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Rough volatility of Bitcoin

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  • Takaishi, Tetsuya

Abstract

Recent studies have found that the log-volatility of asset returns exhibits roughness. This study investigates roughness or the anti-persistence of Bitcoin volatility. Using multifractal detrended fluctuation analysis, we obtain the generalized Hurst exponent of the log-volatility increments and find that the generalized Hurst exponent is less than 1/2, which indicates rough log-volatility increments. Furthermore, we find that the generalized Hurst exponent is not constant. This observation indicates that the log-volatility has a multifractal property. Using shuffled time series of the log-volatility increments, we infer that the source of multifractality partly derives from the distributional property.

Suggested Citation

  • Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
  • Handle: RePEc:eee:finlet:v:32:y:2020:i:c:s154461231930337x
    DOI: 10.1016/j.frl.2019.101379
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    Cited by:

    1. Liang Wang & Weixuan Xia, 2022. "Power‐type derivatives for rough volatility with jumps," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1369-1406, July.
    2. Brandi, Giuseppe & Di Matteo, T., 2022. "Multiscaling and rough volatility: An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 84(C).
    3. Siu Hin Tang & Mathieu Rosenbaum & Chao Zhou, 2023. "Forecasting Volatility with Machine Learning and Rough Volatility: Example from the Crypto-Winter," Papers 2311.04727, arXiv.org, revised Feb 2024.
    4. Angelini, Daniele & Bianchi, Sergio, 2023. "Nonlinear biases in the roughness of a Fractional Stochastic Regularity Model," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    5. Qing Shi & Xiaoqi Sun, 2020. "A Scientometric Review of Digital Currency and Electronic Payment Research: A Network Perspective," Complexity, Hindawi, vol. 2020, pages 1-17, November.
    6. Giuseppe Brandi & T. Di Matteo, 2022. "Multiscaling and rough volatility: an empirical investigation," Papers 2201.10466, arXiv.org.
    7. Karl Oton Rudolf & Samer Ajour El Zein & Nicola Jackman Lansdowne, 2021. "Bitcoin as an Investment and Hedge Alternative. A DCC MGARCH Model Analysis," Risks, MDPI, vol. 9(9), pages 1-22, August.
    8. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    9. Malek, Jiri & Nguyen, Duc Khuong & Sensoy, Ahmet & Tran, Quang Van, 2023. "Modeling dynamic VaR and CVaR of cryptocurrency returns with alpha-stable innovations," Finance Research Letters, Elsevier, vol. 55(PA).

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    Keywords

    Rough volatility; Bitcoin; Hurst exponent; Multifractality;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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