Predicting Firm Profits: From Fama-MacBeth to Gradient Boosting

64 Pages Posted: 10 Sep 2021

See all articles by Murray Z. Frank

Murray Z. Frank

University of Minnesota

Keer Yang

University of California, Davis - Graduate School of Management

Date Written: September 7, 2021

Abstract

This paper studies the predictability of firm profits using Fama-MacBeth regressions and gradient boosting. Gradient boosting can use more relevant factors and it predicts better. Profits are more predictable at firms that are large, investment grade, low R&D, low market-to-book, low cash flow volatility. Effects on financing decisions, and cross-section of stock returns are studied. During recessions profits are less predictable - particularly non-investment grade firms. Both algorithms produce estimates like those interpreted in the literature as evidence of excessive human optimism during booms and excessive pessimism during recessions.

Keywords: Expected profit, Fama-MacBeth, gradient boosting, firm financing decisions, cross-section of stock returns, behavioral finance

JEL Classification: G17, G32, G40

Suggested Citation

Frank, Murray Z. and Yang, Keer, Predicting Firm Profits: From Fama-MacBeth to Gradient Boosting (September 7, 2021). Available at SSRN: https://ssrn.com/abstract=3919194 or http://dx.doi.org/10.2139/ssrn.3919194

Murray Z. Frank (Contact Author)

University of Minnesota ( email )

Carlson School of Management
321 19th Avenue South
Minneapolis, MN 55455
United States
612-625-5678 (Phone)

Keer Yang

University of California, Davis - Graduate School of Management ( email )

One Shields Avenue
Davis, CA 95616
United States

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