The Influence of Dynamic Risk Aversion in the Optimal Portfolio Context

Despite the influence of risk aversion in the optimal portfolio context, there are not many studies which have explicitly estimated the risk aversion parameter. Instead of that, researchers almost always choose random fixed values to reflect the common levels of risk aversion. However, the above could generate optimal portfolios, which do not reflect the actual investor’s attitude towards risk. Otherwise, as it is well known, an individual is more or less risk averse according to the economic and political circumstances. Given the above, we model the risk aversion attitude so that it changes over time, in order to take into account the variability in agents’ expectations. Therefore, the aim of this paper is to shed light on the choice of the risk aversion parameter that correctly represents the investors’ behaviour. For that purpose, we build optimal portfolios for different types of investment profiles in order to compare whether it is better to use a constant risk aversion parameter or a dynamic one. In particular, our proposal is based on estimating the time-varying risk aversion parameter as a derivation of the market risk premium. For that purpose, we implement several statistical univariate and multivariate models. Specifically, we use conditional variance and correlation models, such as GARCH (1, 1), GARCH-M (1, 1) and DCC-GARCH.