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Advanced Expected Tail Loss Measurement and Quantification for the Moroccan All Shares Index Portfolio

Author

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  • Marouane Airouss

    (Department of Mathematics, Faculty of Science, Mohammed V University of Rabat, Rabat 8007, Morocco)

  • Mohamed Tahiri

    (Department of Economics, Faculty of Economics - Salé, Mohammed V University of Rabat, Rabat 8007, Morocco)

  • Amale Lahlou

    (Department of Economics, Faculty of Economics - Agdal, Mohammed V University of Rabat, Rabat 8007, Morocco)

  • Abdelhak Hassouni

    (Department of Mathematics, Faculty of Science, Mohammed V University of Rabat, Rabat 8007, Morocco)

Abstract

In this paper, we have analyzed and tested the Expected Tail Loss (ETL) approach for the Value at Risk (VaR) on the Moroccan stock market portfolio. We have compared the results with the general approaches for the standard VaR, which has been the most suitable method for Moroccan stock investors up to now. These methods calculate the maximum loss that a portfolio is likely to experience over a given time span. Our work advances those modeling methods with supplementation by inputs from the ETL approach for application to the Moroccan stock market portfolio—the Moroccan All Shares Index (MASI). We calculate these indicators using several methods, according to an easy and fast implementation with a high-level probability and with accommodation for extreme risks; this is in order to numerically simulate and study their behavior to better understand investment opportunities and, thus, form a clear view of the Moroccan financial landscape.

Suggested Citation

  • Marouane Airouss & Mohamed Tahiri & Amale Lahlou & Abdelhak Hassouni, 2018. "Advanced Expected Tail Loss Measurement and Quantification for the Moroccan All Shares Index Portfolio," Mathematics, MDPI, vol. 6(3), pages 1-19, March.
    • Handle: RePEc:gam:jmathe:v:6:y:2018:i:3:p:38-:d:135132
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    References listed on IDEAS

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    5. Sirr, Gordon & Garvey, John & Gallagher, Liam, 2011. "Emerging markets and portfolio foreign exchange risk: An empirical investigation using a value-at-risk decomposition technique," Journal of International Money and Finance, Elsevier, vol. 30(8), pages 1749-1772.
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