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Predictability and the cross section of expected returns: evidence from the European stock market

Author

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  • Wolfgang Drobetz

    (University of Hamburg)

  • Rebekka Haller

    (M.M.Warburg & CO)

  • Christian Jasperneite

    (M.M.Warburg & CO)

  • Tizian Otto

    (University of Hamburg)

Abstract

This paper examines the cross-sectional properties of stock return forecasts based on Fama–MacBeth regressions using all firms contained in the STOXX Europe 600 index during the September 1999–December 2018 period. Our estimation approach is strictly out of sample, mimicking an investor who exploits both historical and real-time information on multiple firm characteristics to predict returns. The models capture a substantial amount of the cross-sectional variation in true expected returns and generate predictive slopes close to one, i.e., the forecast dispersion mostly reflects cross-sectional variation in true expected returns. The return predictions translate into high value added for investors. For an active trading strategy, we find strong market outperformance net of transaction costs based on a variety of performance measures.

Suggested Citation

  • Wolfgang Drobetz & Rebekka Haller & Christian Jasperneite & Tizian Otto, 2019. "Predictability and the cross section of expected returns: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 508-533, December.
    • Handle: RePEc:pal:assmgt:v:20:y:2019:i:7:d:10.1057_s41260-019-00138-0
    DOI: 10.1057/s41260-019-00138-0
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    2. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
    3. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.

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    More about this item

    Keywords

    Characteristics-based asset pricing; Factor timing; Active trading strategy;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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