hunting in the long bonds perhaps?

Phil McDonnell comments:

There are many interesting themes in this discussion so I will address a few.

First a few basics assuming a random walk - if you use stops:

1. Your expectation will not change. You will neither make or lose more money assuming a random walk.

2. Your variance will be reduced (a good thing)

3. Your probability of having a loss as least as great as the stop will DOUBLE! Suppose the odds are about 16% that a stop loss set at 1 std deviation will be exceeded to the downside. If you use a stop loss at that price point, the probability it will be hit is 32%. The reason is the Reflection Principle of Statistics which essentially says that every path that reaches that point has an equal and opposite path that reflected back from that point. There are some graphs in my book Optimal Portfolio Modeling (Chapter 4) which illustrate this point.

4. If you use profit targets the preceding points are reversed.

5. On Friday I posted a 9 minute video with charts to which discusses my use of stop profits with respect to options. It is in the Options Profits section but people can get a free trial at the site.

In my opinion it is possible to optimize a stop loss or profit target provided you first specify an objective function that you want to optimize. My preference would be something that includes both risk and reward like a Sharpe Ratio. In one sense a stop loss and a stop profit are much alike. They both double the odds of winding up there. But a loss is more important in the sense of compounding your money. A 25% loss needs a 33% gain to break even. But this information is captured by taking the log as your weighting function. The trick is to take the log at the portfolio level and not the trade level.

Optimizing stops can easily be done in Excel using the solver. But I am not saying that such optimization will always be productive. Essentially it is a search for an anomaly just like a trading system. Just like a trading system it requires a significance test and sufficient data. Adding the stop parameters brings one that much closer to the slippery slope of data mining and curve fitting.

Nick White's interesting point about information is spot on. If you compare the formulas in my book to the formulas developed by Claude Shannon the father of Information Theory they are essentially identical. Yet mine were derived from first principles and compound interest math. As an aside the formulas in list member Ralph Vince's book are essentially the same math even though when you look at them Ralph does not use logs (mostly) so on the surface they appear different from the formulas Shannon and I wrote, but they are not.

To me this says that the market pays for information. That explains the beautiful symmetry between the formulas of Information Theory and portfolio optimization.



1st column: Date of first Hindenburg
Omen Signal

2cnd: # of Signals
In Cluster

3rd: DJIA
% Decline  

4th: Time Until

4/13/2004 (1)   5       5.4%    30 days
6/20/2002       5       15.8%   30 days
                              23.9%   112 days
6/20/2001       2       25.5%   93 days
3/12/2001       4       11.4%   11 days
9/15/2000       9       12.4%   33 days
7/26/2000       3       9.0%    83 days
1/24/2000       6       34.2%   44 days
6/15/1999       2       6.7%    122 days
12/22/1998 (2)  2       0.2%    1 day
7/21/1998 (3)   1       19.7%   41 days
12/11/1997      11      5.8%    32 days
6/12/1996       3       8.8%    34 days
10/09/1995      6       1.7%    1 day
9/19/1994       7       8.2%    65 days
1/25/1994       14      9.6%    69 days
11/03/1993      3       2.1%    2 days
12/02/1991      9       3.5%    7 days
6/27/1990       17      16.3%   91 days
11/01/1989      36      5.0%    91 days
10/11/1989      2       10.0%   5 days
9/14/1987       5       38.2%   36 days
7/14/1986       9       3.6%    21 days

Looking back at historical data, the probability of a move greater than 5% to the downside after a confirmed Hindenburg Omen was 77%, and usually takes place within the next forty-days.

The probability of a panic sellout was 41% and the probability of a major stock market crash was 24%.

Phil McDonnell comments: 

The HO signal is negated when the McClellan advance decline oscillator turns up. It turned up briefly, hence no signal. This is the case even though the MCO has now turned negative again.

The probability of making money when you sell at the high of a given move and buy at the low is 100%. Now would someone kindly tell me when those are going to occur?

Jonathan Bower writes:

I'd like to know when they would occur too!

Phil's assumption is based on the notion that 100% of the position is in place at the high. If one were to follow a strategy (not suggesting that one should for any number of reasons) that added to the position as the market fell (perhaps one was not 100% sure it was the high?) and cover some of the position if a big enough pull back occurred (oops, maybe I'm wrong about this move), then one could get chopped up with sufficient vigor such that covering the entire position on the low would not generate sufficient P/L to cover the losses that occurred from over trading. At least that's one way you could sell the high and buy the low of a move and not win….

Phil McDonnell responds: 

Perhaps I was a bit too indirect and subtle. The people who believe in the HO cite 'back testing' that is seriously flawed. Their back testing methodology requires perfect knowledge of the future. In order to duplicate the claimed results one would have to sell at the high and buy back at the low. And yes they are selling 100% at the high and 100% at the low but that is irrelevant to the broader issue of flawed analysis. This is very flawed because you have to know exactly when the high and low will occur (knowledge of the future).

Looking at results this way you need to ask yourself how often large drops occur at random. It turns out that they are a regular feature of markets. Then we ask the question whether these particular results were unlikely to be due to chance. Remember the distribution of highs in a random walk is controlled by the Arc Sine Distribution not the Gaussian. Same for the lows. The Arc Sine is a U shaped distribution which is ALL tails and not much in the middle. For a discussion of Arc Sine see Feller's An Intro to Probability Theory & Applications. Vol 1 deals with binomial random walks and Arc Sines and Vol 2 moves on to Normal random walks.



 I read an article "How Venice Rigged The First, and Worst, Global Financial Collapse" by Paul Gallagher. Whaddya think?

Bill Rafter summarizes:

Skimming the article one gets the opinion that the author blames most of the 14 Century economic failures on Venetian bankers rather than on the Black Death. 

Victor Niederhoffer writes:

We must hear from Stefan on this subject to get the truth, the whole truth and nothing but. 

Stefan Jovanovich commentates:

I am feeling damn near invincible this morning having had Susan's corn meal and flour drop bisquits for breakfast (also the 10-year old boy cat's favorites) so I am going to pretend that this opinion offers what Vic requested– "the truth, the whole truth and nothing but the truth". I have read Charles Lane's book , and I do know something about the period because my own faith comes closer to what is now called the Eastern Church than any other Christian sect; and I have always been curious about its fate. As Bill tactfully suggests, perhaps Black Death had something to do with the decline in European population that the essayist blames on those awful Italian bankers. The later Crusades and the mere Hundred Years war (which, together, had relative costs greater than WW II and the Cold War combined) may also have played a part. Blaming the bankers for the decline in food production that began around 1300 also seems more than a bit of a stretch. The farmers themselves thought that the end of the Medieval Warm Period was a more likely cause.

The author is right: there was a credit bubble. But like our most recent ones the bubble rose out of a dramatic reduction in the real prices for the things people lived by (computing for the tech bubble, household and home improvement goods from Asia for the consumer/real estate bubble). The rise of the Italian city-state bankers came from the dramatic declines in the costs of transportation and protein. (Archaeologists are finding that around 1100 Europe relatively suddenly went from eating freshwater fish to cod and other salt-water species.) These changes came from developments in naval technology and an outbreak of relative peace. The Italian bankers couldn't have been able to cheat poor King Edward if they hadn't had the means of getting themselves and their gold to London and back quickly without risk of having the Vikings waylay them.

The bubble continued and then broke because events moved against people and then as now, the bankers kept their mansions but most of them lost the better part of their fortunes.The essay assumes that there was ONE GIANT FINANCIAL VILLAIN without which the rise of benevolent national governments would have continued and everyone would have lived in peace and prosperity. This essayist blames the Venetians; others have blamed (who else?) the Jews. What is indisputable is that the bankers kept better books and minted more honest coin than the governments they lent to. How that allowed them to "control the Mongol Empire" and switch legal tender from gold to silver and back again remains unexplained. But, then, so does the modern notion that the Great Depression and the rise of the Nazis were mostly a function of the New York Fed's misadventures with the money supply.

The costs in blood and treasure of WW I, the influenza epidemic and the Tokyo fire and earthquake and the Mississippi Flood of 1927 were entirely incidental. What made people stretch so far for yield that they were willing to invest in match monopolies in the 1920s is the same cause that brought people to do serial refinances with the Bardi, Peruzzi and Venetian banks. Events had left most of them without the incomes they had come to expect so they borrowed and risked more and hoped to make it back when the weather changed and they won the next war.

Phil McDonnell adds:

I have to side with Bill Rafter on this. Arguably the Bubonic Plague may have begun in Europe when the Mongol Golden Horde laid siege to the nearby Genoan city of Kaffa in 1345. The siege was only broken when the Mongols were too badly stricken with the plague and forced to go home. Within a couple of years one third of Europe had died.

I think Plague and Mongols invaders would have a strong chilling effect on trade. Conversely, a banking panic cannot cause the Plague.

Steve Ellison comments: 

One of my pet peeves is the overuse of impenetrable equations in
peer-reviewed finance publications (and I think I'm pretty good at math;
I can still occasionally help my son with his calculus homework). To
cite a recent example, it would not seem to require calculus to explain
that spending on durable goods falls faster in a recession than other

Russ Sears replies:

Mr. Falkenstein's argument should be applied to all modeling, not just economic modeling. Even in a field with time tested product pricing models as actuarial science, I have found time after time that to truly add value, you must ask "where is the model blind spots?" People drove a convey of trucks through the MBS model's blind spot in pricing and ratings. And if left to their own devices FASB mark to market models would have driven all of us to a great depression. As I said at the time, (see A modest Proposal to the SEC)

They were blind to a liquid assets that can quickly turn illiquid and have huge liquidity premium on a mark to market model.Exploit the loopholes, and if nobody ask if this is simply a blind spot that you are exploiting, you will look great on paper like AIGFP… for awhile…until it become apparent that your resource allocation has a divide by zero error in it.

Modeling and regulatory modeling in particular, have replaced the central planner of the failed communist system.



 One disruptive technology that has changed everything in recent years is the search engine. It is a paradigm shift which enables even non-specialists to compete on an even playing field.

Let me give an example. I am a fairly specialized tech type who cannot even do basic repair on a car. I had a van some years ago that developed a squealing sound when the front wheels were turned far to the right or left. I took it into National Chain F for repair. They wanted $1200 to replace the entire front end. When I googled the symptoms there were several people who had experienced the problem and fixed it. In this case the solution was to use a needle tipped grease gun to lubricate the joint which was making the noise. I took it into my mechanic friend who did what I asked without even charging me because it was too easy.

Then there was the time my wife's laptop went black. After watching the video some nice guy posted on how to repair my brand's monitor backlight I tackled it successfully.

My point is that one can obtain a reasonable degree of working knowledge with respect to almost any problem encountered from a search engine. I am not afraid to try things I might have felt were out of my comfort zone before the Internet. The same thing holds true for broader policy discussions where a knowledge of facts is relevant but can easily be researched on the Web.



I have been re-reading Mandlebrot's book The Mis(behavior) of Markets.

Mandelbrot's notions regarding prices (and I have no reservation about saying this) do NOT pertain to us because we have a horizon, a finite period of time to trade in.

Secondly, and more importantly, price changes on the long side are bounded. I KNOW what the worst case can be — and this certain information I can use (overwhelmingly) to my advantage.

If Mandelbrot batted 1000 in his trading, I would listen to what his ideas were. Anything shy of that is silly for me (or anyone else) to listen to or consider.

Philip J. McDonnell comments:

Although I have never given the fractal gnome a chance to physically acost me I do have a peeve with him. His fractal theory has a certain beautiful appeal. However his fractal theory as he applies it to the markets has some serious flaws.

The most important flaw is the /*assumption* /of infinite variance in his form of the four parameter Levy distribution. Mandelbrot argues that because his form fits the cotton data reasonably well that proves the variance is infinite. However a four power rational polynomial fits the normal distribution reasonably well, However the analytical form of the normal is well known not to be a rational polynomial. Just because a form fits does not prove that it /*is*/ that form.

Assuming infinite variance obviates any attempt to do empirical significance testing because it would be meaningless. So you never see significance testing in a paper from the fractal school. They cannot do rigorous empirical testing and that is no way to do science. But it is a pretty theory.

The fractal gnome was F@m@'s Ph.D coach.

Ralph Vince writes:

Let's assume the worst — that Mandelbrot is correct and there IS infinite variance in the distribution of price returns (i.e. c1 / c0).

The Old Frenchman would say, "Who gives a rat's butt?" and he would be correct.

What we experience is a transformation of the distribution of the returns of prices by our trading rules — in other words, we take a pair of scissors to this paper distribution, paring off parts of it as we see fit.

Does a binomial option have infinite variance? Come on!



My sister Adrienne McDonnell has written a novel called The Doctor and the Diva which will be released in the next few weeks (July 22). She teaches Creative Writing at UC Berkeley and knows her craft. Surprisingly this is her first published novel. Apparently someone believes in her novel as it garnered a significant advance - roughly 100 times my book.

The following review was passed on to me and I will pass it on verbatim. Feel free to pass this on to your friends.

This review was written for "LibraryThing Early Reviewers, ( a literary book group!). The unidentified member confided:

"I was lucky enough to receive "The Doctor and The Diva" via the "Early Reviewers" program. It's an extraordinary book! If I could give it more than 5 stars, I would. It's THAT good. Stunning to realize it's a debut novel, which, sadly, means there won't be another new novel from Adrienne McDonnell for a while.

"Back to D&D, though (as I've affectionately started to call it): While taking place in 1905-1914, its storyline is one that could easily revolve around women today thinking about, or actually balancing, careers with motherhood …and Erika's struggles to decide her future at each crossroads in her life certainly rang true and authentic to me (being a similar age, in a similar situation, with similar thoughts and feelings). This is a serious, mature read for mature adults, no doubt about it.

"Yet, it is not a cliche novel in any way - in fact, McDonnell has penned a novel that is rich in settings, characters, and stories that guarantee its uniqueness, perhaps therefore allowing the normal human-ness of the characters to shine through. Each character, however minor (especially Quentin - wow, that kid is a gem!!), comes alive in his or her own time (immediately prior to WW1) and place (Boston, Trinidad, Florence - this is one atmospherically lush read!!!). The character and story development never feels rushed or short-changed. I never got the feeling that there was a story or piece being missed, either - one that would have made this book any better. It was just perfect the way it was. Heart wrenching on so many levels, heartwarming on others, and the novel goes back and forth between these emotions effortlessly.

"In the end, the story feels, for lack of a better word, solid -extraordinarily solid - in its construction. The characters of Ravell, Erika, and Peter are written with such depth and perspective that I could really understand why they made the decisions they did (especially Ravell's decisions while Erika was his major one, in particular) and not judge them, but just be interested in them, and fascinated/awed by them. It's ultimately a story about fallible human beings trying to be true to themselves, and as fair as they can to those around them.

"Loved loved loved the ending!! (though it came way too soon - this novel is 432 pages (verrrry sumptuous to hold!), I read it in 2 sittings - couldn't put it down!)

"One quip - the title of this novel does not do this novel's about so much more than the doctor and the diva."  | May 14, 2010 |



 As a first-time homebuyer a few years back, I am now working on becoming a first time homeseller. I was told by our realtrix that she recently had a closing that was held up by a house that failed to appraise at the selling price. Since she specializes in old houses (and ours is pushing 95) she told us that it was unlikely but possible that a sale of our house could be held up for the same reason, depending on how much we were able to get for it.

I nodded my head at the time, but thinking on it later in the day, I was more and more baffled the more I considered it. In the financial markets, if you value infrequently traded securities, then you know that the absolute holy grail of a security's valuation is an arms length trade, in size, viewable on the "tape" (stock exchange, TRACE, MSRB, etc.). Even if you have no trade, an appropriately sized offering on the security sets a ceiling on the price, while a live, executable bid sets a floor price beneath which there's no justification to value the piece. The terminology varies from sector to sector, but fair valuing, marking to model, etc., should be avoided whenever possible.

I guess people for a while have been saying the appraisal system for houses was a contributor to the housing crisis, but most claim it was improperly performed appraisals which led to the problem. To me, the whole structure of the system is wrong. Right now, it works like this: customer pulls a price less than selling price out of the air, and probably after some negotiations, a price is settled upon by the buyer and seller. At this point, it is probably a written, binding offer, contingent upon inspection and appraisal at or above selling price . THEN, an appraiser is brought in to determine "market value." But the market price has already been set! If the appraiser can't take the live, accepted bid on the very property in question as the house's value, then what can he possibly go on?

The answer, incredibly, is that the appraiser is marking to market. He is marking to a model, based on comps, accouterments, neighborhood, lot size, rebuild cost, etc., but it is undeniably a model. If the system made any sense, it wouldn't go offer -> negotiate -> agree -> appraise -> close. The appraisal would be conducted prior to the offer and negotiation as a bidding tool to the buyer… or even as justification by the seller for the offering price. As it is, the appraisal serves two purposes. One, it gives the buyer a false sense of security that he paid the right price, and it gives the bank a false sense of security that sufficient equity will be coupled with the down payment to motivate the mortgagor to perform, and/or that a sale under duress could make the bank sufficiently whole to take the loan risk. I know that theoretically appraisers don't try to "hit the number" but it seems like the knobs on the appraisal are probably turned a little bit at least to get in the right ballpark. I know that it's supposedly a science and they are professionals, etc., but still…

The structural problem, of course, is that the buyer and the lender are trusting an appraiser's mark-to-model to protect their long-term interests. It allows lenders to be more impersonal and buyers the sense they are delegating responsibility. To me, it's yet another example of unintended consequences of regulation: a process that was intended well but ultimately creates an environment where a buyer's biggest purchase in a lifetime and the financier facilitating the trade are entrusting huge sums of money to the model and signature of an interested (but probably not interested enough) third party. A signature counts more today than it ever, in a time when it probably means less than ever.

But I sure hope my house appraises right when I accept an offer!

Jim Sogi comments:

The appraisers' methods have been well tested in the courts, and recently not so well in the markets. There are 3 ways to value property:

1. Comparable Sales

2. Income

3. Replacement Cost.

Marginal price in liquid markets are set by comparable sales of that security. But we know that they can be wrong also. Comparing the appraisal methods to see if there is undue variance give some back up to each method. If one or more are way off, perhaps something is not right. Chair's Fed Model looks at the income for stocks. Replacement cost is rarely used and does not account for things like location or in the stock market, goodwill. Over reliance on comparable sales, which are set at the margin, resulted in the boom and crash of real estate and derivatives of the mortgages.There is quite a bit of play in the range of price that an appraiser can defend, and it plays out regularly in court with the IRS in estate tax cases so the method has been well tested.
They key is getting a good appraiser.

Sam Humbert explains:

The prospective buyer of your home isn’t the young couple with the cute kids and Labrador retriever you’ve been “negotiating” with. It’s their bank. The bank takes all the risk, aside from the small haircut the down payment represents. And appraisals are how banks roll. If you don’t like it, sell to an all-cash buyer instead, so there’s no bank in the picture.

Jonathan Bower writes:

Appraisers are part of the vig in a real estate transaction. As recent first time homesellers (about a year ago) who "scratched" the house, we discovered the long line of people with their hands out to help facilitate my transaction…

City (Sales and Stamp Tax)

County (Sales and Stamp Tax)


2 Brokers (on the market less than 2 weeks…)






Municipal Service Fee

Document Preparation Fee

Closing Fee

Wire Fee

Overnight Fee et al

This is when I realized why the gov't is so interested in stimulating the housing market…

Ken Drees writes:

In general, during the housing boom there was no restraint on the appraisal part of the transaction. The appraisal price was matched to or above the agreed upon sale price in order for the loan to go through. The appraisal person often asked the real estate agent what number they needed. Once again, this is not true in all cases–but obviously lax rules and lax ethics swirled around this function during the boom. Now there is a lot of heat and scrutiny on the appraisal part of the process. These people can and will be held liable and responsible for any questionable values. So naturally they are over reacting and sharpening their pencils to the point of overkill on the low end of ranges. It really is a buyers market–and only now the appraisal needs to be at or below the selling price for the loan to go through.

No wonder that money supply is high at the base level and crashing in terms of reaching the people. Where is the lending?

Rocky Humbert comments:

If a lender isn't involved, there's no need for an appraiser, and there's no bank closing fees. If one has engineering expertise, an inspector is optional. A knowledgeable buyer can also conduct his own title search from public records and (bravely) skip the Title insurance, and can also (in most states) represent themselves "Pro Se," and not retain an attorney. You can also buy and sell without a broker. All of these people are providing risk-reduction or other services for the parties.

The real "vig" in a real estate transaction is not only the stamp tax and bid/ask spread, but also new drapes for all of the windows, and the discovery that there's no way to fit your 9-foot Steinway Concert Grand Piano through the front door.

Real estate markets have one unique peculiarity: In what other market is the seller's identity and cost-basis a matter of public legal record, but the buyer can remain anonymous prior to the closing?

Phil McDonnell adds:

In a market with fungible items the fair market value is the gold standard. The reason is that the previous transaction is a good measure of value given that all items traded are identical. But in Real Estate every property is unique. Even in cookie cutter developments the locations are unique.

Real Estate also differs in financing because the margins are only about 10% or so. Your broker can and will sell you out if your stock falls in value below maintenance margin even momentarily. The bank cannot do that to a homeowner. In effect a mortgage is a loan and a put option. This is because the homeowner can put the house back to the bank if it falls underwater via a foreclosure or short sale.

In California during the boom an immigrant gardener was able to buy something like 10 houses from his friend for inflated prices because of lax mortgage appraisal standards. In scams like that the friend walks away with fast cash from the overpayment. Appraisals are really designed to weed out the risk of less than arms length transactions for the banks.

Stefan Jovanovich writes:

Around here (Contra Costa, Alameda Counties) in California the appraisers were usually in on the deal and their justification for the absurd valuations was the "fair market value" of the lots on which the houses were built. The primary fallacy was– and is– the idea that the dirt itself could be adequate security for the loan. That has been a recurring delusion throughout American history– that land alone could support debt. In the bad old days when money was itself the gold standard, bankers refused to lend against land; they limited their risk to the earnings power of the improvements - i.e. the buildings or the prepared soil. Rents and reliable crop yields were seen as the only reasonable estimate for comparable value; and, since those were expressed in dollars, properties were not considered unique. That was, of course, one of the limits of the gold standard that the newer, more flexible currency was going to solve. And it did in one sense; imagine what dirt prices would be without FHLBs, FNM, FRE and the AAA of 1938.

Rock Humbert replies:

Maslow's hierarchy of needsOuch. Maslow's Hammer just came down on my head, as Stefan once again suggests that society's ills would be cured by the gold standard.There is an important difference between saying "appraisers were usually in on the deal" (which suggests fraudulent intent), and saying the justification was "fair market value.""Fair Market Value" (FMV) is a defined term: the "price" where a willing buyer and a willing seller complete a transaction. This concept is applicable to all assets (including land, copper, gold, horses, equities, etc.), and the price can be stated in any agreed medium of exchange (dollars, gold, salt, seashells). Although it wasn't called FMV, the FMV concept dates back to at least King Solomon and the Talmud.

If a third party (e.g. a bank) provides capital for an asset purchase/investment (debt, equity or barter), and the third party is falsely induced to provide capital, this is fraud. And the existence of fraud also pre-dates modern history. Hardly an argument for the gold standard.

If the third party provides capital based on assumptions (including FMV) regarding the asset purchase that turn out to be wrong, this can be called a bad business decision. And bad business decisions are not a recent development either. Again, hardly an argument for the gold standard.

However, if the bank makes an investment because it plans to flip the loan to Fannie & Freddie– that's a completely different story. And much of the recent mess can be attributed to this phenomenon.(Yet I don't understand why a gold standard and the existence of a gold-rich Fannie & Freddie are necessarily mutually exclusive.

Perhaps Stefan will explain…. 

Stefan Jovanovich explains:

No Fannie or Freddie could possibly be or want to be "gold-rich"; if you can exchange your paper with the central bank why would you want to endure the vicious discounts that 19th century merchants imposed because they insisted on valuing their inventory by what it would sell for in cash, not what it could be appraised for or securitized into? No one here has disagreed that the state has a monopoly of legal tender. What the medium of exchange folks have said is that the government monopoly (and the potential for abuse inherent in any legal monopoly) does not matter because you can always trade your horses, copper, land for money whenever you want and the government's self-regulation will prevent abuse. Or, as Rocky put it, the tax man will take property instead of cash in payment of taxes. Alas that part is simply not true: the tax liability remains even after the taxpayer's property is seized; it is only discharged when and if the property is sold. (One of the interesting interactions of the present tyranny is how the drug laws have revived debtors prison.) Perfect liquidity, like FMV, is a notion that works better on paper than it ever does on the barrel head where - even now - legal tender (Fed reserve balances and notes) remains in limited supply. Because legal tender is in limited supply, there is the unavoidable temptation for the holders of the government to make more money available whenever Congress and the President want a war - whether against poverty or Iraq. That was what the Founders properly feared. They wanted the unavoidable monopolies of our central government - the powers to make Money and War - to be constrained by the requirement that both be approved by an actual vote of the Congress. Since they knew that no unpopular war could be waged without a debasement of the currency, they imposed the further restraint of insisting in our Constitution that the Money be Coined to a Standard Weight and Measure. Credit would regulate itself, even in a world of mark to model and foreign military/aid adventures, as long as the government monopoly could not create legal tender as needed. Money exchangeable on demand into specie was the ballast for republic itself; it might seem useless to waste all that precious cargo space carrying heavy weights that were only hoarded– until you found yourself caught in a storm– and then the ballast would be the only thing that would give the ship of state's righting arms the weight with which to do their work.

David Hillman writes:

Speaking of real estate, more particularly of having the ranch foreclosed upon, TCM [Turner Classic Movies] will air this evening at 10 EDT/9 CDT, a chair and list favorite, the original 1970 version of the classic 'demise of the old west' tale, "Monte Walsh" starring Lee Marvin. Thought some might like a heads up. Enjoy. 

Stefan Jovanovich adds:

And now for a brief jab at Maslow: anyone who would compare being the lonely Jew in a New York school full of gentiles in 1920 to being "the first Negro enrolled in an all-white children" had a sense of self-importance that would have made even our country's original hammer head (aka George Washington) blush. Talk about a hierarchy of needs!

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