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Testing expected shortfall: an application to emerging market stock indices

Author

Listed:
  • Emilio Cardona

    (Universidad de los Andes, School of Management)

  • Andrés Mora-Valencia

    (Universidad de los Andes, School of Management)

  • Daniel Velásquez-Gaviria

    (Universidad EAFIT
    Instituto Tecnológico Metropolitano-ITM)

Abstract

In a recent paper, Acerbi and Székely (Risk Magazine, 76–81, 2014) presented three methods to test expected shortfall, and this is the first empirical application of that paper on emerging markets. We employ daily stock index returns from the Morgan Stanley Capital International Inc. Emerging Markets Index covering the 2000–2015 period, extending Acerbi and Székely (Risk Magazine, 76–81, 2014) results to derive the significance thresholds for the Student’s skewed-t distribution using two testing methods. We find that the thresholds for the Z1 Test and Z2 Test for skewed-t distribution are similar to the values obtained by Acerbi and Székely for Student’s t distribution. Therefore, the Z1 and Z2 thresholds are invariant to the skewed-t-shaped parameter values found in the emerging market stock indices. Empirical results show outperformance of Student’s skewed-t and Student’s t distributions over Gaussian distribution.

Suggested Citation

  • Emilio Cardona & Andrés Mora-Valencia & Daniel Velásquez-Gaviria, 2019. "Testing expected shortfall: an application to emerging market stock indices," Risk Management, Palgrave Macmillan, vol. 21(3), pages 153-182, September.
    • Handle: RePEc:pal:risman:v:21:y:2019:i:3:d:10.1057_s41283-018-0046-z
    DOI: 10.1057/s41283-018-0046-z
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    2. Daniel Velásquez-Gaviria & Andrés Mora-Valencia & Javier Perote, 2020. "A Comparison of the Risk Quantification in Traditional and Renewable Energy Markets," Energies, MDPI, vol. 13(11), pages 1-42, June.

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