Estimating the Probability Weighting Function used in non-Expected Utility Theory: A case study of mutual fund managers
This dissertation investigates the Probability Weighting Function (PWF), a determinant of individual choice behavior and a key aspect of non Expected Utility Theories (EUT). We focus on mutual fund managers as decision makers and their holdings as reflections of their decisions. In this study we argue that it is possible to improve our understanding and practice of decision making by estimating ex post the parameters of the PWF implied by investors' choices. The methodology we used in eliciting the PWF applies concepts from stochastic dominance theory to make the connection between the consequences of managers' decisions and the PWF. ^ A novel contribution of this dissertation is the elicitation of the PWF parameters within Cumulative Prospect Theory in a real world scenario, specifically concentrating on mutual fund managers' decisions regarding their portfolio holdings. We introduce four innovative methods for determining the PWF parameters. ^ Our conclusions lend support to the hypothesis that probabilities are not treated linearly as in EUT, but rather are transformed by a PWF. A second important result is that there is a high degree of variation in the parameter values obtained at the individual manager level. The average results across all managers are broadly consistent with previous elicitations of parameters done in an experimental fashion. Finally, we find evidence that a two-parameter PWF is a better fit than a one-parameter PWF for describing the weighting of probabilities. In conclusion, our approach is able to unveil the attitudes toward probabilities and risk for a particular investment strategy. ^ As a result, clients can form opinions about whether that strategy is consistent with their own investment philosophy, and whether a manager is suitable for their investments. Also, we provide theorists and finance professionals additional tools for analyzing decision-making and possibly for developing better descriptive and predictive models for investment decisions. ^
Rudean, Diana Ramona, "Estimating the Probability Weighting Function used in non-Expected Utility Theory: A case study of mutual fund managers" (2009). ETD Collection for Fordham University. AAI3377054.