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Relative Efficiency of Component GARCH-EVT Approach in Managing Intraday Market Risk

Author

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  • Samit Paul

    (Indian Institute of Management Calcutta, India)

  • Madhusudan Karmakar

    (Indian Institute of Management Lucknow, India)

Abstract

The purpose of this study is to estimate intraday Value-at-Risk (VaR) and Expected Shortfall (ES) of high frequency stock price indices taken from select markets of the world. The stylized properties indicate that the return series exhibit skewed and leptokurtic distributions, volatility clustering, periodicity of volatility and long memory process in volatility, all of which together suggest the usage of Component GARCH- EVT combined approach on periodicity adjusted return series to forecast accurate intraday VaR and ES. Hence we estimate intraday VaR and ES using Component GARCH-EVT combined approach with different innovation distributions such as normal, student-t and skewed student-t and compare its relative accuracy with the benchmark GARCH-EVT model with different distributions. The Component GARCH-EVT models in general perform better than GARCH-EVT models and the model with skewed student-t innovations forecasts more accurately. The study is useful for market participants involved in frequent intraday trading in such markets.

Suggested Citation

  • Samit Paul & Madhusudan Karmakar, 2017. "Relative Efficiency of Component GARCH-EVT Approach in Managing Intraday Market Risk," Multinational Finance Journal, Multinational Finance Journal, vol. 21(4), pages 247-283, December.
    • Handle: RePEc:mfj:journl:v:21:y:2017:i:4:p:247-283
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    Cited by:

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    2. Panayiotis Theodossiou & Dimitris Tsouknidis & Christos Savva, 2020. "Freight rates in downside and upside markets: pricing of own and spillover risks from other shipping segments," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1097-1119, June.

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    More about this item

    Keywords

    deseasonalized; intraday; value at risk; expected shortfall; component GARCH; EVT;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G19 - Financial Economics - - General Financial Markets - - - Other

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