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A new Technique for Calibrating Stochastic Volatility Models: The Malliavin Gradient Method
[journal article]
Abstract We discuss the application of gradient methods to calibrate mean reverting stochastic volatility models. For this we use formulas based on Girsanov transformations as well as a modification of the Bismut-Elworthy formula to compute the derivatives of certain option prices with respect to the paramet... view more
We discuss the application of gradient methods to calibrate mean reverting stochastic volatility models. For this we use formulas based on Girsanov transformations as well as a modification of the Bismut-Elworthy formula to compute the derivatives of certain option prices with respect to the parameters of the model by applying Monte Carlo methods. The article presents an extension of the ideas to apply Malliavin calculus methods in the computation of Greek's.... view less
Classification
Economic Statistics, Econometrics, Business Informatics
Basic Research, General Concepts and History of Economics
Method
theory application
Free Keywords
Monte Carlo Methods; Calibration of Stochastic Volatility; Derivative Pricing Models; Option Pricing via Simulation; Computational Finance; Stochastic Volatility; Financial Mathematics; Value at Risk
Document language
English
Publication Year
2006
Page/Pages
p. 147-158
Journal
Quantitative Finance, 6 (2006) 2
DOI
https://doi.org/10.1080/14697680500531676
Status
Postprint; peer reviewed
Licence
PEER Licence Agreement (applicable only to documents from PEER project)