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Risk aversion and Bitcoin returns in extreme quantiles

Author

Listed:
  • Elie Bouri

    (School of Business, Lebanese American University, Lebanon)

  • Rangan Gupta

    (University of Pretoria)

  • Chi keung marco Lau

    (University of Huddersfield)

  • David Roubaud

    (Montpellier Business School)

Abstract

We study whether level of risk aversion can be used to predict Bitcoin returns using copulas and quantile-based models. We find evidence of predictability when the market return is at extreme quantiles. Further analyses show that the cross-quantilogram is similar when risk aversion is at the low or medium level for various quantiles of Bitcoin returns. The predictability is positive when the risk aversion is at very low level. However, predictability becomes negative when both the risk aversion and Bitcoin returns are very high, suggesting that when risk aversion and Bitcoin returns are at very high levels, Bitcoin is less likely to have large gains.

Suggested Citation

  • Elie Bouri & Rangan Gupta & Chi keung marco Lau & David Roubaud, 2021. "Risk aversion and Bitcoin returns in extreme quantiles," Economics Bulletin, AccessEcon, vol. 41(3), pages 1374-1386.
    • Handle: RePEc:ebl:ecbull:eb-21-00863
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    References listed on IDEAS

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    More about this item

    Keywords

    Risk-aversion; Bitcoin returns; price predictability; copulas; quantiles;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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