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Managing extreme risk in some major stock markets: An extreme value approach

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  • Karmakar, Madhusudan
  • Shukla, Girja K.

Abstract

The study investigates the relative performance of Value-at-Risk (VaR) models using daily share price index data from six different countries across Asia, Europe and the United States for a period of 10years from January 01, 2000 to December 31, 2009. The main emphasis of the study has been given to Extreme Value Theory (EVT) and to evaluate how well Conditional EVT model performs in modeling tails of distributions and in estimating and forecasting VaR measures. We have followed McNeil and Frey's (2000) two stage approach called Conditional EVT to estimate dynamic VaR. In stage 1, we model the conditional volatility of each series using an appropriate asymmetric GARCH model which serves to filter the return series such that the asymmetric GARCH residuals are closer to iid than the raw return series. In stage 2, we apply EVT to model the fat tails of the asymmetric GARCH residuals. We have compared the accuracy of Conditional EVT approach to VaR estimation with other competing models. The best performing model is found to be the Conditional EVT for the entire sample. To confirm whether the Conditional EVT would still be the best for a sub-period, we have compared the forecasting accuracy for the sub-sample of bull market. Here too the Conditional EVT maintains its superiority even more precisely. Since the Conditional EVT approach clearly dominates other competing models in terms of VaR forecasting, we would advocate the use of the model when managing tail related market risk in such equity markets.

Suggested Citation

  • Karmakar, Madhusudan & Shukla, Girja K., 2015. "Managing extreme risk in some major stock markets: An extreme value approach," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 1-25.
  • Handle: RePEc:eee:reveco:v:35:y:2015:i:c:p:1-25
    DOI: 10.1016/j.iref.2014.09.001
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    References listed on IDEAS

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    Cited by:

    1. Li, Longqing, 2017. "A Comparative Study of GARCH and EVT Model in Modeling Value-at-Risk," MPRA Paper 85645, University Library of Munich, Germany.
    2. repec:eee:quaeco:v:68:y:2018:i:c:p:31-38 is not listed on IDEAS
    3. Karmakar, Madhusudan & Paul, Samit, 2016. "Intraday risk management in International stock markets: A conditional EVT approach," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 34-55.
    4. Prateek Sharma & Vipul _, 2015. "Forecasting stock index volatility with GARCH models: international evidence," Studies in Economics and Finance, Emerald Group Publishing, vol. 32(4), pages 445-463, October.

    More about this item

    Keywords

    Extreme Value Theory; Peak over threshold method; Conditional EVT; Value-at-Risk;

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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