Charles Kirkpatrick has been publishing his market newsletter for decades. His simple factor based stock-screener has been beating the pants off the market for a long time. Here is a paper he published in 2001 “Stock Selection – A Test of Relative Stock Values Reported Over 17-1/2 Years“. He has continued to refine and simplify his model which includes relative strength and price/sales as key factors. But hey, what’s wrong with 20%-30% compounded returns? Here is his homepage.
When listening to Lo’s speech I was struck by the comment he made on a factor that was predictive in up markets (EPS Growth), but not down markets. Kirkpatrick decided it was not a good search criteria, but he could not explain the difference in behavior related to the different market environments. Lo offered an explanation based upon his AMH model. In bull markets, investors are making decisions using the part of their brains (neocortex) associated with analytical skills and seeking to maximize profits. In down markets, the ‘fight or flight’ part of the brain influences the investment decision making process and fear dominates the markets.
I have done quite a bit of work with factor based stock models, but never divided the periods based on trend.
My Q: Is there any research out there that takes a look at the most predictive factors for up markets (say, above the 200 day moving
average) vs. down markets (below)? Any academic literature? Thoughts? Any quant shops that do this?
He has also recently published the definitive textbook on technical analysis, Technical Analysis: The Complete Resource for Financial Market Technicians
the first similar analysis I can think of is described in a brief paper by John Hussman of the Hussman Funds. Link is here:
http://www.hussmanfunds.com/pdf/mixdist.pdf
I really enjoy your blog and link to you often. Unfortunately that won’t bring you many readers other than my relatives. http://www.derivativemusings.blogspot.com/
This is the sort of thing that makes me want to get a piled higher and deeper degree.
A long time ago in a galaxy far, far away, a man named O’Neil used a screen for stocks with strong EPS growth, but only entered them when the market trend was up.
They called it “CAN-something” or other …
Verily, I say to thee, there is nothing new under the sun.
BBL – I’ll check it out
Bill – Yeah I’ve read O’Neils books, but that doesn’t help when market is going down. . .looking for predictive factors when that happens as well.
He’s got a book on how to short stocks, too.
There are quite a few papers looking at growth vs. value in bull and bear markets. Value tends to underperform in bear markets and this is sometimes cited as the increased risk that you take in compensation for higher long run historical returns.
-Gary
Gary that is the best ID ever.
bill – still doesn’t answer what i am looking for, but thanks for the note.
You should check the equity curve of the short system here:
http://www.billakanodoodahs.com/2008/01/trpits-part-iv/
Note the timeframe during which it was hitting highs.
Scoring algorithm is here:
http://www.billakanodoodahs.com/2008/01/trpits-part-iii/
To some extent, taking what works long (espec. in bull markets) works really well when you flip it in a bear market.
If you have monthly output for test long and short data, you can always segregate it by whether the 100 ema was above the 180 ema for the S&P 500 (or in your case, the S&P 500 was above the 12-month sma).
Or, you could simply take a long-only set of factors that develop a portfolio with high beta (I mean REAL beta, as in slope of regression line beta), and go short those stocks in bear markets (assuming you have a good definition of those) and go long them in bull markets.
I’m not aware of any academic work on the subject.
Here’s another question, or really, a statement. Looking for factors that work in down markets better than in up markets presupposes that the modeler’s universe is domestic stocks and the benchmark is a relative one …
The response below may not be exactly what you were looking for, but may be helpful to you and/or your readers nonetheless. It is a bit wordy, but if you bear with it, I think you can find a nugget or two of value!
This problem really has two aspects; determining the market environment (bull or bear), and then deriving factors to gain the maximum RAR from that environment.
IMO the market environment question really comes down to market timing (for example, it would be useless to measure price v. the 200 day ma unless this exercise had some predictive value).
The question is then what is the most effective market timing model. Academic research has determined pretty conclusively that stocks are positively autocorrelated in the 3-12 month horizon, and negatively autocorrelated in the 1 month and under horizon. For a basic market timing model, it is then a matter of selecting and testing a two factor model which selects one longer term and one shorter term factor (moving average, ROC, advance/decline measures, etc). The more time one applies to researching and backtesting the factors, the better the model.
The really interesting aspect of market timing, and the segway into the response to your question, is when one combines sentiment data into the market timing and factor selection process.
Denys Glushkov from Barclays demonstrates pretty well in the paper below that sentiment can not only help with the market timing problem, but in the question of factor selection as well.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=862444
I think if one expirements with the momentum/mean-reversion technique I discussed above, and combines that with sentiment data, a robust market timing model will be the result (for an example, the blog regimenia demonstrates an excellent fusion of momentum and sentiment models into an asset allocation model).
Then, finding inspiration from Glushkov, one can construct a high-beta portfolio for the times when the model is positive, and a low-beta portfolio when the model is negative (of course the factor doesn’t have to be Beta, but it is something that performs well in my testing).
this is a useful research
http://www.financialmarketresearch.net/
if my memory serves me well, years ago i heard an inspired discussion concerning the bull/bear- relative strength issue presented by a money manager named “Gary Anderson?” who wrote a book- the Janus Factor.