Here's something I'm trying hard to understand. Should the US bail out their carmakers, how is that likely to make them profitable going forward or are they going to require ever more taxpayer funding? It seems to me the latter is more likely to be true, especially if they are to be burdened with tough regulation.

It is said that much of problems in the 30s stemmed from the tariff wars, and some blame WW II in part from these tensions. But the political tensions were too ripe to not exploit for political gain that lead down this dangerous path.

While not as obvious global aggression, funding ones own country's industry is a tariff by a PC correct name. In the end, its not about having a "profit" off the loan, its about funding them by giving them a break over market rates. Again a slide of the hand, making the subsidy a loan at a "cost" to them and politically acceptable.

Stefan Jovanovich writes:

The United States in 1873 was in the same position that China is today. It was the fastest growing economy in the world. It was still significantly smaller than the combined economies of Europe, but it was rapidly catching up. U.S. goods — corn, flour, wheat, agricultural and industrial machinery, shoes –were cheaper and were being produced in ever increasing volumes. However, the United States was a capital importer, not exporter. Even as its exports grew, the demand for savings grew even faster. (Then, as now, Americans were inclined to spend before they saved.) The post-Civil War boom in railroad construction and railroad bonds and shares was like the tech bubble and real estate bubble combined. When the bubble burst, with the spectacular failure of Jay Cooke & Company, the consensus was that the Treasury would have to come to the rescue. President Grant took the train to New York and sat down over a weekend with Vanderbilt and Morgan. What came out of the meeting was not TARP one but the first iteration of Bagehot's "lend freely but at a premium". The New York banks formed a clearing house and accepted bank assets as pledges for clearing house certificates that could be used to discharge interbank obligations. Within 3 months the financial panic was over. That did not save the country from a slump, but Grant's subsequent actions did. In 1874 he vetoed the greenback bill even though "everyone" agreed that the United States had to issue more fiat currency to "solve the crisis". In 1875 the U.S. put its national currency back on the gold standard. Within 6 months the dollar was trading at par with specie on international markets; by 1876 the public was no longer worried about the economy but titillating itself with the fright that the Sioux might invade Chicago now that they had disposed of the 7th cavalry.

Where China seems to be fundamentally different from the U.S. in the 19th century is in labor's share of the national income. Immigrants flocked the United States in the late 19th century because wage rates were so much better than they were in Europe. For China wages and domestic private lending have not kept pace with growth. That has left them in the enviable position of having an U.S. dollar and euro reserve, but it has also left them in the dangerous position of being unable - so far - to rely on a revival of economic activity from increased domestic consumption. Instead, they seem to be going down the path that Russ describes: hinting at a depreciation of their own currency, paying export subsidies, restricting imports. That is a very different policy from the one the U.S. followed in the 1870s. The United States did have a tariff, but there were no restrictions on quantities and no protectionist inspections. Throughout the rest of the 19th century British and German steel exports to America rose even as the U.S. become the world's steel producer and the resumption of the gold standard increased the exchange value of the dollar.

One wishes the Chinese would follow the American example of a century and a half ago and the Americans would not adopt the European state capitalist solutions that came out of the collapse of their property and financial markets during that same period.

Somehow, I don't think either economic pony is going to end up under the Christmas tree this year or next.



 Reading the remarks of some economists today, I wonder whatever happened to professional reserve. Is is really useful to have melodrama such as this:

"You can't get much uglier than this. The economy has just collapsed, and has gone into a free fall," said Richard Yamarone, chief economist at Argus Research in New York.

"It's just a disaster," said Stephen Stanley, chief U.S. economist at RBS Greenwich in Greenwich, Conn.

As an Englishman, I'd like to point out the correct response is to tinge one's objectivity with understatement. Thus if one's leg gets taken off by shrapnel one should complain that 'it stings a bit' before estimating the time required to be fully mobile using the remaining one. That way we avoid spreading unnecessary panic.

They should pull themselves together.




In recent months the market has become more volatile. This volatility has led to further evolution in the traditional option to underlying linkage. In many cases we are seeing the option move the opposite to its traditional correlation with the underlying.

For example, the calls on the Russell 2000 index ETF (IWM) sometimes drop when the underlying goes up. Even on days when IWM is up more than 2% the calls will often drop. The reason for this paradoxical behavior is the simultaneous radical change in expected volatility. When the market goes up the VIX will usually fall. The correlation is a powerful -83%. When VIX falls options become less valuable. Specifically we are seeing the VIX effect completely overwhelming the effect of delta.

To trade this successfully one needs both a directional model and an ability to predict volatility. The ability to merely predict direction is no longer sufficient.

Dr. McDonnell is the author of Optimal Portfolio Modeling, Wiley, 2008

Greg Calvin writes:

We have also seen call options hold their value on days the market/underlying is headed down fast. A misplaced sense of comfort may arise in these situations. One needs confidence that the underlying will rebound in the future planned trading time frame, as the IV settles back down and time decay marches on. I have found option spread trading to be one way to [sometimes more than] offset losses on long calls or puts due to IV drops. The sold calls or puts will also drop in value when IV declines. In addition to vertical spreads, calendar spreads can provide opportunities when front month options have significantly higher IV. Volatility tends to increase not only when underlyings decline, but also as announcement events approach. Lagging into spreads as volatility increases is particularly attractive, as the higher IV premium tab gets picked up by someone besides you.

Diego Joachin remarks:

I think options' behavior is the underlyings' subconscious. It reveals the fear of players. That's why studying volatility is more important now.



 Many years ago I wanted to date a friend of mine. When I called her, sometimes she was nice and would talk. This gave me hope. The same hope you have when markets rebound after a sell off for a few sessions even with light volume. Sometimes she would tell me: "Call me back in five minutes. I am doing something very important." When I called back after five minutes, she would not pick up the phone. Or if she finally did, she would say: "Sorry. I am leaving now. Can you call me this evening?" When I called her later, I wouldn't simply find her at home, she would be busy brushing her teeth or shampooing her hair. Eventually I didn't succeed in my efforts and I gave up. Low after low, rebound after rebound, you refuse to accept that you are in a bear market. You keep on insisting as stubborn as ever. And your losses mount. You refuse to see signals that are very clear to those not emotionally involved in the situation. And you average your positions as prices go down, with horrible outcomes. As if, in the case of my girlfriend's story, hope resulted in a mortal disease.

At the same time, I like to remember the epic fight between Rocky Balboa and Lang. Rocky was feeling the pain of his opponent's tough punches. Lang said: "I'm gonna torture him. I'm gonna crucify him. Real bad." Rocky replied: "You ain't so bad, you ain't so bad, you ain't nothin'. C'mon, champ, hit me in the face! My mom hits harder than you!". Lang expended his energy trying to knock Rocky out. Rocky eventually retaliated and knocked the confused Lang out with an impressive counter-attack. The 9% plunge few days ago hurt me much less than the downtrend did back in October. Eventually you get used to these plunges. You get prepared to expect very negative events. Hopefully bears will get exhausted like Lang did and we will eventually see higher prices and a trend reversal. The selling pressure at a certain point will ease and the bulls will prevail with a fast and sudden counter trend as Rocky came back and surprised his opponent.

Kim Zussman comments:

It's hard to imagine that most traders can discern random from non-random, not to mention that even scientists have trouble with the subtleties (pertinent variables, sample size, learning set selection, multiple hypotheses, causation vs. association, etc.).

Another way to assess this is whether statistically astute traders do better (under all market conditions) than innumerates.

Dan Grossman remarks:

Regarding the girlfriend story, it is a principle of behavioral psychology, and gambling, that random reinforcement is highly addictive. 

Victor Niederhoffer replies:

One should carefully consider whether there is any evidence that random reinforcement is better than systematic reinforcement or punishment in inducing behavior. The evidence is very mixed and inconclusive last time I studied it.

Gibbons Burke writes:

The wikipedia article on Operant Conditioning in a sub-article titled Reinforcement provides a decent trailhead to further references, as well as criticisms:

Effects of different types of simple schedules

• Ratio schedules produce higher rates of responding than interval schedules, when the rates of reinforcement are otherwise similar.

• Variable schedules produce higher rates and greater resistance to extinction than most fixed schedules. This is also known as the Partial Reinforcement Extinction Effect (PREE)

• The variable ratio schedule produces both the highest rate of responding and the greatest resistance to extinction (an example would be the behavior of gamblers at slot machines)

• Fixed schedules produce 'post-reinforcement pauses' (PRP), where responses will briefly cease immediately following reinforcement, though the pause is a function of the upcoming response requirement rather than the prior reinforcement. • The PRP of a fixed interval schedule is frequently followed by an accelerating rate of response which is "scallop shaped," while those of fixed ratio schedules are more angular.

• Organisms whose schedules of reinforcement are 'thinned' (that is, requiring more responses or a greater wait before reinforcement) may experience 'ratio strain' if thinned too quickly. This produces behavior similar to that seen during extinction.

• Partial reinforcement schedules are more resistant to extinction than continuous reinforcement schedules. • Ratio schedules are more resistant than interval schedules and variable schedules more resistant than fixed ones.



 I think one of the challenges in speculation is in deciding what data set to use, i.e  what part of the data do you include and exclude, whether it be by filtering for days that share similar characteristics, or by selecting a date range based on a known structural break. How do you decide what portion of history is relevant? And is it valid to use history to decide what portion of history is relevant? Jeff Watson's question is interesting: "what if you were paid to do the exact opposite of what history told you?" Historically, would this have been profitable? In a way, it would be a paradox if it had been. My feeling is that there may be some high-hanging fruit that exists as a premium for trading on smaller sample of data - i.e. lower statistical significance - but with correspondingly greater risk. At the limit, there is what Aaron Brown in his book The Poker Face of Wall Street called "unquantifiable risk". What is the difference between "unquantifiable risk" and mere hunch? Do unquantifiable risk situations exist? Are they truly unquantifiable? And if so, where does the edge come from?

Nick White writes:

I think the real issue is determining the best method of adaptation to new circumstances. How does one free oneself from Pavlovian responses to old market relationships? How can we have courage to believe the data when it changes?

Every speculator's current predicament is to find a path through a new and unfamiliar environment; an environment where it seems that a great deal of what we have learned about markets — from the textbooks as well as from our own experiences — are, at least for the time being, essentially worthless.

Some of the most basic market microstructure foundations — things we take for granted every day in pricing and trading — have come under attack. Even the market-wide reliance on arbitrageurs to keep things reasonably orderly required the a priori assumption that there would always be the odd dollar or two of capital around to eliminate the anomaly… so much for that.

The ever-changing cycles have well and truly thrown us a curve-ball. More than ever, current market conditions - full of unprecedented anomalies and broken relationships as they are - require fresh thinking and an unrelenting dedication to pushing through proximate causes to find the ultimate ones.

So, as it relates to choice of data, the very fact that the market is a different beast post-September to its pre-September form means we have to be more wise in our data choice and analysis. The most stable relationships, instruments and markets have undergone seismic shifts in daily ranges and changes — the correlation shifts alone have been a wonder to observe. Yes, we have a very limited data set of ~70 observations — but, in this new environment, perhaps it is more risky NOT to use that new data set? Imagine you were out sailing on a sunny day — and, all of a sudden, conditions rapidly deteriorated from blue skies to hurricanes and enormous swells — would you continue to sail as though the conditions were still blue skies and a gentle breeze? Our heuristics have to match the conditions, not the other way around.

Having made that concession, so much now seems to be driven by market-exogenous factors. In that case, perhaps the best and most reliable data set of all — studies of human behaviors under stress and uncertainty — can supplement the lack of more numerous traditional observations. In other words, it seems like a good time to apply the appropriately-filtered qualitative data alongside the quantitative.

So much of this website is dedicated to the lessons we can learn from other fields. A recurrent theme is biology and evolution; surely now is the time for the greatest flexibility in strategy and tactics so that we can be amongst the quickest to successfully adapt to the new environment.

I'm sure there would be a great range of evolutionary examples that the more biology-savvy Specs could provide for inspiration…



 Yo yos were popular at various times when I was a kid. The basic yo yo movement was up and down the length of the string. As the speed built up, one could make the yo yo sleep by spinning a while at the bottom of the string as the yo yo spun. If it didn't sleep long, the yo yo would come back up pretty fast. If it slept too long, sometimes it used up the spin and would not come all the way back up. If you really did it hard, and the string was old, it would break and drop to the ground.

Recent market action reminds me of kid days yo yo ing. The market yo yos up and down the length of the string. It bounces up fast, some times spinning a bit on the bottoms. The length of the string is about equal. Its better than a couple of weeks ago when the string kept breaking. Like the yo yo fads of old, soon the fad wore out and was gone. Probably same with the market.



 With the market down some 35% this year, the question of the performance of companies that have been beaten down hard becomes very relevant. On the one hand is the conventional wisdom that those that are down will be sold hard in the remainder of the year to realize losses before the end of the service year. On the other hand is the well known effect for companies that are beaten down hard to rally during the first month of the year, in conjunction with a bounceback that in some years has been as much as 50% in the first month. There are so many variables involved in such a study that it is hard to do anything scientific. As a start, I looked at the NASDAQ 100 companies as of November 2007. They were down an average of 5% that year. I compared the performance in the next month of the 10 best performing companies to the 10 worst performing companies as follows:

Performance of 10 best and 10 worst in December 2007

10 best                                 10 worst

company dec 07 perf        company dec 07 perf

Top 10 / Bottom 10

mean 0.5                               mean  -1

The change in NASDAQ 100 for December 07 was -1%. There was thus, no significant difference between the performance of these companies in 2007 although there is some small evidence that except for LEAP, which was the worst in the first 11 months but the best in the last, that the 10 worst performed worse than the 10 best. There was survivor bias in this study since I worked with the performance of the current NASDAQ 100. Other studies one would want to see would be the performance of companies as a function of their goodwill to market value ratios. One would hypothesize that retrospectively those companies with high goodwill to market value ratios would have performed significantly worse than the average during the past several years as goodwill is prone to be valueless in a declining market. Also, with the performance of IPOs in the current environment one would hypothesize that their subsequent performance would be well above average. More studies of this nature are in order.

Michael Pomada writes:

Mr / Mrs DudeA quick & dirty study on the top and bottom 20 turkeys/non-turkeys in the sp500 from 1992-present. This is based on the sp500 membership list as of the beginning of each year, so it disregards changes intrayear, but is adjusted annually. Also, I only include stocks with px>$5, mktcap>$100MM & avg volume >100k shs/day as of November 30. I rank the stocks that meet these criteria on the last trading day of November and here I report the average return of those 20 stocks YTD, then Nov30 to Dec31, then Dec31 to approx Jan15.

So, bottom line,  the 20 stocks that have performed worst YTD shed on avg another -19bps while the best add 2.81% until the end of the year. This is then reversed during the first couple of weeks of Jan with the worst adding +2.59% and the best only adding +40bps.

WORST20 TURKEYS    AVG     SD   CNT        WINpct   Zscr        Zdrft
RETjan-nov30           -43.54   16.66    16            0.00%  -10.45

RETnov30-dec31        -0.19     5.65    16            56.25%  -0.14     -1.00

RETdec31-jan15          2.59     11.38   16           62.50%    0.91      0.89

BEST20 TURKEYS       AVG    SD      CNT         WINpct  Zscr        Zdrft
RETjan-nov30           99.21   38.06     16          100.00%   10.43

RETnov30-dec 31      2.81       5.50     16           68.75%     2.04       1.15

RETdec31-jan15        0.40       5.77     16           56.25%     0.27       0.24

S&P                              AVG    SD       CNT          WINpct   Zscr
SPRETnov30-dec31    1.22     2.95       16            75.00%    1.66

SPRETdec31-jan15     0.05     2.70       16            56.25%    0.08

The 20 worst turkeys on the menu this year: ticker and retYTD:

20 Worst

It must be noted that the "best turkeys" list will always be skewed by pending acquisitions — particularly in a year such as 2008 when most stocks are down YTD. One would need to exclude these stocks. Also, inevitably the resulting portfolios will be heavily exposed to particularly industries (like financials, oil & construction stocks this year) which changes the risk profile of the portfolio such that the S&P is not an accurate comparison for the drift.



On November 21 we published a table from the Avunc in a way that made it difficult to adduce the point being made. After comment from aforesaid I have redone the table in a way that should be more self explanatory.  Sorry and I hope to still be invited to the party.



 Turkey prices are very seasonal. With the prices decreasing when the appetite increases for them right before the holidays in November and December.  The market price drops so it can clear last months birds right before the holidays. With this in mind, may I suggest the following changes to the hypothesis of the turkey study. Like the seasonal studies this is more descriptive than predictive. Buy when you think risk appetite will increase, and sell before risk appetite disappears. I stumbled across the following warning from S&P rating agency from Feb. of 2003. Of their 10 sectors (technology being split into tech and telecom) they gave negative outlooks to 5 sectors in order of negative watch (rating changes outlooks negative) . The rankings are based on those companies S&P gives a credit rating and are in the S&p 500 index which was 435 companies in 03 1. Utilities (worst with 49% on negative watch) 2. Consumer Discr. 39% 3. Telecom 33% 4. Tech 31% 5. Industrials. While only 2 sectors with positive outlooks. 1. Financials 2. Healthcare While not mentioning Energy, materials or Consumer staples. Looking over the results of the sectors from March 03 to march 07 with the Vix falling these turkey sectors outperformed the positive outlook with about a 50% r^2 to 4 yr return to rank worst to positive outlook. I'll leave it to the reader to develop a this into a more predictive/profitable study.



 From Capital Press, The West's Ag Website:

"Tree seedling nurseries have been hard hit financially on two fronts. The housing market free-fall has sunk lumber and timber prices, reducing logging operations and thus cutting demand for seedlings for reforestation. At the same time, large numbers of Christmas trees have been reaching maturity and tree prices have fallen in recent years, reducing that industry's demand for seedlings as well."

"'We've seen a tremendous downturn in orders,' said Tom Jackman, CEO of IFA Nurseries, which produces seedlings for forestry in numerous locations in Oregon and Washington."

Craig Bowles responds:

I had a buddy who used to sell trees. He always said there's a three-year cycle. By the third year, everyone has jumped into the business, so sell out early and don't order that second truckload. I remember helping him one year and the guy across the street was getting that second truck just as we cut prices to $25/tree. We still even had "free trees" just before Christmas.

James Schroeder writes:

I had the great joy of growing up on a family Christmas tree farm and retail lot Wisconsin. In fact I've made the 3-4 hour drive home for the last couple of weekends to help my parents out as the ready their retail lot for the Christmas season.I'm not familiar with a three year cycle at the retail level, but that may be a regional thing, or it might be that my parents really aim at creating an experience that brings people back year after year. Aside from the consistently high quality trees they offer every year, they also strive to offer the best service in the area. More importantly they add little touches that make the Christmas tree shopping experience more of a tradition than a transaction. There are cookies and hot apple cider in the office (where people pay for their tree and pick up any smaller items they may need or want). If it's a Sunday the Packer game is on the office TV. Throughout the season there are surprise visits from reindeer. And there are many other small touches that hopefully transform the experience into something more than commerce.

On the growing and wholesale side of the business, trends are hard to predict and prepare for because they must be anticipated 8-12 years in advance. In the late 80s there was a trend in the growing industry toward the planting of lower quality, easier to maintain species (pines instead of firs) and from this came my first lesson in contrarian thought, offered by my dad, "Everyone is planting pines right now, because that is what is in demand now, no one is planting firs; in 10 years if you have firs for sale you'll command your price." He was right, and he planted nothing but firs for several years. Interestingly he has been planting more and more pines of late. Sounds like the cycles are changing.



 Back when I was a freshman in college, I had to take a course in University Physics. I found the course to be most practical, and helpful in the development of my thinking. One phenomenon that we studied in that class was the concept of Parallax. A quick Wiki definition of parallax is:

"Parallax is an apparent displacement or difference of orientation of an object viewed along two different lines of sight, and is measured by the angle or semi-angle of inclination between those two lines. The term is derived from the Greek parallaxis, meaning 'alteration.'"

A person can observe in real life the effect of the parallax by measuring something, using a ruler and not looking directly over the scale. By looking at an angle other than directly over the scale will cause a measurement error due to the parallax. That error can be measured and corrected by knowing the distance from the object and the angle. One's measure of the market might be affected by an internal, mental parallax. This parallax might be a function of the time frame, or might be something else… what else I don't know. It would be interesting to see if anyone has studied or quantified this concept as related to markets.

George Zachar adds:

 Greybeard camera buffs have studied this, using twin-lens reflex (TLR) cameras. One of my prize possessions is the Voigtlander TLR my dad took with him, fleeing Europe in 1949.

Lots of info on this phenomenon in photographyland.

Don Chu writes:

 “The stars are the apexes of what wonderful triangles! What distant and different beings in the various mansions of the universe are contemplating the same one at the same moment!” (H.D. Thoureau)

Thoreau probably did not have in mind stellar parallax in relation towards distance computation, and his imagined use of triangulation is more a heartfelt outreach to find resonance with another, be it of this world or otherwise. Still, there may be something in Thoreau’s words that transcends their initial appearance and speaks more directly to Mr Watson’s musings.

Thoreau continues from the above: “Nature and human life are as various as our several constitutions. Who shall say what prospect life offers to another? Could a greater miracle take place than for us to look through each other’s eyes for an instant? We should live in all the ages of the world in an hour; ay, in all the worlds of the ages. History, Poetry, Mythology! — I know of no reading of another’s experience so startling and informing as this would be.”

Paraphrasing and taking enormous license with the inimitable Thoreau and one contemporary other, perhaps the inspiring lines above may be reduced to the more familiar and definitely modern - “a latticework of mental models.”

Mr Watson rightly postulated “internal, mental” parallaxes predicated upon by any number of possible variables. But one fears that trying to elucidate error terms in any single mental construct may necessitate recourse to never-ending phenomenological reduction and render any resulting “cognition” and perceived derivative error to be indeed, in doubt.

The unkindest and yet most impersonal a priori parallax may come from the observer himself, delivered through the remorselessly agnostic Observer Effect. In the context of the markets, presupposing that the state of a market system exists independently of its observer/participant will surely be unwise and inevitably, loss-making.

But here is a naive yet hopeful thought — perhaps singular errors from any one mental construct matters less from the perspective of the whole. If every man holds in his mind (and inherently all men do, to a greater or lesser degree), a “latticework of mental models”, then in a mind where the structural tensions and forces remain basically stable, it follows that individual mental disjoints/errors have mitigated and largely damped themselves out.

Perhaps a healthy dose of History, Poetry, Mythology! shall prove to be rather profitable…

Henry Gifford comments:

Older meters of the type used to measure electronic circuits have a speedometer type needle that moves across a numerical scale. To eliminate parallax there was a mirror mounted just above or below the numbers scale, which allowed a user who was not viewing the instrument from directly ahead to look at both the needle and its reflection, and use the reading that appeared midway between the two.

It reminds me of looking at currency values relative to other things instead of just each other.

Perhaps some prices of seemingly unrelated markets which have predictive value that could be used to trade in one or both of the seemingly unrelated markets.



A VAs the S&P begins its advance off of the decade lows, we find a telling indicator in daily Open Interest breakdown. We just completed five straight up-sessions, beginning with the 11/21 Fri bounce from the 739 low: O.I. in bigSP and E-mini were little changed. On 11/24, a powerful up-day: O.I. in bigSP was up big, E-mini's down. 11/25 up-tick: bigSP O.I. up, E-mini down. 11/26 big up-day: but bigSP O.I. slightly down, E-mini's down. 11/28 up-tick: bigSP O.I. down, E-mini's up.

So, the observation of this five-day bounce showed that bigSP players correctly went Long early-on and then basically aborted up-higher; while E-mini players did the opposite!

« go back


Resources & Links