Forecasting betas with random forests

Emmanuel Alanis

Applied Economics Letters, 2022, vol. 29, issue 12, 1134-1138

Abstract: It is common to estimate equity betas for private firms or non-traded assets through a comparable company analysis, and we test if the Random Forest algorithm can provide superior forecasts. In out-of-sample tests from 1992 to 2018, we find that Random Forest forecasts produce substantially lower average errors and mean absolute errors every year.

Date: 2022
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DOI: 10.1080/13504851.2021.1912278

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