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Spectral estimation of the fractional order of a Lévy process

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  • Denis Belomestny

Abstract

We consider the problem of estimating the fractional order of a L´evy process from low frequency historical and options data. An estimation methodology is developed which allows us to treat both estimation and calibration problems in a unified way. The corresponding procedure consists of two steps: the estimation of a conditional characteristic function and the weighted least squares estimation of the fractional order in spectral domain. While the second step is identical for both calibration and estimation, the first one depends on the problem at hand. Minimax rates of convergence for the fractional order estimate are derived, the asymptotic normality is proved and a data-driven algorithm based on aggregation is proposed. The performance of the estimator in both estimation and calibration setups is illustrated by a simulation study.

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File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2009-021.pdf
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Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2009-021.

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Length: 38 pages
Date of creation: Apr 2009
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2009-021

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Related research

Keywords: regular Lévy processes; Blumenthal-Getoor index; semiparametric estimation;

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References

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  1. Akgiray, Vedat & Lamoureux, Christopher G, 1989. "Estimation of Stable-Law Parameters: A Comparative Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 85-93, January.
  2. Denis Belomestny & Markus Reiß, 2006. "Spectral calibration of exponential Lévy models," Finance and Stochastics, Springer, vol. 10(4), pages 449-474, December.
  3. Eberlein, Ernst & Keller, Ulrich & Prause, Karsten, 1998. "New Insights into Smile, Mispricing, and Value at Risk: The Hyperbolic Model," The Journal of Business, University of Chicago Press, vol. 71(3), pages 371-405, July.
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Cited by:
  1. Michał Grajek & Lars-Hendrik R�ller, 2012. "Regulation and Investment in Network Industries: Evidence from European Telecoms," Journal of Law and Economics, University of Chicago Press, vol. 55(1), pages 189 - 216.
  2. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Which continuous-time model is most appropriate for exchange rates?," Working Papers 2013-024, Federal Reserve Bank of St. Louis.
  3. Jakob S\"ohl, 2012. "Confidence sets in nonparametric calibration of exponential L\'evy models," Papers 1202.6611, arXiv.org, revised Sep 2013.
  4. Jakob Söhl, 2012. "Confidence sets in nonparametric calibration of exponential Lévy models," SFB 649 Discussion Papers SFB649DP2012-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  5. Belomestny, Denis & Panov, Vladimir, 2013. "Abelian theorems for stochastic volatility models with application to the estimation of jump activity," Stochastic Processes and their Applications, Elsevier, vol. 123(1), pages 15-44.
  6. Mathias Trabs, 2011. "Calibration of selfdecomposable Lévy models," SFB 649 Discussion Papers SFB649DP2011-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  7. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  8. Yacine A�t-Sahalia & Jean Jacod, 2012. "Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data," Journal of Economic Literature, American Economic Association, vol. 50(4), pages 1007-50, December.
  9. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  10. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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