Pure Factor Portfolios and Multivariate Regression Analysis

Linking factor portfolio construction to cross-sectional regressions of security returns on standardized factor exposures leads to a transparent and investable perspective on factor performance. Under capitalization weighting, multivariate regression coefficients translate to portfolio returns that...

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Bibliographic Details
Published inJournal of portfolio management Vol. 43; no. 3; p. 16
Main Authors Clarke, Roger, de Silva, Harindra, Thorley, Steven
Format Journal Article
LanguageEnglish
Published London Pageant Media 01.04.2017
Subjects
Earnings per share
Equity
Interest rates
Portfolio management
Profits
Regression analysis
Stock exchanges
Stocks
Valuation
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Summary:Linking factor portfolio construction to cross-sectional regressions of security returns on standardized factor exposures leads to a transparent and investable perspective on factor performance. Under capitalization weighting, multivariate regression coefficients translate to portfolio returns that are benchmark relative and cleared of secondary factor exposures. The methodological contributions in this article are illustrated using a 50-year data set of 1,000 large U.S. stocks and five factor exposures: value, momentum, small size, low beta, and profitability. Using two case studies in factor portfolio analysis, the authors focus on cheapness, as measured by earnings yield, and interest rate risk, as measured by sensitivity to the 10-year Treasury bond return.
ISSN:0095-4918
2168-8656
DOI:10.3905/jpm.2017.43.3.016