Abstract
Stylized facts about statistical properties for short horizon returns in financial markets have been identified in the literature, but a satisfactory understanding for their manifestation is yet to be achieved. In this work, we show that a simple asset pricing model with representative agent is able to generate time series of returns that replicate such stylized facts if the risk aversion coefficient is allowed to change endogenously over time in response to unexpected excess returns under evolutionary forces. The same model, under constant risk aversion, would instead generate returns that are essentially Gaussian. We conclude that an endogenous time-varying risk aversion represents a very parsimonious way to make the model match real data on key statistical properties, and therefore deserves careful consideration from economists and practitioners alike.
Highlights
The statistical analysis of price variations in financial markets has attracted a lot of attention, both from practitioners and academic economists, in an attempt to find regularities that could help us understand and possibly predict the evolution of pricesM
Such extensive analysis has led to the identification of a number of statistical properties for financial returns that seem to hold across markets and over time, and that can be summarized in the following set of empirical stylized facts: i) the distribution of returns is not Gaussian but presents instead fat tails; ii) there is no serial correlation in returns; iii) there is positive correlation in absolute returns, with slow decay; iv) returns show strong volatility clustering, with large fluctuations that tend to cluster together
We suggest in this work that a common origin could be identified in the time-varying nature of the risk aversion coefficient for investors, and show that an otherwise standard, rational expectations asset pricing model, once enhanced with such a feature, can generate time series for returns that replicate very closely the main stylized facts identified in the empirical literature
Summary
The statistical analysis of price variations in financial markets has attracted a lot of attention, both from practitioners and academic economists, in an attempt to find regularities that could help us understand and possibly predict the evolution of prices. We suggest in this work that a common origin could be identified in the time-varying nature of the risk aversion coefficient for investors, and show that an otherwise standard, rational expectations asset pricing model, once enhanced with such a feature, can generate time series for returns that replicate very closely the main stylized facts identified in the empirical literature. An evolutionary justification for changes in attitudes towards risk is provided by Netzer (2009), who shows that, from an evolutionary perspective, the utility function of agents, and their risk aversion, should depend on the probability distribution of alternatives about which agents need to make decisions In our context, such alternatives are represented by returns from risky versus risk-free activities, and agents adapt their perceptions about the distribution of such alternatives using observations about unexpected excess returns on the stock market.
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