On the Expected Earnings Hypothesis Explanation of the Aggregate Returns-Earnings Association Puzzle

Forthcoming Journal of Financial and Quantitative Analysis

52 Pages Posted: 3 Jan 2019 Last revised: 16 Aug 2019

See all articles by Warren Bailey

Warren Bailey

Cornell University; Fudan University - Fanhai International School of Finance and China Institute of Economics and Finance

Huiwen Lai

Hong Kong Polytechnic University

Date Written: August 13, 2019

Abstract

We provide strong support for the underappreciated expected earnings hypothesis of negative correlation between aggregate stock returns and earnings (Sadka and Sadka (2009); Choi, Kalay, and Sadka (2016)). For the 1970 to 2000 period studied by Kothari, Lewellen, and Warner (2006), our powerful modeling strategy incorporating macroeconomic information reveals that aggregate returns are significantly negatively correlated with expected aggregate earnings changes but uncorrelated with unexpected aggregate earnings changes. However, this negative correlation changes after 2000, perhaps from heightened volatility or accounting changes. We also show that underlying macroeconomic information explains the power of aggregate earnings to predict future GDP growth.

Keywords: aggregate returns-earnings association, return news hypothesis, expected earnings hypothesis, earnings predictability, macroeconomic forecasting

JEL Classification: E32, G12, G14, M41

Suggested Citation

Bailey, Warren B. and Lai, Huiwen, On the Expected Earnings Hypothesis Explanation of the Aggregate Returns-Earnings Association Puzzle (August 13, 2019). Forthcoming Journal of Financial and Quantitative Analysis, Available at SSRN: https://ssrn.com/abstract=3303227 or http://dx.doi.org/10.2139/ssrn.3303227

Warren B. Bailey (Contact Author)

Cornell University ( email )

S. C. Johnson Graduate School of Management
387 Sage Hall
Ithaca, NY 14853-6201
United States
607-255-4627 (Phone)
607-254-4590 (Fax)

HOME PAGE: http://courses.cit.cornell.edu/wbb1/

Fudan University - Fanhai International School of Finance and China Institute of Economics and Finance ( email )

China

Huiwen Lai

Hong Kong Polytechnic University ( email )

Hung Hom, Kowloon
Hong Kong

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