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Estimation of tail‐related risk measures in the Indian stock market: An extreme value approach

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  • Madhusudan Karmakar
Abstract
The purpose of the study is to estimate tail‐related risk measures using extreme value theory (EVT) in the Indian stock market. The study employs a two stage approach of conditional EVT originally proposed by McNeil and Frey (2000) to estimate dynamic Value at Risk (VaR) and expected shortfall (ES). The dynamic risk measures have been estimated for different percentiles for negative and positive returns. The estimates of risk measures computed under different quantile levels exhibit strong stability across a range of the selected thresholds, implying the accuracy and reliability of the estimated quantile based risk measures.

Suggested Citation

  • Madhusudan Karmakar, 2013. "Estimation of tail‐related risk measures in the Indian stock market: An extreme value approach," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 79-85, September.
    • Handle: RePEc:wly:revfec:v:22:y:2013:i:3:p:79-85
    DOI: 10.1016/j.rfe.2013.05.001
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    References listed on IDEAS

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    1. Turan G. Bali & Panayiotis Theodossiou, 2008. "Risk Measurement Performance of Alternative Distribution Functions," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(2), pages 411-437, June.
    2. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, vol. 31(4), pages 519-530, July.
    3. Bali, Turan G. & Mo, Hengyong & Tang, Yi, 2008. "The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 269-282, February.
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    Cited by:

    1. Majumder, Debasish, 2023. "Subjectivity in conventional tail measures: An exploratory model with 'risks & biases’," Finance Research Letters, Elsevier, vol. 55(PB).

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