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Modeling the volatility of Bitcoin returns using Nonparametric GARCH models

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  • Sami MESTIRI

Abstract

Objective: The purpose of this paper is to demonstrate the effectiveness of the nonparametric GARCH model for the prediction of future Bitcoin prices. \n \n Methodology: The parametric GARCH models to characterize the volatility of Bitcoin returns are widely used in the empirical literature. Alternatively, we consider a non-parametric approach to model and forecast the volatility of Bitcoin returns. \n \n Results: We show that the volatility forecast of the nonparametric GARCH model yields superior performance compared to an extended class of parametric GARCH models. \n \n Originality / relevance: The improved accuracy of forecasting the volatility of Bitcoin returns based on the nonparametric GARCH model suggests that this method offers an attractive and viable alternative to commonly used GARCH parametric models.

Suggested Citation

  • Sami MESTIRI, 2022. "Modeling the volatility of Bitcoin returns using Nonparametric GARCH models," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 13(1), pages 2-16, June.
    • Handle: RePEc:jaf:journl:v:13:y:2022:i:1:n:489
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    File URL: https://www.scientific-society.com/AF/article/view/489
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    JEL classification:

    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration
    • N8 - Economic History - - Micro-Business History
    • G3 - Financial Economics - - Corporate Finance and Governance

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