The Devil Is in the Details: The Risks Often Ignored in Low-Volatility Investing

Published in The Journal of Portfolio Management, July 2020.

Executive summary

Low-volatility equity has drawn heavy inflows, but implementation choices matter. Building on an earlier analytical comparison of construction methods, this paper tests empirical differences across common low-volatility approaches. Optimizer-based minimum-variance portfolios are highly sensitive to risk-model inputs: small changes in covariance or volatility estimates can produce large shifts in sector weights, stock positions, and factor exposures, with meaningful performance consequences.

Investors should treat input stability as a first-class requirement, not an afterthought. Risk-balancing approaches can capture the low-volatility premium with far less sensitivity to model assumptions. The core message is that the anomaly is real, but naive optimization can leave an investor with a different portfolio than they think they bought.

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