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A Comparison of Extreme Value Theory with Heavy - tailed Distributions in Modeling Daily VAR

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  • Emrah Altun
  • Hüseyin Tatlidil

Abstract

In this study, the performances of GARCH models with different distribution assumptions in modeling Value-at-Risk are evaluated by the backtesting procedure for three equity indexes. Recent researches indicate that Extreme Value Theory (EVT) is good candidate to model rare extreme events and unpredictable losses. Due to return series have non-normal characteristics, standardized residuals of GARCH are modeled by EVT and leptokurtic distributions. Empirical findings show that EVT based GARCH model is outperformed according to the backtesting results modeling daily VaR for all equity indexes.

Suggested Citation

  • Emrah Altun & Hüseyin Tatlidil, 2015. "A Comparison of Extreme Value Theory with Heavy - tailed Distributions in Modeling Daily VAR," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 4(2), pages 1-5.
    • Handle: RePEc:spt:fininv:v:4:y:2015:i:2:f:4_2_5
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