|
|
Predicting Stock Returns Using Industry-Relative Firm Characteristics
Summary
Better proxies for the information about future returns contained in firm characteristics such as size, book-to-market equity, cash flow-to-price, 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. In particular, and contrary to Moskowitz and Grinblatt [1999], we find that within-industry momentum 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 even when we restrict the sample to only the most liquid firms. Our decomposition of one month past return strategies into within-industry and across-industry effects, and the understanding this brings to the one-year momentum effect, expands our understanding of the time-series properties of stock returns in an important way.
If you wish to have a copy of this paper, please provide the following information
Predicting Stock Returns Using Industry-Relative Firm Characteristics
|
|
