Timing Prediction Error Volatility and Dynamic Asset Allocation

We solve a portfolio selection problem in which return predictability, risk predictability and transaction cost are incorporated. In the problem, both expected return, prediction error volatility, and transaction cost are time-varying. Our optimal strategy suggests trading partially toward a dynamic aim portfolio, which is a weighted average of expected future tangency portfolio and is highly influenced by the common fluctuation of prediction error volatility (CPE). When CPE is high, the investor would invest less and trade less frequently to avoid risk and transaction cost. Moreover, the investor trades more closely to the aim portfolio with a more persistent CPE signal. We also conduct an empirical analysis based on the commodities futures in Chinese market. The results reveal that by timing prediction error volatility, our strategy outperforms alternative strategies.