The method of evaluation of stochastic volatility (SV) model coefficients, with time going to the infinity, is consid-ered. The problem of finding the solution of a system of stochastic differential equations is reduced to that of the analytical solution of the Fokker-Planck-Kolmogorov...

The method of evaluation of stochastic volatility (SV) model coefficients, with time approaching the infinity, is consid-ered. The problem of finding the solution of a system of stochastic differential equations is reduced to that of the ana-lytical solution of the Fokker–Planck–Kholmogorov...

In this paper we use Malliavin calculus techniques to obtain an expression for the short-time behavior of the at-the-money implied volatility skew for a generalization of the Bates model, where the volatility does not need to be neither a difussion, nor a Markov process as the examples in...

Missing variable models are typical benchmarks for new computational techniques in that the ill-posed nature of missing variable models offer a challenging testing ground for these techniques. This was the case for the EM algorithm and the Gibbs sampler, and this is also true for importance...

Missing variable models are typical benchmarks for new computational techniques in that the ill-posed nature of missing variable models offer a challenging testing ground for these techniques. This was the case for the EM algorithm and the Gibbs sampler, and this is also true for importance...

Many of the different numerical techniques in the partial differential equations framework for solving option pricing problems have employed only standard second-order discretization schemes. A higher-order discretization has the advantage of producing low size matrix systems for computing...

In this paper we discuss a new approach to extend a class of solvable stochastic volatility models (SVM). Usually, classical SVM adopt a CEV process for instantaneous variance where the CEV parameter γ takes just few values: 0—the Ornstein–Uhlenbeck process, 1/2—the Heston (or square...