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Evaluating Measures Of Market Risk In Circumstances Of Global Financial Crisis – Empirical Evidence From Five Countries

Author

Listed:
  • Ivica Terzić

    (Singidunum University)

  • Marko Milojević

    (Singidunum University)

Abstract

The purpose of this paper is to evaluate performance of value-at-risk (VaR) produced by two risk models: historical simulation and Risk Metrics. We perform three backtest: unconditional coverage, independence and conditional coverage. We present results on both VaR 1% and VaR 5% on a one-day horizon for the following indices: S&P 500, DAX, SAX, PX and Belex 15. Our results show that Historical simulation 500 days rolling window approach satisfies unconditional coverage for all tested indices, while Risk Metrics has many rejection cases. On the other hand Risk Metrics model satisfies independence backtest for three indices, while Historical simulation has rejected more times. Based on our strong criteria to accept accuracy of VaR models only if both unconditional coverage and independence properties are satisfied, results indicate that during the crisis period all tested VaR models underestimate the true level of market risk exposure.

Suggested Citation

  • Ivica Terzić & Marko Milojević, 2013. "Evaluating Measures Of Market Risk In Circumstances Of Global Financial Crisis – Empirical Evidence From Five Countries," CBU International Conference Proceedings, ISE Research Institute, vol. 1(0), pages 75-81, June.
    • Handle: RePEc:aad:iseicj:v:1:y:2013:i:0:p:75-81
    DOI: 10.12955/cbup.v1.17
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    More about this item

    Keywords

    value at risk; backtesting; market risk; historical simulation; risk metrics;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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