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Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets

Author

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  • Silahli, Baykar
  • Dingec, Kemal Dincer
  • Cifter, Atilla
  • Aydin, Nezir

Abstract

This paper extends the univariate two-sided Weibull distribution to a multivariate case for portfolio-value-at-risk estimation. This method allows to capture the stylized facts of the time series of cryptocurrencies, such as extreme volatility, volatility clustering, very heavy tails, and skewness. This new portfolio risk model is applied to a cryptocurrency portfolio consisting of four major coins: Bitcoin, Litecoin, Ripple, and Dash. The predictive performance of the proposed model is compared with several widely used models. We find that the portfolio value-at-risk with two-sided Weibull distribution outperforms the other models.

Suggested Citation

  • Silahli, Baykar & Dingec, Kemal Dincer & Cifter, Atilla & Aydin, Nezir, 2021. "Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:finlet:v:38:y:2021:i:c:s1544612319312024
    DOI: 10.1016/j.frl.2019.101425
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    Cited by:

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    2. Mercik, Aleksander & Słoński, Tomasz & Karaś, Marta, 2024. "Understanding crypto-asset exposure: An investigation of its impact on performance and stock sensitivity among listed companies," International Review of Financial Analysis, Elsevier, vol. 92(C).
    3. Katarína Draganová & Karol Semrád & Monika Blišťanová & Tomáš Musil & Rastislav Jurč, 2021. "Influence of Disinfectants on Airport Conveyor Belts," Sustainability, MDPI, vol. 13(19), pages 1-13, September.
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    5. Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023. "Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

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    More about this item

    Keywords

    Two-sided Weibull distribution; Portfolio Value-at-Risk; Volatility; Cryptocurrency markets;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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