Dynamic Portfolio Analysis Based on Realized Higher Moments

Realized higher moments, which are the expansion of realized volatility in high-frequency time series, is proposed in the paper to measure the time-varying financial risk. The dynamic assets allocation is settled by Taylor series expansion of utility function. We apply realized higher moments to portfolio analysis, and derive dynamic portfolio strategy. Our model repair two defects in traditional portfolio theory, without considering higher moments risk and settle problem statically. High frequency financial data in Chinese stock markets are selected to make empirical research. The empirical results show that higher moments risk possess volatility cluster, and dynamic portfolio is obviously superior to static portfolio.