Power-Log Portfolio Optimization for Managing Downside Risk

This research paper tests the effectiveness of Power-Log
optimization for managing the downside risk of investment
portfolios. It uses Power-Log utility functions, which are based
on tenets of behavioral finance, to give investors the ability to
build downside protection directly into a portfolio. Comparing
optimal Power-Log portfolios with matched mean-variance
efficient portfolios, we find that the optimal Power-Log portfolios
have lower downside risk, while delivering higher geometric
average return. They also provide much better downside
protection against unanticipated market shocks, such as the
one in 2008, in contrast to the disastrous performance for
matched mean-variance efficient portfolios. Power-Log
optimization succeeds in managing downside risk effectively,
while mean variance analysis fails to protect investors from
such risk.

JEL Codes: G11

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