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Solving the Inverse Problem of Option Pricing Based on a Black-Scholes Model Using a Regularized-Gauss-Newton Method

Yitong Han, Minghui Jiang, Yong Chen, Yixin Dou


This paper investigates the inverse problem of a stochastic volatility based on the Black-Scholes option pricing model. In order to overcome the ill-posedness of reconstructing a stochastic volatility, a regularized-Gauss-Newton method is applied to solve the inverse problem. Numerical examples show that the reconstruction algorithm is convergence and stable.


Option pricing,Black-Scholes model , inverse problem, ill-posedness,

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