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Behavioral Portfolio Choice and Disappointment Aversion: An Analytical Solution with “Small” Risks

  • Enrico SaltariEmail author
  • Giuseppe Travaglini
Chapter

Abstract

The standard portfolio model based on expected utility (EU) theory predicts a large equity position for most households. Empirical analysis demonstrates, however, that the composition of household’s wealth is characterized by a small proportion of risky assets. A consolidated empirical literature providesmeasures of these financial phenomena (Brandolini et al., 2004; Faiella and Neri, 2004; Giannetti and Koskinen, 2009; Heaton and Lucas, 1996; Mankiw and Zeldes, 1991; Guiso and Zingales unpublished). For instance, in Italy over the period 1965–2006 the percentage of stocks held by households has been on average 9% of the total wealth. Similar proportions can be found in the portfolio of families in United States, France, Germany and Great Britain.

The puzzling aspect of these data is that the excess return on equities – a measure of the risk premium – has been often positive and even large. Dimson et al. (2002) illustrate that during the twentieth century it was around 6% in United States, Germany and Great Britain. This return was even higher and close to 7% in Italy and France. Similar rates of return are computed by Mehra and Prescott (1985, 2003) and Campbell (2003) over the same period for the main industrialized countries.

Loosely speaking the puzzle is the following. Given that equities yield such a high risk premium, why do households buy so few stocks? Almost all calibrated version of dynamic portfolio choice models with standard preferences (even when augmented with other important ingredients like transaction costs or borrowing constraints) fail in replicating the previous basic facts. Indeed, given plausible estimated stochastic processes for stock market returns, an implausibly high risk aversion is needed to keep the investors away from stocks.

Keywords

Risk Aversion Risk Premium Expect Utility Risky Asset Excess Return 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of Public EconomicsUniversity of Rome, “La Sapienza”RomeItaly

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