Psychology and smart beta

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Please note that this article may contain technical language. For this reason, it is not recommended to readers without professional investment experience.

‘Smart beta’ sounds like an oxymoron. How smart can it be to continue using the same strategy in such fickle markets? A portfolio manager calling on all his skills (‘alpha’) in analysing market environments (the source of ‘beta’) should be able to outperform an unchanged algorithm, right? And yet, for several decades, findings in behavioural psychology have cast doubt on this assumption.

Studies have found that investment decisions are fraught with errors caused by our cognitive and emotional biases, which are unchanging and which can be exploited systematically by the various factors used in a smart-beta approach. Here is a brief look at the ‘behavioural’ explanations of the performance factors in smart beta.

Momentum: A natural consequence of human evolution

Momentum strategies consist in buying what is going up and selling what is going down, with a typical horizon of a few months. However, to generate short-term returns, we ought to be selling what has just risen and buying what has just fallen. Classical economic theory has a hard time explaining such a strategy, given that new information, for instance on equities, is typically disseminated instantaneously to the entire market, which is then supposed to readjust prices immediately and rationally.

The field of psychology, on the other hand, sees human beings as the product of their evolution, i.e., animals that have learned to survive in an uncertain and hostile environment through their ability to communicate and organise themselves into groups. This evolution has led to both a certain wariness of change, which explains short-term mean reversion, and the slow actual dissemination of information and a strong drive to follow the crowd, which explains medium-term momentum.

In short, a human investor has a hard time changing his mind, but once he has made up his mind, he has an even harder time admitting when he is wrong. In emotional terms, it is far less dangerous to be wrong in a group than to be right alone.

The low volatility anomaly: Tapping the overconfidence bias

A low-volatility strategy consists in buying the least-risky shares on the assumption that they will end up offering roughly the same performance as riskier shares, but involve lower risk. This is at odds with classical economic theory, which – rationally – assumes that risk and return go hand-in-hand. From the viewpoint of psychology, the ‘low vol anomaly’ can be explained in several ways.

First of all, the most volatile shares are the best-known ones since they are the ones where something is happening. And we like what we know. Psychology calls this bias the ‘overconfidence effect’ and, as any celebrity will tell you, a bad reputation is better than no reputation at all. Highly volatile shares draw an excessive number of investors, which ultimately explains the anomaly.

Another psychological cause of the low vol anomaly is the ‘bias in estimating probabilities’. As lottery organisers will tell you, the emotional value of a probability is not the same as its mathematical value. Human beings are occasionally fearful, but still like to dream, so much so that they overestimate the low probabilities of big gains or the low probabilities of large losses. That’s why low-vol shares are often overlooked.

The ‘memory bias’ is the third cause of the anomaly. We believe we remember the past accurately, but, in fact, our memories are selective, preferring events that stand out, that make sense and, if possible, that work in our favour. As a result, the good investments that we remember will mostly be in the minority of the universe of volatile, successful shares and we feel we knew it all from the start.

Value and quality: Other forms of ‘investor blindness’

Smart-beta strategies based on fundamentals use companies’ financial data (on balance sheets, income statements, cash flow statements etc.) to pick investments. Value consists in selecting shares that look cheap compared to the level of profitability, for example on the basis of price/earnings (P/E) ratios. A quality bias consists in choosing companies that have generated large profits relative to the resources they used, for example on the basis of return-on-equity (ROE) data.

From a psychological point of view, the existence of these premiums proves that investors are, on average, underestimating the importance of financial data, which are publicly available but abstract in nature, compared to other, more emotional and more direct, factors. This observation encompasses psychology’s discovery of two very distinct ways of thinking that coexist within each of us: a conscious and logical system that is also ‘slow and effortful’ (According to Nobel Prize winner Daniel Kahneman in System 1/ System 2: Thinking, fast and slow), and a faster but more approximate system that is based on associated meanings, impressions and feelings.

The numerous bubbles in the history of finance have provided abundant illustration of the extent to which this second way of thinking can drive investors out of any economic rationality, even though, as the old saying goes, “trees don’t grow to the sky”.

Also see:
Bye-bye “Smart Beta”. Hello “Factor Investing”
Low-volatility anomalies in the time series of factor premia
Etienne Vincent

Head of Global Quantitative Management, THEAM

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