Abstract

The title of this thesis is Conditional Value at Risk Asset Allocation, A Copula Based Method, and it is written by Hamed Naeini. The thesis supervisor is Professor Thomas J. Walker. Using a non-parametric bootstrapping method, we allocate funds to eleven preselected asset classes based on a series of conditional value at risk and variance criteria. Next, we employ copulas to model the data and build our comparison portfolios. We compare the results of the two methods during both bull and bear markets conditions. We find that model-based asset allocation significantly improves the performance of portfolios during financial crises. Under normal market conditions, the two methods result in comparable performance. We conclude that our optimization procedure provides asset allocation strategies that result in portfolios that perform at least as well as portfolios constructed based on the commonly used bootstrapping method and significantly better during periods of financial turmoil.