TY - JOUR
T1 - The empirical risk-return relation
T2 - A factor analysis approach
AU - Ludvigson, Sydney C.
AU - Ng, Serena
N1 - Funding Information:
Ludvigson acknowledges financial support from the Alfred P. Sloan Foundation and the CV Starr Center at NYU. Ng acknowledges financial support from the National Science Foundation (SES-0345237). We thank G. William Schwert (the editor) and an anonymous referee for helpful comments, Kenneth French for providing the portfolio data, and Massimiliano Croce for excellent research assistance. Any errors or omissions are the responsibility of the authors.
Copyright:
Copyright 2006 Elsevier B.V., All rights reserved.
PY - 2007/1
Y1 - 2007/1
N2 - 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.
AB - 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.
KW - Expected returns
KW - Sharpe ratio
KW - Stock market volatility
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U2 - 10.1016/j.jfineco.2005.12.002
DO - 10.1016/j.jfineco.2005.12.002
M3 - Article
AN - SCOPUS:33845316866
SN - 0304-405X
VL - 83
SP - 171
EP - 222
JO - Journal of Financial Economics
JF - Journal of Financial Economics
IS - 1
ER -