Taming models of prospect theory in the wild? : estimation of Vlcek and Hens (2011)

Shortcomings revealed by experimental and theoretical researchers such as Allais (1953), Rabin (2000) and Rabin and Thaler (2001) that put the classical expected utility paradigm von Neumann and Morgenstern (1947) into question, led to the proposition of alternative and generalized utility func- tions, that intend to improve descriptive accuracy. The perhaps best known among those alternative preference theories, that has attracted much popu- larity among economists, is the so called prospect theory by Kahneman and Tversky (1979) and Tversky and Kahneman (1992). Its distinctive features, governed by its set of risk parameters such as risk sensitivity, loss aversion and decision weights, stimulated a series of economic and financial models that build on the previously estimated parameter values by Tversky and Kahne- man (1992) to analyze and explain various empirical phenomena for which expected utility does not seem to offer a satisfying rationale. In this paper, after providing a brief overview of the relevant literature, we take a closer look at one of those papers, the trading model of Vlcek and Hens (2011) and analyze its implications on prospect theory parameters using an adopted max- imum likelihood approach for a dataset of 656 individual investors from a large German discount brokerage firm. In contrast to existing literature, we find ev- idence that investors in our dataset are only moderately averse to large losses and display high risk sensitivity, supporting the main assumptions of prospect theory. Illustrating simulations show that, for those investors, who can be characterized by these parameter estimates, realized returns and roundtrip length statistically resembles those in our dataset.