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<p>This study addresses risk management for a ten-dimensional cryptocurrency portfolio, focusing on value at risk, expected shortfall, and range value at risk. It introduces a hybrid model combining the ARMA-EGARCH approach with flexible bulk and tails extreme value distribution and copula functions to improve risk measurement. The results show that the ARMA-EGARCH-EVT copula model better captures dependencies and outperforms traditional risk assessment methods (such as historical simulations and the variance covariance paradigm). This study underscores the potential of using a novel extreme value theory probability model to enhance risk assessment and provide valuable insights for investors and financial policymakers.</p>

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Novel modeling for assessment of extreme values risk in cryptocurrencies portfolio

  • 期刊论文

  • 发表日期：

    2025年7月8日

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  • Shafique Ur Rehman,
  • Touqeer Ahmad,
  • Desheng Wu

摘要

This study addresses risk management for a ten-dimensional cryptocurrency portfolio, focusing on value at risk, expected shortfall, and range value at risk. It introduces a hybrid model combining the ARMA-EGARCH approach with flexible bulk and tails extreme value distribution and copula functions to improve risk measurement. The results show that the ARMA-EGARCH-EVT copula model better captures dependencies and outperforms traditional risk assessment methods (such as historical simulations and the variance covariance paradigm). This study underscores the potential of using a novel extreme value theory probability model to enhance risk assessment and provide valuable insights for investors and financial policymakers.