Long-term decision making in the presence of financial disasters

The research question focuses on three areas. First, what is the most appropriate model and estimation method for studying portfolio optimisation under tail risk with an aim towards managerial incentives. Second, how outcomes differ for investors who take jumps into account compared to those who do not. Third, how managerial incentives in the form of fees and compensation structures create a conflict of interest between investors and funds in the presence of jumps, leading to a need for policy suggestions. To answer those questions the thesis builds up from a CARA single-state model to an SV model to an SVCJ model with jumps in returns and volatility, leverage and heteroskedasticity. The model and its SV only counterpart are estimated via MCMC. A closed-form solution for the portfolio weights is derived and used in subsequent simulations. The results are that the investor always has an incentive to knowingly ignore tail risk in terms of wealth but never in terms of utility, the manager has an incentive in the short- and mid-run to undertake excess risk but not in the long-run, the criteria for the incentive horizon are risk aversion and how investor wealth moves between funds, and policy suggestions are made based on those grounds.