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Irrational Investments and Behavioural Finance

A SAD Stock Market Cycle – How the seasons of the year affect investor behavior 

It is well known that many external factors and personal biases affect investors and make them behave irrationally. But did you know that even the seasons of the year can affect investor behavior? 

The important factor that changes over the seasons of the year is the length of the day, so how many hours of sunlight there are each day. In their paper, Kamstra et al. (2003) show that seasonal variation in the length of daylight translates into seasonal variation in equity returns. Consequently, investors seem to change their behavior depending on the length of the day. But why? 

Why do investors change their behavior over the seasons? 

To understand this, one has to analyze the psychological factors involved.   

Studies suggest that approximately 10% of humans suffer from the so-called seasonal affective disorder (SAD) and a further 15% suffer from a milder form, the “winter blues”. SAD is defined as prolonged periods of sadness and chronic fatigue (it is a form of depressive disorder) during the seasons with relatively fewer hours of daylight. Symptoms may include difficulty in concentrating, decreased sex drive, social withdrawal, loss of energy, lethargy, sleep disturbance and carbohydrate or sugar craving. The disorder is not purely psychological, there is also a physiological source: SAD is connected to serotonin dysregulation in the brain and PET scans have revealed abnormalities in prefrontal and parietal cortex areas connected to to diminished daylight. For those affected, symptoms can start as early as in September, around the Autumn equinox. 

However, this does not yet explain how seasonal variation in the length of daylight changes investor behavior. To answer this, one has to look at experimental research in psychology that has shown that there is a direct link between depression and heightened risk aversion. Changing risk aversion indeed translates into changing behavior of investors in the stock markets: more risk-averse investors tend to allocate a larger share of their assets to less risky investment opportunities, like bonds, while less risk-averse investors tend to choose riskier investment opportunities, like stocks. 

What can we conclude from this in terms of investor behavior over the seasons? 

Investors affected by SAD or the “winter blues” will start to experience depressive feelings when days become shorter in Autumn. This will translate into them becoming more risk-averse and, consequently, rebalancing their portfolios towards less risky assets. In Spring, when the depressive symptoms fade, as days start to become longer again, the affected investors will become less-risk averse again and therefore rebalance their portfolios towards riskier assets. 

How does changing investor behavior translate into overall market behavior? 

Although of course not every market participant is influenced by this syndrome, approximately 25% of investors will be, and this is enough for individual choices to have a considerable effect on the overall stock market behavior. 

And this is exactly what Kamstra et al. show in their paper: stock markets present lower returns in Autumn, when SAD effects begin. Investors tend to sell stocks (to rebalance their asset allocation towards less risky assets like bonds) and this has a negative impact on stock prices, and hence stock returns. The month of September is the one in which returns are on average at their lowest point of the year, across a set of different stock markets in different countries and over a long time span. On the other hand, stock markets show abnormally high returns in early Spring, when days begin to lengthen and SAD effects begin to fade, since investors tend to buy stocks (to rebalance their asset allocation again towards more risky assets), increasing stock prices and,consequently, stock returns. As a matter of fact, stock prices on average peak in January, the first month after winter solstice, when days are starting to become longer again.  

Of course one could now ask whether the observed changes in equity returns are not caused by other seasonal factors. However, Kamstra et al. control for such factors and also test their hypothesis (that seasonal variation in the length of day translates into seasonal variation in equity returns) using stock market data from different latitudes and both sides of the Equator: They find that higher-latitude markets (e.g. Sweden) show a more pronounced SAD effect (the variation in the length of the day is larger there than in countries closer to the Equator: Autumn and Winter days are relatively shorter) and results in the Southern hemisphere are six months out of phase (as are the seasons there). This provides strong support for the thesis that we can indeed observe a significant and substantial SAD effect related to the seasonal variation in the length of day in the stock markets. 

Conclusion and Implications 

In summary, seasonal variation in the length of day translates into seasonal variation in equity returns. But how can this knowledge bring us any advantage? A smart investor could trade on this seasonal variation in equity returns: one can buy cheap stocks in September, when the SAD effect sets in and sell them for a much higher price in January or February when the SAD effect fades out and investors demand more stocks again, driving prices up. An even smarter investor could go a step further and do this twice a year: one time in the Northern hemisphere market, buying stocks in September and selling them in January, and one time in the Southern hemisphere market (whose SAD effect is shifted by 6 months with respect to the Norther hemisphere, as the seasons are shifted as well) buying stocks in March and selling them in July. Indeed Kamstra et al. show that such a strategy in the past would have yielded a substantial excess return in comparison to the overall market return. 

Sources 

Kamstra, M. J., Kramer, L. A., & Levi, M. D. (2003). Winter Blues: A SAD Stock Market Cycle. American Economic Review, 93(1), 324–343. https://doi.org/10.1257/000282803321455322 

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