State of the Laggard Rally

September 23, 2009

The laggard rally that began at the March 9th bottom is still alive and well. The table below shows the performance of a universe of mid and large cap domestic equities in September, broken down by relative strength decile and quartile and then compared to the universe return. Those at the top of the ranks are those stocks which have the best intermediate-term relative strength. Relative strength strategies buy securities that have strong intermediate-term relative strength and hold them as long as they remain strong.

Time frame (8/31/09 - 9/22/09):

In fact, the top 5 performing stocks in this investment universe so far this month have been stocks that (with the exception of AMD) have dramatically underperformed the S&P 500 over the last 12 months.

Even though the best performance is still coming from those stocks with the worst longer-term relative strength, it is encouraging to see the performance of the top decile pull slightly ahead of the universe for the month.

How long this laggard rally will persist is anyone’s guess, but I suspect that the further we get from the bear market low the better relative strength strategies will perform.

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Posted by Andy Hyer

The Market Gods

September 23, 2009

will let you buy on the bottom tick and sell on the top tick once in your investing career. You are, however, free to do the opposite as often as you like.

Nouriel Roubini’s stupendously accurate (and lucky) prediction of a financial meltdown is thus counterbalanced by this article in Forbes in which he contends that the stock market will go much, much lower. Check the date on the article-it is three days after the bottom.

My point is not to bag on Mr. Roubini’s forecasting prowess, but just to point out the uselessness of prediction in general.

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Posted by Mike Moody

A Primer on Behavioral Finance

September 23, 2009

Even the CFA Institute has been holding seminars on behavioral finance in the last ten years. A number of years ago, they devoted an issue of the Financial Analysts Journal to behavioral finance. Behavioral finance came about because of all of the anomalies that were observed when making predictions from Modern Portfolio Theory. Certain things should have happened, but they didn’t—and so researchers wanted to find out why.

What they discovered was a whole host of cognitive biases that human beings share. These biases are probably quite adaptive under most circumstances, but in investing they are not. (Cognitive biases are not just present in investing. Statisticians can document tons of behaviors that are not borne out by the numbers. They are adaptive for some reason other than trying to get the optimal outcome. For example, here is an article about a high school football coach who refuses to punt, always goes for it on fourth down, and uses only onside kicks. Being the first to do things differently is perhaps not psychologically comfortable, but his behavior is based on statistical data. Although he may sound like a crackpot, he’s already won a state football championship.)

Morningstar has a nice piece here on some of the most common cognitive biases that affect investors. The implication is pretty clear: control these behaviors and your results will improve. Not surprisingly, that’s exactly what our systematic processes are designed to do.

1 Comment | Investor Behavior, Thought Process | Permalink
Posted by Mike Moody

Emotional Reactions Know No Bounds

September 23, 2009

Lest you think American investors are alone, it turns out that European investors are just as subject to making poor investment decisions on the basis of emotion. One of the reasons that many predictions of Modern Portfolio Theory don’t hold up is that investors are human, and thus not necessarily rational.

This highlights the importance (we think) of using a systematic, quantitative process rather than emotion.

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Posted by Mike Moody

Why Predictions Are Often Wrong

September 23, 2009

We all know how difficult it is to get predictions right. And even when the forecaster is extremely knowledgeable about the topic—maybe even the world’s leading expert—the prediction is often wrong. Why does that happen?

In a great post about predictions, Phil Birnbaum notes, “The problem is that no matter how much you know about the price of oil, it’s random enough that the spread of outcomes is really, really wide: much wider than the effects of any knowledge you bring to the problem.” (The emphasis is mine.) In other words, the standard deviation around the mean is so huge that getting it right is simply a matter of luck.

Rather than rely on prediction (luck), we rely on our systematic process to guide our investment decisions. A systematic process is not always correct either, of course, but the decisions are made on the basis of data rather than relying on luck.

(Thanks to John Lewis for the article reference.)

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Posted by Mike Moody