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On the Conditional Value at Risk Based on the Laplace Distribution with Application in GARCH Model

Author

Listed:
  • Malik Zaka Ullah

    (Mathematical Modeling and Applied Computation (MMAC) Research Group, Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Fouad Othman Mallawi

    (Mathematical Modeling and Applied Computation (MMAC) Research Group, Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Mir Asma

    (Institute of Mathematical Sciences, Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Stanford Shateyi

    (Department of Mathematics and Applied Mathematics, School of Mathematical and Natural Sciences, University of Venda, P. Bag X5050, Thohoyandou 0950, South Africa)

Abstract

In this article, the Laplace distribution is employed in lieu of the well-known normal distribution for finding better scalar values of risk. Explicit formulas for value-at-risk (VaR) and conditional value-at-risk (CVaR) are studied and used to manage the risk involved in a stock movement by using the GARCH model. Numerical simulations are given for a variety of stocks in equity markets to uphold the findings.

Suggested Citation

  • Malik Zaka Ullah & Fouad Othman Mallawi & Mir Asma & Stanford Shateyi, 2022. "On the Conditional Value at Risk Based on the Laplace Distribution with Application in GARCH Model," Mathematics, MDPI, vol. 10(16), pages 1-13, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:3018-:d:894242
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    References listed on IDEAS

    as
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