Filtering and Maximum Likelihood Methods in the Calibration of Some Stochastic Volatility Models of Mathematical Finance

摘要

In this paper we present a formulation of the calibration problem for the Heston stochastic volatility model and for one of its generalizations based on filtering and maximum likelihood methods. Numerical algorithms are developed to solve the problem posed. Synthetic and real data are used to validate the formulation of the calibration problem and its numerical solution.