The empirical risk-return relation: A factor analysis approach

Sydney C. Ludvigson, Serena Ng

    Research output: Contribution to journalArticlepeer-review


    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.

    Original languageEnglish (US)
    Pages (from-to)171-222
    Number of pages52
    JournalJournal of Financial Economics
    Issue number1
    StatePublished - Jan 2007


    • Expected returns
    • Sharpe ratio
    • Stock market volatility

    ASJC Scopus subject areas

    • Accounting
    • Finance
    • Economics and Econometrics
    • Strategy and Management


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