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Conditional Extreme Values Theory and Tail-related Risk Measures: Evidence from Latin American Stock Markets

Author

Listed:
  • Raúl de Jesús-Gutiérrez

    (Facultad de Economía, Universidad Autónoma del Estado de México, México,)

  • Roberto J. Santillán-Salgado

    (EGADE Business School, Tecnológico de Monterrey, México)

Abstract

The purpose of this work is to extend McNeil and Frey´s (2000) methodology by combining two component GARCH models and extreme value theory to evaluate the performance of the value at risk (VaR) and expected shortfall (ES) measures in the Latin American stock markets. In-sample analysis, the results of the backtesting indicate that there is no a model that predominates to the others in the estimation of VaR at any confidence level. However, the P-values of the Kupiec test confirm the out-of-sample predictive ability of the CGARCH-EVT models to estimate the VaR for long and short financial positions from Argentina and Mexico, although their performance is insufficient to provide accurate estimates of the ES. The modeling of fat tails, asymmetry and long memory have important implications for risk management, and hedging strategies in volatile stock markets.

Suggested Citation

  • Raúl de Jesús-Gutiérrez & Roberto J. Santillán-Salgado, 2019. "Conditional Extreme Values Theory and Tail-related Risk Measures: Evidence from Latin American Stock Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 127-141.
  • Handle: RePEc:eco:journ1:2019-03-12
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Conditional extreme value theory; Value at Risk; Expected Shortfall.;

    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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