The Cross-Section of Stock Returns before 1926 (And Beyond)
85 Pages Posted: 24 Nov 2021 Last revised: 17 Mar 2022
Date Written: March 16, 2022
We study the cross-section of stock returns using a novel constructed database of U.S. stocks covering 61 years of additional and independent data. Our database contains data on stock prices, dividends and hand-collected market capitalizations for 1,488 major stocks between 1866-1926. Results over this ‘pre-CRSP’ era reveal a flat relation between market beta and returns, an insignificant size premium, and significant momentum, value, and low-risk premiums that are of similar size as over the post-1926 period. Overall, stock characteristics can explain over 25% of variation in stock returns. Further, recent machine learning methods are successful in predicting cross-sectional returns out-of-sample. These results show strong out-of-sample robustness of traditional factor models and novel machine learning methods.
Keywords: empirical asset pricing, return anomalies, machine learning, factor premiums, p-hacking, momentum, value, beta, low volatility, size
JEL Classification: G10, G11, N21, N22
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