The Low-Risk Effect in Equities: Evidence from Industry Data in an Earlier Time

C. Mitchell Conover, Joseph D. Farizo and Andrew C. Szakmary

Financial Analysts Journal, 2023, vol. 79, issue 2, 98-119

Abstract: Recently, there has been discussion of a “replication crisis” in Finance, where many empirical results in financial research are said not to be replicable. Previous research finds that low-risk stocks have higher returns than higher-risk stocks on a risk-adjusted basis. We reexamine the low-risk effect using a unique dataset for U.S. industries from 1871 to 1925. We confirm the presence of the effect for portfolios of U.S. industries, indicating that the low-risk effect is not due to data mining in previous studies. Comparing the results to that for more recent data, we find that the overall effect is at least as strong in the earlier data. Given that some market frictions were fewer in the earlier period, the results suggest that implicit trading costs, illiquidity, and/or behavioral biases may play an important role in the low-risk effect.

Date: 2023
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DOI: 10.1080/0015198X.2022.2158709

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