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On Empirical Challenges in Forecasting Market Betas in Crypto Markets

Author

Listed:
  • Jan Sila

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University & The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic)

  • Michael Mark

    (Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland)

  • Ladislav Kristoufek

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University & The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic)

Abstract

This paper investigates the predictability of market betas for crypto assets. The market beta is the optimal weight of a short position in a simple two-asset portfolio hedging the market risk. Investors are therefore keen to forecast the market beta accurately. Estimating the market beta is a fundamental financial problem and we document pervasive empirical issues that arise in the emerging market of crypto assets. Although recent empirical results about US stocks suggest predictability of the future realized betas about 55%, predictability for the universe of crypto assets is at most 20%. Our results suggest that the crypto market betas are highly sensitive not only to the beta estimation method but also to the selection of the market index. Thus we also contribute to the discussion on the appropriate market representation.

Suggested Citation

  • Jan Sila & Michael Mark & Ladislav Kristoufek, 2022. "On Empirical Challenges in Forecasting Market Betas in Crypto Markets," Working Papers IES 2022/19, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2022.
    • Handle: RePEc:fau:wpaper:wp2022_19
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    File URL: https://ies.fsv.cuni.cz/en/veda-vyzkum/working-papers/6650
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    More about this item

    Keywords

    C21; C53; C58; G12;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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