Downside Loss Aversion and Portfolio Growth

Jivendra Kale, Arnav Sheth

Research output: Contribution to journalArticlepeer-review


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.

Original languageAmerican English
JournalJournal of Finance and Bank Management
StatePublished - Jun 1 2015


  • Business
  • Economics

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