Essays on Prospect Theory and the Statistical Modeling of Financial Returns

Sammanfattning: This thesis consists of three self-contained essaysEssay 1 presents an empirical study of volatility spillover from oil prices to stock markets within an asymmetric BEKK model. Using weekly data on the aggregate stock markets of Japan, Norway, Sweden, the U.K., and the U.S., strong evidence of volatility spillover is found for all stock markets but the Swedish one, where only weak evidence is found. News impact surfaces show that, although statistically significant, the volatility spillovers are quantitatively small. The stock markets’ own shocks, which are related to other factors of uncertainty than the oil price, are more prominent than oil shocks.Essay 2 replicates the study of Benartzi and Thaler (1995), who suggest a behavioral explanation to the equity premium puzzle by myopic loss aversion. A technical extension to their methodology is suggested where conditional heteroskedasticity is incorporated when simulating returns, in place of the original temporal independence assumption. Swedish data is considered in addition to U.S. data. First, it is found that myopic loss aversion can explain the U.S. equity premium over bonds, although the obtained evaluation periods are somewhat shorter than a year. For example, over the full U.S. sample period from 1926 to 2003, evaluation periods of seven and ten months are found using the original and new approach to simulating returns, respectively. Second, myopic loss aversion suggestively explains the Swedish equity premium as well, which is new to the literature. Third, throughout the analysis of both data sets, longer evaluation periods are obtained under conditional heteroskedasticity. The last result indicates that myopic loss-averse and, in turn, cumulative prospect theory investors are sensitive to the distributional assumption made on returns.Essay 3 relates cumulative prospect theory to the moments of returns distributions, e.g. skewness and kurtosis, assuming returns are normal inverse Gaussian distributed. The normal inverse Gaussian distribution parameterizes the first- to fourth-order moments, making the investigation straightforward. Cumulative prospect theory utility is found to be positively related to the skewness. However, the relation is negative when probability weighting is aside. This shows that cumulative prospect theory investors display a preference for skewness through the probability weighting function. Furthermore, the investor’s utility is inverse hump-shape related to the kurtosis. Consequences for portfolio choice issues are studied. The findings, among others, suggest that optimal cumulative prospect theory portfolios are not mean-variance efficient under the normal inverse Gaussian distribution.