Lessons from David Dreman (Part 3)

I want to wrap up this mini-series today on David Dreman by discussing a few more cognitive biases, or heuristics, and offering some commentary on effectiveness.

David Dreman may be a living example of a repetitive theme throughout this blog: ideas that sound good but truly have no merit. I make no performance claims about Dreman Value Management. I mentioned backtesting his idea of investing in out-of-favor issues because I have not done so myself. Contrarian investing is conventional wisdom discussed in books and seminars for traders, which is a big reason it resonates with me and feels right.

I will close with discussion of a few other types of cognitive heuristics.

Historical consistency leads to greater confidence about predictability. Dreman found investors have more confidence in a stock that consistently rises with 10% earnings growth than a more volatile stock with 15% earnings growth. Is a less volatile stock more likely to outperform into the future? That is an empirical question.

The anchoring heuristic describes a common human tendency to rely heavily on the first piece of information when making decisions. Other judgments are made in reference to the anchor, and bias exists toward interpreting other information around the anchor. For example, a stock purchase price defines what is “good” (higher subsequent prices) and “bad” (lower prices). These are purely subjective judgments. Mr. Market certainly does not care about my cost basis.

Finally, confirmation bias is the tendency to search for, remember, interpret, and favor information in a way to confirm preexisting beliefs or hypotheses while giving less consideration to alternative possibilities. The effect is stronger for deeply entrenched beliefs and emotionally charged issues, which would certainly include the prospect of making money!

Confirmation bias is the main reason I seek collaboration for trading system development, which I have written for a long time. I do not want to be blinded by confirmation bias if I get a whiff of something good. In this case, other critical minds can better maintain objectivity; the idea remains less emotionally-charged because it is not theirs.

Certainly I would rather be proven wrong in the development stage rather than with real money on the line. Confirmation bias circumvents this and collaboration is the antidote.

Lessons from David Dreman (Part 2)

David Dreman uses a contrarian investing approach in an attempt to profit from irrational heuristic thinking. Today I want to discuss Dreman’s suggestions to protect yourself from such harmful cognitive biases.

With regard to the representativeness heuristic, Dreman suggests focusing on relevant factors that may result in an entirely different investment result. Do not be blinded by similarity. Sometimes only a slight similarity is necessary to significantly resonate with us especially if a big profit/loss was realized in the previous instance.

Dreman cautions against being influenced by short-term returns of a money manager, analyst, or any kind of financial adviser. The better the numbers, the more alluring the results but this is based on an insufficiently small sample size. Look for stronger supporting evidence like a longer term track record.

Dreman suggests being doubly cautious of short-term returns when they deviate significantly from long-term averages. This applies to performance of money managers, analysts, and advisers as well as to individual stocks or funds. Mean-reversion is the rule, not the exception.

Dreman recommends patience with new investment strategies rather than expectation of quick success. Investors are more likely to adopt strategies that have recently done well, which implicates mean-reversion as an immediate headwind. One way to offset this would be to enter a strategy when it seems somewhat out-of-favor. Such a strategy has already mean-reverted or is broken altogether, in which case future outperformance will no longer result. Only in retrospect can these two possibilities be differentiated.

These are four ways to prevent biases from affecting your investing decisions.

Dreman suggests purchasing out-of-favor stocks (e.g. low price-to-earnings ratios) as one way to profit from the biases of others. While this idea sounds good, as with most other strategies I would be interested to see a large backtest to better understand context.

Lessons from David Dreman (Part 1)

David Dreman founded Dreman Value Management in 1977 and has written many books and articles on contrarian investing. In this mini-series I will highlight certain aspects of his investment philosophy that resonate strongly with me.

According to Dreman, sound investment decisions are obstructed by psychological biases that I have called heuristic thinking. Crowd behavior is therefore irrational, which leads to market bubbles and violent selloffs. Contrarian investing aims to profit from the excess.

Dreman discusses the representativeness heuristic: human tendency to draw analogies and see similarities in things that are completely different. Overemphasis on similarity leads to miscalculation if we forget to assess the actual probability of an event occurring. One example would be recognizing a company as belonging to the automotive industry and remembering what happened last time an automotive stock was purchased. Representativeness reduces perceived importance given to the variables critical in determining actual probability of the event (e.g. the stock moving higher).

Dreman discusses the law of small numbers, which is a judgmental bias that occurs when one assumes characteristics of a sample population can be estimated from a small number of observations or data points. An example would be investors flocking to the hottest mutual fund. Research suggests funds that outperform in one time period often underperform in the next. Investors also tend to follow stock analysts who have demonstrated recent accuracy rather than checking the analyst’s performance over time for a logical measure of accuracy.

Investors ignore regression to the mean. Data show a tendency for valuations and returns to revert back to long-term averages—a conclusion overlooked by investors who pile in to buy a hot stock or rush to dump out-of-favor shares.

Investors fall prey to information overload, which is related to information bias. When under siege by information, people tend to see only what they are interested in while blocking out the rest. This is related to confirmation bias. Information bias is a delusion that more information guarantees better decision making.

In the next post I will review Dreman’s recommendations to overcome heuristic thinking.

Can We Scientifically Understand the Financial Markets? (Part 1)

A couple years ago I stumbled across an interesting article by Jeffrey Mishlove, Ph.D. In the article, he presents some survey responses to the question about whether scientific understanding of the financial markets is possible.

While Mishlove does not present us with the optimistic responses, he does show us some of the more pessimistic ones:


> …The future never resembles the past and persistence in
> performance for any length of time in the investment industry
> is almost unheard of.


> I am surprised that you do not know that predicting financial
> markets can’t be done. It’s a “Fool’s Game”


> “Never…” there is no useful research. The minute any useful
> research emerged (to the general public as suggested by the
> question), it would immediately be incorporated into financial
> markets, rendering that research no longer useful.


> Most of us, including myself, are all about data, but, as
> others have said, no empirical results – back, realtime or
> front, regardless of the power applied – can be the basis for
> long-term successful trading. Sadly, not even actual results
> can form such a basis – as actuals are indistinguishable
> from random.


> Back testing is essential but most of the output is a
> curve fit illusion… Forward testing is of little use
> either; especially for longer term trading….I fear that
> studying scientific research is not a route to Eldorado.
> Investors should remember that at the end of the day,
> Candide gave up the attempt and resorted to peacefully
> cultivating his garden. Most would be traders would do
> well to do the same.


> Building models incorporating genuinely objective data
> into a probability based decision chain is an
> interesting pursuit. However, no one knows what happens
> next particularly within any specified time slice.
> Seeking a useful predictive model producing near term
> efficacy is an exercise in futility.


I will conclude with the next post.

Day Trading Is Not All That (Part 3)

Inspired by the writing of Louis Horkan Jr., today I will conclude by sharing more experience of a full-time trader.

I am just one [full-time trader] so please take this for what it’s worth.

I do not find trading to be a business where I make money all the time. I make money much of the time but on rare occasion I lose far more than I ever make in a short time periods. This makes me interested, motivated, and humble. I am interested to overcome the challenge of staying on top. I am motivated to grasp and manage my risk every day in order to prevent career-ending losses. I am humble enough as a result of my experience to know it never makes sense to claim victory in this pursuit. I am always one catastrophic loss away from being forced to return to Corporate America.

I disagree with Horkan Jr. because I do believe trading is about having nerves of steel. The “preconceived ideas” are formidable distractions that have good potential to cost me a lot of money if my nerves of steel don’t resist the illusory temptation. I have found it necessary to flex my nerves of steel and be mentally tough in the midst of stressful drawdown. When I’ve had catastrophic losses, those nerves of steel have prevented me from walking away forever with tail between my legs.

Finally, I find it noteworthy that the amount of time I spend doing the actual trading (e.g. entering, working, and executing) is just a fraction of my overall workday. I do many other activities that keep me engaged and, I hope, “sharp.” I spend a lot of time blogging. I spend time backtesting. I listen to trading calls and trading groups.  I tweet with other traders.  I read trading forums.  I sometimes talk with other traders to share ideas and develop new strategies.

Thanks to Louis Horkan Jr. for a very thought-provoking article.