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Time-varying higher moments in Bitcoin

Author

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  • Leonardo Ieracitano Vieira

    (FEARP, University of São Paulo)

  • Márcio Poletti Laurini

    (FEARP, University of São Paulo)

Abstract

Cryptocurrencies represent a new and important class of investments but are associated with asymmetric distributions and extreme price changes. We use a modeling structure where higher-order moments (scale, skewness and kurtosis) are time-varying, and additionally we used nontraditional innovations distributions to study the return series of the most important cryptocurrency, Bitcoin. Based on the estimation of a series of Generalized Autoregressive Score (GAS) models, we compare predictive performance using a loss function based on Value at Risk performance.

Suggested Citation

  • Leonardo Ieracitano Vieira & Márcio Poletti Laurini, 2023. "Time-varying higher moments in Bitcoin," Digital Finance, Springer, vol. 5(2), pages 231-260, June.
    • Handle: RePEc:spr:digfin:v:5:y:2023:i:2:d:10.1007_s42521-022-00072-8
    DOI: 10.1007/s42521-022-00072-8
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    More about this item

    Keywords

    Bitcoin; Higher-order moments; Risk management; Generalized autoregressive score;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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