Dec
2
A Disturbing Chart, from Bruno Ombreux
December 2, 2014 |
A disturbing chart: "This is Probably the Second Worst Time in History to Own Stocks"
Bill Rafter writes:
The trouble with the chart is that the regression fit was done cumulatively, resulting in older data being subject to look-ahead bias. Thus only the current values are useful, and one wonders exactly how useful. As Steve has commented, the way to foil that is to use a moving regression fit in which the values are static over time, always taking the last point in the fit. Thus all data, past and current are relevant and can then be used in statistical studies.
The question that then comes up is which lookback period do you use. Wherever possible all lookback periods should be adaptive, the question then being to what input. In shorter term price data the market will tell you the relevant lookback period. I have never tried determining lookbacks for longer term data because (a) I don't expect to live long enough to take advantage of it, and (b) too many things can happen in the short run to screw up a good plan. Most people don't marry someone in their 20s based on the supposition that (s)he will look good in their 70s.
I also question the use of any equity or debt data prior to 1972. If you don't know why, ask Stefan. **That's one of the great things about the list; there are sources for just about everything.
Several moving functions you should consider:
Moving linear (i.e., regression) fits and their slopes.
Moving parabolic fits and their slopes. Since most economic and price data are parabolic, this is the better of the two. There is also something to be gained in the difference between a parabolic fit and a linear fit. Fitting parabolas is quite tricky, and it took us a while to code it. If you try to do so and want a check on your efforts, try fitting a parabola to a straight line. If the result is ludicrous, try a different method.
Moving correlations are particularly interesting between markets that might be alternatives to one another. Moving correlations between stocks and bonds (levels to levels) are something we have used for years and continue to do so. I thank Gibbons for his comment that Colby & Myers recommended them, as I had not been aware of that. (I'm not a fan of C&M.)
Gyve Bones responds:
Colby and Myers didn't recommend the linear regression study per se… the empirical analysis simply showed that study to perform best with a fixed loopback parameter over NYSE index returns data over a long period of time compared to other trend following signal generators. This book was an early attempt to quantify different approaches to see how they performed trying as best as can be done to compare apples to apples. In the mid-to-late 80s, it was the best thing that had been done like that since Dunn & Hargitt's study using punch card futures data in the late 1960s (which found that the Donchian Four Week system was best, the system which launched a thousand CTA, including the Dennis Turtles and their spawn.) Another similar study was done in the 90s by Jack Schwager and another fellow whose name escapes me at the moment which was well done.
Larry Williams adds:
A question: when was the regression line fit? Today? 20 years ago? 50 years ago? The slope will change based on your starting and end points. How overbought or sold is a function of this. A more careful analysis would either apply this same "method" every year with a set of rules (i.e sell above x% overbought) or would do the same thing on a rolling window basis. It's an interesting chart nonetheless and gives one pause, but I would suggest it lacks a certain amount of rigor.
Gibbons Burke writes:
It seems to me that this is a flawed chart to look at historically to make rules from because the trend line drawn into the past contains information about the future. The line is drawn using the linear regression of the entire data set so, for example, the line segment covering 1998-1999 "knows" about what happened in 2014. Very deceptive and misleading to make a rule based on the relationship of the data to the trend line.
Victor Niederhoffer comments:
The disturbing chart is a case study of why charting is so misleading because of the regression bias and also at the variance of a sum is the sum of the variances.
Steve Ellison says:
Here is the way to solve the problem of the regression line incorporating future data. Attached is a graph of a "moving regression", as Dr. Rafter calls it. For each date, the red point is the last point of a 30-year regression of the S&P 500 as of that date (the graph is from 2010).
Comments
WordPress database error: [Table './dailyspeculations_com_@002d_dailywordpress/wp_comments' is marked as crashed and last (automatic?) repair failed]
SELECT * FROM wp_comments WHERE comment_post_ID = '9828' AND comment_approved = '1' ORDER BY comment_date
Archives
- April 2021
- March 2021
- February 2021
- January 2021
- December 2020
- November 2020
- October 2020
- September 2020
- August 2020
- July 2020
- June 2020
- May 2020
- April 2020
- March 2020
- February 2020
- January 2020
- December 2019
- November 2019
- October 2019
- September 2019
- August 2019
- July 2019
- June 2019
- May 2019
- April 2019
- March 2019
- February 2019
- January 2019
- December 2018
- November 2018
- October 2018
- September 2018
- August 2018
- July 2018
- June 2018
- May 2018
- April 2018
- March 2018
- February 2018
- January 2018
- December 2017
- November 2017
- October 2017
- September 2017
- August 2017
- July 2017
- June 2017
- May 2017
- April 2017
- March 2017
- February 2017
- January 2017
- December 2016
- November 2016
- October 2016
- September 2016
- August 2016
- July 2016
- June 2016
- May 2016
- April 2016
- March 2016
- February 2016
- January 2016
- December 2015
- November 2015
- October 2015
- September 2015
- August 2015
- July 2015
- June 2015
- May 2015
- April 2015
- March 2015
- February 2015
- January 2015
- December 2014
- November 2014
- October 2014
- September 2014
- August 2014
- July 2014
- June 2014
- May 2014
- April 2014
- March 2014
- February 2014
- January 2014
- December 2013
- November 2013
- October 2013
- September 2013
- August 2013
- July 2013
- June 2013
- May 2013
- April 2013
- March 2013
- February 2013
- January 2013
- December 2012
- November 2012
- October 2012
- September 2012
- August 2012
- July 2012
- June 2012
- May 2012
- April 2012
- March 2012
- February 2012
- January 2012
- December 2011
- November 2011
- October 2011
- September 2011
- August 2011
- July 2011
- June 2011
- May 2011
- April 2011
- March 2011
- February 2011
- January 2011
- December 2010
- November 2010
- October 2010
- September 2010
- August 2010
- July 2010
- June 2010
- May 2010
- April 2010
- March 2010
- February 2010
- January 2010
- December 2009
- November 2009
- October 2009
- September 2009
- August 2009
- July 2009
- June 2009
- May 2009
- April 2009
- March 2009
- February 2009
- January 2009
- December 2008
- November 2008
- October 2008
- September 2008
- August 2008
- July 2008
- June 2008
- May 2008
- April 2008
- March 2008
- February 2008
- January 2008
- December 2007
- November 2007
- October 2007
- September 2007
- August 2007
- July 2007
- June 2007
- May 2007
- April 2007
- March 2007
- February 2007
- January 2007
- December 2006
- November 2006
- October 2006
- September 2006
- August 2006
- Older Archives
Resources & Links
- The Letters Prize
- Pre-2007 Victor Niederhoffer Posts
- Vic’s NYC Junto
- Reading List
- Programming in 60 Seconds
- The Objectivist Center
- Foundation for Economic Education
- Tigerchess
- Dick Sears' G.T. Index
- Pre-2007 Daily Speculations
- Laurel & Vics' Worldly Investor Articles