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

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Operations Research Proceedings 2015

Part of the book series: Operations Research Proceedings ((ORP))

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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.

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Notes

  1. 1.

    Due to its late listing we excluded Visa.

  2. 2.

    For the interested reader, we are happy to provide a detailed methodological description of our study upon request.

References

  1. Berger, T.: A wavelet based approach to measure and manage contagion at different time scales. Physica A 436, 338–350 (2015)

    Article  Google Scholar 

  2. Gallegati, M.: A wavelet-based approach to test for financial market contagion. Comput. Stat. Data Anal. 56, 3491–3497 (2012)

    Article  Google Scholar 

  3. Gençay, R., Selçuk, F., Whitcher, B.: Scaling properties of foreign exchange volatility. Physica A 289, 249–266 (2001)

    Article  Google Scholar 

  4. Jorion, P.: Value at Risk: The New Benchmark for Controlling Derivatives Risk. McGraw, New York (2007)

    Google Scholar 

  5. Ramsey, J.B., Uskinov, D., Zaslavsky, G.M.: An analysis of U.S. stock price behavior using wavelets. Fractals 3, 377–389 (1995)

    Article  Google Scholar 

  6. Reboredo, J., Riveiro-Castro, M.: Wavelet-based evidence of the impact of oil prices on stock returns. Int. Rev. Econ. Financ. 29, 145–176 (2014)

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Bremen, Wilhelm-Herbst-Str. 5, 28359, Bremen, Germany

    Theo Berger

Authors
  1. Theo Berger
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Correspondence to Theo Berger .

Editor information

Editors and Affiliations

  1. Department of Business Administration, University of Vienna, Vienna, Austria

    Karl Franz Dörner

  2. Decision Sciences and Statistics (IDS) Department, ESSEC Business School of Paris, Cergy Pontoise Cedex, France

    Ivana Ljubic

  3. Department of Statistics and Operations Research, University of Vienna, Vienna, Austria

    Georg Pflug

  4. Operations Research and Control Systems, TU Wien, Vienna, Austria

    Gernot Tragler

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Berger, T. (2017). Value-at-Risk Forecasts Based on Decomposed Return Series: The Short Run Matters. In: Dörner, K., Ljubic, I., Pflug, G., Tragler, G. (eds) Operations Research Proceedings 2015. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-42902-1_68

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