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Flexible stochastic volatility structures for high frequency financial data

Author

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  • Feldmann, David
  • Härdle, Wolfgang Karl
  • Hafner, Christian M.
  • Hoffmann, Marc
  • Lepskii, Oleg V.
  • Tsybakov, Alexandre B.

Abstract

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a simulation study and apply the test to the HFDF96 data set. Our results confirm a linear AR(1) structure for the analyzed stock indices S&P500, Dow Jones Industrial Average and for the exchange rate DEM/USD.

Suggested Citation

  • Feldmann, David & Härdle, Wolfgang Karl & Hafner, Christian M. & Hoffmann, Marc & Lepskii, Oleg V. & Tsybakov, Alexandre B., 1998. "Flexible stochastic volatility structures for high frequency financial data," SFB 373 Discussion Papers 1998,34, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:199834
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    References listed on IDEAS

    as
    1. Hardle, W. & Tsybakov, A., 1997. "Local polynomial estimators of the volatility function in nonparametric autoregression," Journal of Econometrics, Elsevier, vol. 81(1), pages 223-242, November.
    2. repec:crs:wpaper:9546 is not listed on IDEAS
    3. Ronald J. Mahieu & Peter C. Schotman, 1998. "An empirical application of stochastic volatility models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(4), pages 333-360.
    4. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    5. Leblanc, F. & Lepski, O. V., 1996. "Test for symmetry of regression curves," SFB 373 Discussion Papers 1996,51, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
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