Calibration of local volatility using the local and implied instantaneous variance
AbstractWe document the calibration of the local volatility in terms of local and implied instantaneous variances; we first explore the theoretical properties of the method for a particular class of volatilities. We confirm the theoretical results through a numerical procedure which uses a Gauss-Newton style approximation of the Hessian in the framework of a sequential quadratic programming (SQP) approach. The procedure performs well on benchmarks from the literature and on FOREX data.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by HAL in its series Post-Print with number hal-00338114.
Date of creation: 09 Dec 2009
Date of revision:
Publication status: Published, Journal of Computational Finance, 2009, 13, 2, 1--18
Note: View the original document on HAL open archive server: http://hal.archives-ouvertes.fr/hal-00338114
Contact details of provider:
Web page: http://hal.archives-ouvertes.fr/
calibration; local volatility; implied volatility; Dupire formula; adjoint; instantaneous local variance; instantaneous implied variance; implied variance;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-02-22 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lishang Jiang & Qihong Chen & Lijun Wang & Jin Zhang, 2003. "A new well-posed algorithm to recover implied local volatility," Quantitative Finance, Taylor and Francis Journals, vol. 3(6), pages 451-457.
- Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.
- F. Gerlich & A. Giese & J. Maruhn & E. Sachs, 2012. "Parameter identification in financial market models with a feasible point SQP algorithm," Computational Optimization and Applications, Springer, vol. 51(3), pages 1137-1161, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD).
If references are entirely missing, you can add them using this form.