|M.Sc Student||Gurevich Gregory|
|Subject||Decision-Making under Uncertainty - a Field Study|
|Department||Department of Industrial Engineering and Management||Supervisors||Professor Doron Kliger|
|Dr. Uri Levy|
The solution of various problems in economics, as well as in other social sciences, requires understanding of agents’ behavior under risk and uncertainty. Expected Utility Theory (EUT) served for this purpose for a long time as a normative model of rational choice. However, actual choices often exhibit systematic deviations from this widely accepted theory, as has been reported by a range of studies. To resolve this discrepancy, an alternative model, Cumulative Prospect Theory (CPT), was developed by Daniel Kahneman and Amos Tversky. The purpose of this descriptive model was to explain agents’ behavior in uncertain environments, which remained unexplained by EUT. The presented research tests the CPT using data from the US capital market. Specifically, data of options written on various firms’ stocks are used. Option prices supply the information about actual investors’ preferences, while an exploitation of conventional instruments of options analysis, along with empirically established theoretical relationships, made it possible to adjust the chosen data to a framework of the examined theory. The options data in this study serve for estimating the two essential elements of the CPT, namely, the value function and the Probability Weighting Function. The main part of the work focuses on the functions’ simultaneous estimation under the original parametric specifications. The obtained results are then analyzed. Qualitatively, the results support the central principles of the model: the shapes and the properties of the estimated functions are in line with the theory. Quantitatively, the estimated functions are both more linear in comparison to those acquired in laboratory experiments, and the utility function exhibites less loss aversion than was obtained in the laboratory.