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Volatility measures and Value-at-Risk

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  • Bams, Dennis
  • Blanchard, Gildas
  • Lehnert, Thorsten

Abstract

We evaluate and compare the abilities of the implied volatility and historical volatility models to provide accurate Value-at-Risk forecasts. Our empirical tests on the S&P 500, Dow Jones Industrial Average and Nasdaq 100 indices over long time series of more than 20 years of daily data indicate that an implied volatility based Value-at-Risk cannot beat, and tends to be outperformed by, a simple GJR-GARCH based Value-at-Risk. This finding is robust to the use of the likelihood ratio, the dynamic quantile test or a statistical loss function for evaluating the Value-at-Risk performance.

Suggested Citation

  • Bams, Dennis & Blanchard, Gildas & Lehnert, Thorsten, 2017. "Volatility measures and Value-at-Risk," International Journal of Forecasting, Elsevier, vol. 33(4), pages 848-863.
    • Handle: RePEc:eee:intfor:v:33:y:2017:i:4:p:848-863
    DOI: 10.1016/j.ijforecast.2017.04.004
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