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Spectral calibration of exponential Lévy models


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  • Denis Belomestny


  • Markus Reiß



The calibration of financial models has become rather important topic in recent years mainly because of the need to price increasingly complex options in a consistent way. The choice of the underlying model is crucial for the good performance of any calibration procedure. Recent empirical evidences suggest that more complex models taking into account such phenomenons as jumps in the stock prices, smiles in implied volatilities and so on should be considered. Among most popular such models are Levy ones which are on the one hand able to produce complex behavior of the stock time series including jumps, heavy tails and on other hand remain tractable with respect to option pricing. The work on calibration methods for financial models based on Lévy processes has mainly focused on certain parametrisations of the underlying Lévy process with the notable exception of Cont and Tankov (2004). Since the characteristic triplet of a Lévy process is a priori an infinite-dimensional object, the parametric approach is always exposed to the problem of misspecification, in particular when there is no inherent economic foundation of the parameters and they are only used to generate different shapes of possible jump distributions. In this work we propose and test a non-parametric calibration algorithm which is based on the inversion of the explicit pricing formula via Fourier transforms and a regularisation in the spectral domain. Using the Fast Fourier Transformation, the procedure is fast, easy to implement and yields good results in simulations in view of the severe ill-posedness of the underlying inverse problem.

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Bibliographic Info

Article provided by Springer in its journal Finance and Stochastics.

Volume (Year): 10 (2006)
Issue (Month): 4 (December)
Pages: 449-474

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Handle: RePEc:spr:finsto:v:10:y:2006:i:4:p:449-474

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Keywords: European option; Jump diffusion; Minimax rates; Severely ill-posed; Nonlinear inverse problem; Spectral cut-off; 60G51; 62G20; 91B28; G13; C14;

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  4. Ernesto Mordecki, 2002. "Optimal stopping and perpetual options for Lévy processes," Finance and Stochastics, Springer, vol. 6(4), pages 473-493.
  5. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-51, October.
  6. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  7. Peter Carr & Helyette Geman, 2002. "The Fine Structure of Asset Returns: An Empirical Investigation," The Journal of Business, University of Chicago Press, vol. 75(2), pages 305-332, April.
  8. 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. Kappus, Johanna, 2014. "Adaptive nonparametric estimation for Lévy processes observed at low frequency," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 730-758.
  2. Söhl, Jakob, 2010. "Polar sets for anisotropic Gaussian random fields," Statistics & Probability Letters, Elsevier, vol. 80(9-10), pages 840-847, May.
  3. Johanna Kappus, 2012. "Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes," SFB 649 Discussion Papers SFB649DP2012-016, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  4. Reiß, Markus, 2013. "Testing the characteristics of a Lévy process," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2808-2828.
  5. Jan Kallsen & Paul Kr\"uhner, 2013. "On a Heath-Jarrow-Morton approach for stock options," Papers 1305.5621,, revised Aug 2013.
  6. Jacob Söhl & Mathias Trabs, 2012. "Option calibration of exponential Lévy models: Implementation and empirical results," SFB 649 Discussion Papers SFB649DP2012-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  7. Song, Seongjoo, 2010. "Lévy density estimation via information projection onto wavelet subspaces," Statistics & Probability Letters, Elsevier, vol. 80(21-22), pages 1623-1632, November.
  8. Mathias Trabs, 2011. "Calibration of selfdecomposable Lévy models," SFB 649 Discussion Papers SFB649DP2011-073, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  9. Jakob S\"ohl, 2012. "Confidence sets in nonparametric calibration of exponential L\'evy models," Papers 1202.6611,, revised Sep 2013.
  10. Richard Nickl & Markus Reiß, 2012. "A Donsker Theorem for Lévy Measures," SFB 649 Discussion Papers SFB649DP2012-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  11. Jakob Söhl, 2012. "Confidence sets in nonparametric calibration of exponential Lévy models," SFB 649 Discussion Papers SFB649DP2012-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  12. Jakob S\"ohl & Mathias Trabs, 2012. "Option calibration of exponential L\'evy models: Confidence intervals and empirical results," Papers 1202.5983,, revised Oct 2012.
  13. Chen, Song X. & Delaigle, Aurore & Hall, Peter, 2010. "Nonparametric estimation for a class of Lévy processes," Journal of Econometrics, Elsevier, vol. 157(2), pages 257-271, August.
  14. Denis Belomestny, 2009. "Spectral estimation of the fractional order of a Lévy process," SFB 649 Discussion Papers SFB649DP2009-021, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.


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