Predicting Stock Returns Using Industry-Relative Firm Characteristics

46 Pages Posted: 5 Jul 2000

See all articles by Clifford S. Asness

Clifford S. Asness

AQR Capital Management, LLC

R. Burt Porter

Iowa State University

Ross L. Stevens

Date Written: February 24, 2000


Better proxies for the information about future returns contained in firm characteristics such as size, book-to-market equity, cash flow-to-price, percent change in employees, and various past return measures are obtained by breaking these explanatory variables into two industry-related components. The components represent (1) the difference between firms' own characteristics and the average characteristics of their industries (within-industry variables), and (2) the average characteristics of firms' industries (across-industry variables). Each variable is reliably priced within-industry and measuring the variables within-industry produces more precise estimates than measuring the variables in their more common form. Contrary to Moskowitz and Grinblatt [1999], we find that within-industry momentum (i.e., the firm's past return less the industry average return) has predictive power for the firm's stock return beyond that captured by across-industry momentum. We also document a significant short-term (one-month) industry momentum effect which remains strongly significant when we restrict the sample to only the most liquid firms.

JEL Classification: G11, G12

Suggested Citation

Asness, Cliff S. and Porter, R. Burt and Stevens, Ross L., Predicting Stock Returns Using Industry-Relative Firm Characteristics (February 24, 2000). Available at SSRN: or

Cliff S. Asness

AQR Capital Management, LLC ( email )

Two Greenwich Plaza, 3rd Floor
Greenwich, CT 06830
United States
203-742-3601 (Phone)
203-742-3101 (Fax)


R. Burt Porter (Contact Author)

Iowa State University ( email )

College of Business
3345 Gerdin Business Bldg
Ames, IA 50011-2063
United States
515-294-2612 (Phone)

Ross L. Stevens

50 East 13th Street
New York, NY 10003
United States

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