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Modeling Bitcoin price volatility: long memory vs Markov switching

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  • Walid Chkili

    (University of Carthage
    International Finance Group Tunisia Lab., University of Tunis El Manar)

Abstract

The aim of this paper is to identify the best model to describe the volatility dynamics of Bitcoin prices for the turbulent period 2013–2020. We use two types of models namely the long memory model and Markov switching model. Empirical results point out the presence of long memory in the volatility dynamics of the Bitcoin market. In addition, the FIGARCH model that explicitly accounts for long memory outperforms all other models in modeling the volatility of the Bitcoin prices. The finding has several implications for portfolio diversification, hedging strategy and Value at Risk assessment. Such analysis guides international investors towards the optimal portfolio diversification and the effective hedging instruments.

Suggested Citation

  • Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    • Handle: RePEc:spr:eurase:v:11:y:2021:i:3:d:10.1007_s40822-021-00180-7
    DOI: 10.1007/s40822-021-00180-7
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    More about this item

    Keywords

    Bitcoin; Volatility; GARCH model; Long memory; Markov switching;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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