Predicting Stock Market Returns with Aggregate Discretionary Accruals

Journal of Accounting Research, Forthcoming

52 Pages Posted: 9 Mar 2010

See all articles by Qiang Kang

Qiang Kang

Florida International University (FIU) - Department of Finance

Qiao Liu

The University of Hong Kong - School of Economics and Finance; Peking University - Guanghua School of Management

Rong Qi

St. John's University

Multiple version iconThere are 2 versions of this paper

Date Written: January 8, 2010

Abstract

We find that the positive relation between aggregate accruals and one-year-ahead market returns documented in Hirshleifer, Hou and Teoh [2009] is driven by discretionary accruals but not normal accruals. The return forecasting power of aggregate discretionary accruals is robust to choices of sample periods, return measurements, estimation methods, business condition and risk premium proxies, and accrual models used to isolate discretionary accruals. Our extensive analysis shows that aggregate discretionary accruals, in sharp contrast to aggregate normal accruals, contain little information about overall business conditions or aggregate cash flows and display little co-movement with ICAPM-motivated risk premium proxies. Our findings imply that aggregate discretionary accruals likely reflect aggregate fluctuations in earnings management, thereby favoring the behavioral explanation that managers time aggregate equity markets to report earnings.

Keywords: Aggregate Discretionary Accruals, Return Predictive Regressions, ICAPM-Motivated Risk Premium Proxies, Managerial Market Timing

JEL Classification: G10, M40

Suggested Citation

Kang, Qiang and Liu, Qiao and Qi, Rong, Predicting Stock Market Returns with Aggregate Discretionary Accruals (January 8, 2010). Journal of Accounting Research, Forthcoming. Available at SSRN: https://ssrn.com/abstract=1567012

Qiang Kang (Contact Author)

Florida International University (FIU) - Department of Finance ( email )

University Park
11200 SW 8th Street
Miami, FL 33199
United States

Qiao Liu

The University of Hong Kong - School of Economics and Finance ( email )

School of Economics and Finance
Pokfulam
Hong Kong
Hong Kong
852-2859-1059 (Phone)
852-2548-1152 (Fax)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

Rong Qi

St. John's University ( email )

8000 Utopia Parkway
Queens, NY 11439
United States

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