Avoiding momentum crashes using stochastic mean-CVaR optimization with time-varying risk aversion

Xiaoshi Guo and Sarah M. Ryan

The Engineering Economist, 2023, vol. 68, issue 3, 125-152

Abstract: In occasions called momentum crashes, the usually effective cross-sectional momentum strategy for financial asset allocation produces drastically negative returns. We develop a stochastic mean-risk optimization model featuring CVaR to control the risk, dynamically adjusted CVaR tail probability and objective function weight, and return scenarios generated by hybrid moment-matching. In a 95-year backtest, portfolios rebalanced by our method provide higher returns and lower risk than those rebalanced by a cross-sectional momentum heuristic, while avoiding momentum crashes.

Date: 2023
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DOI: 10.1080/0013791X.2023.2229620

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