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Modeling dynamic VaR and CVaR of cryptocurrency returns with alpha-stable innovations

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  • Malek, Jiri
  • Nguyen, Duc Khuong
  • Sensoy, Ahmet
  • Tran, Quang Van

Abstract

We employ alpha-stable distribution to dynamically compute risk exposure measures for the five most traded cryptocurrencies. Returns are jointly modeled with an ARMA-GARCH approach for their conditional mean and variance processes with alpha-stable innovations. We use the MLE method to estimate the parameters of this distribution, along with those of conditional mean and variance. Our results show that the dynamic approach is superior to the static method. We also find out that these risk measures of five cryptocurrencies do not offer the same pattern of behavior across subperiods (i.e., pre-, during- and post-COVID pandemic).

Suggested Citation

  • 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).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pa:s1544612323001903
    DOI: 10.1016/j.frl.2023.103817
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    1. Artor Nuhiu & Florin Aliu & Jakub Horák & Bedri Peci, 2023. "Making Informed Decisions in the Volatile Crypto Market: An Analysis of Portfolio Risk and Return," SAGE Open, , vol. 13(3), pages 21582440231, August.

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    More about this item

    Keywords

    Alpha stable distribution; ARMA-GARCH; Cryptocurrencies; Dynamic VaR and CVaR; COVID-19;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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