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Journal of Financial Economics Vol. 83 No. 1 2007

The empirical risk–return relation: A factor analysis approach☆

Sydney C. Ludvigson1; Serena Ng2

1 New York University · 2 University of Michigan–Ann Arbor

Abstract

Existing empirical literature on the risk–return relation uses relatively small amount of conditioning information to model the conditional mean and conditional volatility of excess stock market returns. We use dynamic factor analysis for large data sets, to summarize a large amount of economic information by few estimated factors, and find that three new factors—termed “volatility,” “risk premium,” and “real” factors—contain important information about one-quarter-ahead excess returns and volatility not contained in commonly used predictor variables. Our specifications predict 16–20% of the one-quarter-ahead variation in excess stock market returns, and exhibit stable and statistically significant out-of-sample forecasting power. We also find a positive conditional risk–return correlation.

DOI
10.1016/j.jfineco.2005.12.002
Volume
83
Issue
1
Pages
171-222
Language
en
Sources
openalex crossref bibtex:phds-export.bib

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