Behavioural finance: Mean reversion

June 2016

Regression to the mean is a technical term for things evening out from extremes; if a variable is extreme on first measurement, it will tend to be closer to average on its second measurement. Primarily associated with statistics, the concept was first popularised by Sir Francis Galton in the 19th century based on his work on genetics and hereditary stature.

A good analogy that helps to explain the mean regression concept and some of the difficulties we have with it relates to the experienced golfer who is a 10 handicapper. When he has a bad round that is way over his handicap, he books an hour with the pro and improves next time. But did the pro really help or is this simply another case of reversion to the mean? The bad round was bound to be followed by one closer to his handicap, yet the fact he went to the pro remains persuasive to him.

This is what makes mean regression a difficult concept for the human mind to grasp: our pattern-seeking brains are strongly biased towards causal explanations. The principles of randomness and regression to the mean rarely make satisfying and vivid explanations. This is why essentially random events are often ascribed causal explanations in the media.

Unfortunately, regression to the mean can have negative effects if misinterpreted. For instance, in the field of education, teachers can be guilty of falsely attributing the effect of their interventions – castigation of poorly performing students can seem more effective than praise.

In investment, regression to the mean is more commonly referred to as mean reversion and it has a different meaning. It is used to describe how returns can be extreme in the short run but more stable in the long run. Or to put it another way, periods of lower returns in certain markets or sectors tend to be systematically followed by compensating periods of higher returns.

This is a powerful idea that underpins certain value and contrarian approaches to investing. We know that shifts in investor sentiment can cause market sectors and stocks to become loved or unloved – this is what sets up the conditions for mean reversion. Pure (unloved) value stocks are those companies that are intrinsically cheap based on a simple “sum of the parts” valuation of their business. They are not stocks that can be characterised as “cheap” based on whether they meet projections of future growth. The latter are better thought of as undervalued growth stocks.

The value approach is also informed by the observation that some stocks move around within long-term peaks and troughs in metrics such as price-earnings ratios, price-book ratios and dividend yields. This means they can be bought on dips with an expectation that the valuation or share price will revert to the longer-term mean. Using mean reversion involves identifying the trading range for a stock and calculating the average price or valuation. Profit warnings, which can happen for many reasons including cyclical or temporary setbacks, provide one example of mean reversion in action.

Pure value stocks tend not to have compelling buy rationales attached, nor do they have alluring growth elements such as digital and e-commerce strategies. For this reason, they tend to lack cheerleaders and they can often be relatively dull businesses. However, dull businesses can be effective ones that become irrationally cheap due to swings in investor sentiment.

Some sectors of the stock market occasionally get hot, others get cold. From 2000 to2003, the share prices of technology stocks fell after the dotcom bubble. At the same time, however, “old-economy” stocks like breweries – shunned during the bubble years for being boring – did well as they positively reverted towards the mean. The inflated sectors deflated and the cold, unloved sectors won over weary investors looking for reliable earnings.

Some ETFs try to take advantage of mean-reverting phenomena but investors should carefully consider the turnover of such systemic strategies and the nature of portfolio construction. Systematic approaches based on screening for cheap stocks don’t discriminate cheap yet solid businesses from fast-falling duds. Cheap stocks can’t mean revert if they go bankrupt. Unstinting company and industry analysis can separate value opportunities from value traps.

Mean reversion is a concept that can be somewhat confusing in the investment world, however. The waters are muddied by the fact that some investment strategies (value, contrarian) seem to be partly dependent on the existence of mean reversion; others seem to be partly dependent on the fact that there are notable (and valuable) exceptions to the “rule”.

In this case, the exceptions are much vaunted “earnings-growth-compounder” stocks that defy mean reversion (in profits and share prices). These stocks can grow earnings over a sustained period due to a strong structural growth driver – for example, favourable demographic trends – typically combined with some sustainable competitive advantage (which can be patent-protected technological or intellectual property, often supplemented with brand loyalty).

The challenge lies in correctly identifying these stocks and investing at sensible valuations. Forward-looking valuation tools such as discounted cash-flow modelling can be particularly useful to project potential returns, since price-earnings multiples can occasionally flash a false sell signal. For much of the past decade, star performer Apple was consistently characterised by its detractors as expensive, yet it defied the odds by delivering earnings growth based on a strong product pipeline that was met with sustained demand for its products.

So there you have it: some stocks revert to the mean; some defy the mean completely. It’s another take on the age-old debate between growth and value. There is plentiful evidence for both kinds of strategies outperforming the market over time.

 

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References to specific securities should not be taken as recommendations.