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Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations

Author

Listed:
  • Vahidin Jeleskovic

    (University of Kassel)

  • Mirko Meloni

    (University of Kassel)

  • Zahid Irshad Younas

    (National University of Sciences and Technology)

Abstract

Given the increasing interest in cryptocurrencies shown by investors and researchers, and the importance of the potential loss scenarios resulting from investment/trading activities, this research provides market operators with a dynamic overview on the short-term portfolio tail risk contribution of six widely-traded cryptocurrencies. Considering the high volatility dynamics of the cryptocurrency market, realized volatility measures computed from different frames (1m, 5m, 15m, 30m, 1h) are included in the estimation of univariate GARCH models, to be used in combination with copula functions for VaR/ES Monte Carlo simulations. Even if results lack data frequency ordinality in terms of out-of-sample goodness, Bitcoin and Litecoin are generally recognized as the safest and riskiest currency respectively on an equally-weighted framework, reflecting how the contribution to portfolio returns is not representative of the real grade of risk diversification.

Suggested Citation

  • Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    • Handle: RePEc:mar:magkse:202034
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    References listed on IDEAS

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    More about this item

    Keywords

    cryptocurrency tradiing; tail risk; realized volatility; copula; portfolio optimization.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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