Dynamic asset allocation with jump risk

ABSTRACT Major events often trigger large jumps in stock prices and volatility. Previous studies on the implications of jumps in prices and volatility for optimal portfolio choice were based on utility functions; however, since this approach describes the risk in an indirect way, it is rarely adopted in practice. Using the stochastic volatility with jump models (Bakshi et al (1997); Bates (2000)) and the stochastic volatility with correlated jump models (Duffie et al (2000)), we develop a hybrid simulation tree stochastic programming model to investigate the effects of jumps in prices and volatility on optimal portfolio choice. Our empirical results show that jumps in the prices and in the volatility will both have important effects on the optimal portfolio choice.