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Crypto market betas: the limits of predictability and hedging

Author

Listed:
  • Jan Sila

    (Charles University
    Czech Academy of Sciences)

  • Michael Mark
  • Ladislav Kristoufek

    (Charles University
    Czech Academy of Sciences)

  • Thomas A. Weber

    (École Polytechnique Fédérale de Lausanne)

Abstract

This article analyzes the predictability of market betas concerning cryptocurrency assets and evaluates the efficiency of beta-hedged, market-neutral portfolios. We forecast 1-year-ahead market betas using various estimating methods, including ordinary least squares (OLS) and Vasicek’s Bayesian shrinkage estimator, and assess their impact on portfolio variance reduction across cryptomarket indices. Our findings indicate that while standard OLS betas explain significantly less of the variation in future betas for cryptoassets compared to US stocks, slope winsorization and Bayesian shrinkage improve prediction accuracy. The results suggest that beta-hedged portfolios reduce variance for approximately 17% of the universe, with the Broad Digital Market Index demonstrating the best hedging efficiency. These findings underscore the significant challenges of developing effective hedging strategies in the cryptocurrency market, emphasizing the importance of idiosyncratic risk in crypto returns and the need for appropriate market index representation.

Suggested Citation

  • Jan Sila & Michael Mark & Ladislav Kristoufek & Thomas A. Weber, 2025. "Crypto market betas: the limits of predictability and hedging," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-28, December.
    • Handle: RePEc:spr:fininn:v:11:y:2025:i:1:d:10.1186_s40854-025-00777-w
    DOI: 10.1186/s40854-025-00777-w
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    More about this item

    Keywords

    Asset pricing; Market beta; Cryptocurrency; Crypto; Market risk; CAPM; Bitcoin; Beta-hedging;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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