Any theory of individual choice faces a challenge – can it be applied more generally, in aggregate, while still describing the world well? In economics, expected utility can be aggregated into the Capital Asset Pricing Model (CAPM), a model that aims to account for the relationship between the risk and return of financial assets. The model has a number of weaknesses, including its handling of extreme (tail) events and the inconsistency of results through time. Does accommodating behavioural considerations make for a better pricing model?
Prospect theory suggests that as individuals we seek out stocks that have a small chance of a large return, in an attempt to find the next big winner. In a number of studies, the evidence has supported the theory.2 Investors do seem to care about the tendency of an asset either to have a tail of more positive returns or of more negative returns (skewness). Therefore, including these preferences in a CAPM-style model can improve the model’s performance under certain assumptions.
The equity premium puzzle3 is another part of the finance landscape that has been subjected to the behavioural lens. The puzzle is that investors generally demand a higher return for investing in risky equities over safer bonds; this excess is higher than conventional economic theory would suggest. Prospect theory helps – because investors’ loss aversion combines with myopia.4
Take Bob, an imaginary investor. Bob checks the performance of his portfolio several times a week. This regular checking means he sees more volatility, up and down. Like most people, Bob feels losses more keenly than gains of the same size. Over time, a sort of emotional deficit builds up: for an equal number of gains and losses, the losses hurt more. For this reason, Bob demands a larger-than-predicted equity premium.
While a behavioural angle provides some appealing solutions to market conundrums, there are shortcomings.5 There is also the danger we create our own Just So stories of how the world works – extrapolating observed or postulated behaviours and assuming investors behave in a certain way all the time. Are we using our stories to explain away consequential features of finance and markets?
Consider the battered world of the short-volatility exchange-traded fund. In effect, these products were a bet the market would keep going up smoothly. They stood to do well for as long as this was the case. They also stood to suffer badly if markets fell. In the jargon, their return profile had a highly negative skew – a tendency to produce gains, punctuated by infrequent but sizeable losses. In an era of steady equity returns and rock-bottom interest rates, this return profile proved irresistible. Retail investors piled into the products, chasing the momentum of positive gains. This all ended in tears in February 2018: volatility spiked, the negative skew showed the sting in its tail, and short-volatility products lost most or all of their value.
This buying behaviour arguably went against one of the key findings of prospect theory. Investors were buying an asset experiencing healthy gains, participating in a momentum trade. Instead of selling winners – as per the original findings – investors were chasing winners.
What is clear is that investor behaviour is far from consistent over time and under different conditions. There is always potential for a tweak to be made to a model’s preference curve or reference point, but the hallmark of an enduring model is that its foundations don’t need to be altered to cope with differing environments. The path of time shouldn’t change our fundamental description of the markets.