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A new Technique for Calibrating Stochastic Volatility Models: The Malliavin Gradient Method

[journal article]

Ewald, Christian-Oliver
Zhang, Aihua

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)


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Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.