Predicting corporate policies using downside risk: A machine learning approach

Doron Avramov, Minwen Li and Hao Wang

Journal of Empirical Finance, 2021, vol. 63, issue C, 1-26

Abstract: This paper develops a text-based downside risk measure using corporate annual reports and assesses its ability to forecast future corporate policies. The forward-looking measure dynamically captures adverse firm conditions evolving from economic fundamentals. When the measure is below its sample average, leverage, investment, R&D, employment, and dividends consistently fall. When the measure rises, firms increase cash holdings. The proposed measure also delivers robust and persistent forecasts based on in-sample and out-of-sample LASSO regressions.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:63:y:2021:i:c:p:1-26

DOI: 10.1016/j.jempfin.2021.04.009

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