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Market Anomalies And Behavioural Finance

Investment Theory - Part VII

Market Anomalies And Behavioural Finance

Stock market anomalies are phenomena that contradict the efficient market hypothesis (EMH) as they seem to show the possibility of consistently achieving abnormal returns by engaging in an investment strategy that takes advantage of such an anomaly.

There is a vigorous debate in academia about the nature of market anomalies, such as the tendency for stocks that have risen in the recent past to keep going up (momentum). Do they reflect a hidden risk factor that (according to CAPM logic) deserves a greater reward? Or are they simply be the result of “data mining”, along the lines of “torture the numbers enough, and you will find something eventually”.

Also, one should not forget that any test of market efficiency is a joint hypothesis test, meaning that one’s determination of the “normal” return of an asset is based on the assumption that the asset pricing model used (for example, the CAPM) is the correct one. So maybe those anomalies occur because one is using the wrong pricing models to determine the normal return.

Practitioners, on the other hand, would most likely argue that those “anomalies” are not real anomalies, but rather normal occurrences in an inefficient market. Whatever the reasons are for the phenomena outlined in this article, they remain a matter of debate, which is interesting to look into. Famous “puzzles” that researchers have come up with include:

  • Size Effect
  • Value Effect
  • Momentum Effect
  • Post-earnings Announcement Drift
  • Calendar Anomalies

Famous Investment Anomalies

  • Size Effect

The size effect describes the phenomenon of small-cap companies to outperform large companies in the long-run. To some, this is not a real anomaly as they argue that smaller firms have a longer way to grow than their larger counterparts and this incremental growth should allow their stock to outperform that of slower growing giants.

  • Value Effect

One of the best-known investment anomalies is the value effect, where stocks with below-average accounting metrics (like price-to-book ratio) tend to outperform the market. This anomaly has influenced a whole generation of value investors, some of which are among the most successful investors of all times.

A famous explanation for the value effect, which is in line with a popular topic within corporate finance, is the reflection of distress risk. Put simply, proponents of this explanation argue that the superior returns of cheap value stocks reflect their increased risk of falling into financial distress, which is associated with costs and a risk of (total) capital loss.

  • Momentum Effect

A study first conducted in 1993 found that recent winners outperform recent losers in the short to medium-term. If this effect was to be reliably exploitable, one could do so by buying the “winners” and shorting the “losers”, to make an isolated bet on momentum without having to fear wider market fluctuations. This would, of course, violate market efficiency.

Over the years, academics and practitioners have come up with a range of possible explanations for the momentum effect. One of the theories is that markets are not promptly pricing in new information but rather do so more gradually.

One of the reasons for that could be the complexity of information which means that market participants need some time to fully interpret a new set of information before reviewing their investment decisions based on the new information.

Another theory is that investors choose fund managers on the basis of their past performance; when doing so, they will naturally pick those that have done well. When they switch, the successful manager will receive money that they will reinvest in his favourite stocks; by definition, these are likely to be stocks that have recently performed well.

This inflow of cash will push such stocks up even further. This theory would also explain the limited time horizon of this anomaly, which tends to disappear (or even turns around, see “reversal effect”) in the long-run.

  • Post-earnings Announcement Drift

This phenomenon describes a significant post-earnings announcement price drift in the direction of the earnings surprise, also called earnings momentum. In perfectly efficient markets, new information (such as surprisingly high or low earnings during an earnings announcement) should cause a one-off instant price shift in the direction of the surprise.

However, what is usually observed is a longer lasting gradual shift in the price rather than an instant repricing of all new information. The dominant view is that an incomplete response to earnings is the cause of this anomaly, again contradicting the “instant pricing of all available information” assertion of the EMH.

  • Calendar Anomalies

One of the most puzzling categories of market anomalies is that of calendar anomalies. These describe phenomena like the “January Effect”, where it was observed that most of the premium for holding small cap or high book-to-market portfolios comes in January.

There also seems to be a “Monday Effect”, as several studies have shown that returns on the first day of the week are lower than returns on other days of the week.

The same holds for the “Turn of the Month Effect”, where stocks have been shown to yield consistently higher returns on the last day and first four days of the month. These anomalies are often explained due to the timing of real money (pension funds, asset managers) (re-)allocating their funds.

Behavioural Finance Explanations of Anomalies

A relatively new school of thought seeks explanations for seemingly irrational anomalies (why does no one exploit an anomaly once it is publicly known) in the field of psychology.

By describing psychological biases of investors, supporters of behavioural finance have come up with a set of alternative explanations for irrational investor behaviour and how it leads to market anomalies. These are some of the most well-known biases:

  • Conservatism

Conservatism describes investors’ preference to stick with their old beliefs rather than changing them due to new information about an asset or a stock.

  • Overconfidence

The most documented bias in experimental settings. Investors overestimate their ability or the precision of their information. This leads them to behave less risk-averse than they should, leading to irrational investment decisions. Since people fail more often than they expect to, rational learning over time would (in theory) tend to eliminate overconfidence.

  • Biased Self-attribution

Individuals attribute events that confirm their beliefs/actions to their own ability, and discard events that disconfirm their beliefs. In other words, investors tend to attribute good outcomes to their own ability, and bad outcomes to external circumstances (e.g., bad luck). This mechanism hinders a rational learning process and induces individuals to learn to be overconfident.

  • Limited Computational Ability

Humans are limited in their information processing and have a limited attention span. They often focus on a subset of all available information (“heuristics“). This is one of the most intuitive flaws of the EMH, as everyone can relate to the human constraint of not being able to process every piece of a large chunk of information.

In a perfect world in line with all EMH assumptions, investors gather all possible information about a firm and test all kind of statistical and forecasting models to assess its value. However, their time is limited and therefore they end up making an investment decision based on limited information, leading to suboptimal and often irrational investment decisions.

  • Attention Bias

Investors tend to look at stocks that are covered by big banks and appear in the newspaper at the expense of less-known stocks, despite their proven superior return potential.

  • Under-diversification

On average, investors tend to only have 4-6 stocks in their portfolio and focus their portfolio heavily on stocks in their own country.

  • Disposition Effect

There is a tendency of investors to sell shares whose price has increased while keeping assets that have dropped in value. This is further explained by the famous “prospect theory“ developed by Kahneman and Tversky, which basically explains that people react in a more extreme manner to increasing losses than they do to rising profits, causing them to engage in irrational investment behaviour.

Implications on Market Efficiency

Why is all this important? Well, ultimately this article (and the previous one) is about the EMH. Having looked at some of the still prevalent anomalies in the market, it is hard to fully believe in the EMH with all its assertions put forward by its supporters.

It seems that the much more interesting question is why some of the anomalies exist and whether one can learn something about investor behaviour in that context. The field of behavioural finance provides some interesting ideas for this.

One thing that is important to keep in mind is that inefficiencies are the reason for their own elimination. In today’s market, it can be assumed that an efficiency will be tried to be exploited by a range of market participants and hence the profitability of exploiting the inefficiency decreases until it is not profitable at all anymore.

The rise of ETFs and Smart-Beta investing (factor investing), which try to exploit phenomena like the outperformance of low-volatility stocks, have particularly contributed to eliminating some inefficiencies.

Conclusion

Most of the strategies that tried to benefit from market inefficiencies were actually profitable (creating Alpha) for some time, but eventually, as more market participants tried to exploit the same phenomena, with their profitability they lost some of their attraction.

From this finding one can take away an important lesson on market efficiency: it is not a stable concept, markets are not efficient or inefficient forever. They can change their degree of efficiency over time. And as more and more of the apparent inefficiencies are exploited by an increasing number of investors, the market arguably becomes more efficient over time.

However, that does not mean that the market is headed for a day in the future where it will be completely efficient after all inefficiencies have been wiped out. Rather, in times where psychology plays an excessive role, for example at the height of bubbles or during their bursting, markets can lose some degree of efficiency.

Howard Marks provides a good example of this when he talks about how the best investment opportunities arise when one can buy from a “forced” seller. Such forced sellers could be, for example, banks that have taken on loans that they are not allowed to hold anymore due to tightened regulatory requirements.

Those banks will then have to sell those assets at any price, which makes it a great bargain for investors looking to buy this asset. This shows how external, uncontrollable factors (in this case changes in regulation) can affect market efficiency.

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