Using Stocks or Portfolios in Tests of Factor Models

Autor:	Andrew Ang, Jun Liu, Krista Schwarz
Rok vydání:	2019
Předmět:	Economics and Econometrics 050208 finance Risk premium 05 social sciences Standard error Accounting 0502 economics and business Econometrics Capital asset pricing model Portfolio Statistical dispersion 050207 economics Volatility (finance) Beta (finance) Finance Factor analysis Mathematics
Zdroj:	Journal of Financial and Quantitative Analysis. 55:709-750
ISSN:	1756-6916 0022-1090
DOI:	10.1017/s0022109019000255
Popis:	We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.
Databáze:	OpenAIRE
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