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- W2033200020 abstract "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 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. Keywords: Malliavin calculusMonte Carlo simulationStochastic volatility modelsCalibrationGradient methodsValue at risk Acknowledgment Our thanks go to the Stochastic Control and Mathematical Finance Group of the University of Kaiserslautern for presenting us with a rich and stimulating working environment and Ralf Korn, Heinrich von Weizsäcker, David Nualart and Klaus Schenk-Hoppé for fruitful discussions and advice. Additionally the first author wants to thank in particular the BBSRC and the University of Bristol for financial support. The second author wants to thank Leeds University Business School as well as the University of Kaiserslautern for financial support. Thanks also go to an anonymous referee for many useful comments and suggestions which we used to improve an earlier version of this article. This work was partly supported by the Rheinland-Pfalz Excellence Cluster ‘Dependable adaptive systems and mathematical modeling’." @default.
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- W2033200020 date "2006-04-01" @default.
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- W2033200020 title "A new technique for calibrating stochastic volatility models: the Malliavin gradient method" @default.
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- W2033200020 doi "https://doi.org/10.1080/14697680500531676" @default.
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