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Anomaly Predictability with the Mean-Variance Portfolio

Author

Listed:
  • Favero, Carlo A.

    (Bocconi U)

  • Melone, Alessandro

    (Ohio State U)

  • Tamoni, Andrea

    (Rutgers U)

Abstract

According to a no-arbitrage condition, risk-adjusted returns should be unpredictable. Using several prominent factor models and a large cross-section of anomalies, we find that past cumulative risk-adjusted returns predict future anomaly returns. Cumulative returns can be interpreted as deviations of an anomaly price from the price of the mean-variance efficient portfolio. Price deviations constitute a novel anomaly-specific predictor, endogenous to the given heuristic mean-variance portfolio, thus providing direct evidence for conditional misspecification. A zero-cost investment strategy using price deviations generates positive alphas. Our findings suggest that incorporating price information into cross-sectional models improves their ability to capture time-series return dynamics.

Suggested Citation

  • Favero, Carlo A. & Melone, Alessandro & Tamoni, Andrea, 2023. "Anomaly Predictability with the Mean-Variance Portfolio," Working Paper Series 2023-20, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    • Handle: RePEc:ecl:ohidic:2023-20
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    More about this item

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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