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Value-at-Risk Forecasts Based on Decomposed Return Series: The Short Run Matters

In: Operations Research Proceedings 2015

Author

Listed:
  • Theo Berger

    (University of Bremen)

Abstract

We apply wavelet decomposition to decompose financial return series into a time frequency domain and assess the relevant frequencies for adequate daily Value-at-Risk (VaR) forecasts. Our results indicate that the frequencies that describe the short-run information of the underlying time series comprise the necessary information for daily VaR forecasts.

Suggested Citation

  • Theo Berger, 2017. "Value-at-Risk Forecasts Based on Decomposed Return Series: The Short Run Matters," Operations Research Proceedings, in: Karl Franz Dörner & Ivana Ljubic & Georg Pflug & Gernot Tragler (ed.), Operations Research Proceedings 2015, pages 503-509, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-42902-1_68
    DOI: 10.1007/978-3-319-42902-1_68
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