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The value of expected return persistence

Author

Listed:
  • Wolfgang Schadner

    (University of Innsbruck
    University of St. Gallen)

  • Sebastian Lang

    (University of St. Gallen
    Berufliche Hochschule Hamburg)

Abstract

This work utilizes the fractional Black–Scholes model to estimate the option-implied Hurst exponents, interpreted as forward-looking expectations of return persistence. The focus of the paper is on how corresponding believes enter into factor based asset pricing models. Empirical analyses are carried out for the cross-section of S &P 500 stocks. We make the important observations that (i) stock returns show significant patterns of time-varying persistence and (ii) corresponding believes are reflected within option prices. Incorporating the Hurst exponents allows us to split up CAPM betas into pure market correlation risk (around 70–80%) and into excess persistence believes (about 20–30% of the risk loading). A direct comparison to standard CAPM shows that incorporating persistence believes significantly improves the predictability of future realized returns, and partially releases the beta anomaly. The effects become even stronger the greater the prediction horizon. Hence, the concept of fractal motions enables a deeper understanding of risk structures without the need of additional risk factors.

Suggested Citation

  • Wolfgang Schadner & Sebastian Lang, 2023. "The value of expected return persistence," Annals of Finance, Springer, vol. 19(4), pages 449-476, December.
    • Handle: RePEc:kap:annfin:v:19:y:2023:i:4:d:10.1007_s10436-023-00428-z
    DOI: 10.1007/s10436-023-00428-z
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    References listed on IDEAS

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    More about this item

    Keywords

    Return persistence; Implied volatility; Fractal Brownian motion; Long range memory;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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