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A forecast comparison of volatility models using realized volatility: evidence from the Bitcoin market

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  • Takahiro Hattori

Abstract

This paper first evaluates the volatility modeling in the Bitcoin market in terms of its realized volatility, which is considered to be a reliable proxy of its true volatility. Based on the 5-minute return of Bitcoin, the proxy of its true volatility is computed as the sum of the squared intraday returns. To evaluate the performance of volatility modeling, this paper relies on MSE and QLIKE, which are the measures for making the forecast accuracy robust to noise in the imperfect volatility proxy, while different measures are also used for the robustness check. The empirically findings summarized as (1) the asymmetric volatility models such as EGARCH and APARCH have a higher predictability, and (2) the volatility model with normal distribution performs better than the fat-tailed distribution such as skewed t distribution.

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  • Takahiro Hattori, 2020. "A forecast comparison of volatility models using realized volatility: evidence from the Bitcoin market," Applied Economics Letters, Taylor & Francis Journals, vol. 27(7), pages 591-595, April.
    • Handle: RePEc:taf:apeclt:v:27:y:2020:i:7:p:591-595
    DOI: 10.1080/13504851.2019.1644421
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    Cited by:

    1. Michael Frömmel & Eyup Kadioglu, 2023. "Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    2. Wang, Weichen & An, Ran & Zhu, Ziwei, 2024. "Volatility prediction comparison via robust volatility proxies: An empirical deviation perspective," Journal of Econometrics, Elsevier, vol. 239(2).

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