Abstract
Optimizing over power-log utility functions allow for the inclusion of downside loss aversion, a broader range of investor preferences, and account for higher-order moments like skewness and kurtosis in the optimization process. We implement multi-period power-log optimization (PLO) with annual rebalancing on a portfolio consisting of a treasury security, the S&P500 index and a call option on the index. PLO results in higher geometric average realized returns with lower tail risk, and lower standard deviation than meanvariance efficient portfolios with the same ex-ante expected returns. It also provides better downside protection against large, negative return surprises, such as the down markets in 2002 and 2008.
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