On the pricing of multi-asset options under jump-diffusion processes using meshfree moving least-squares approximation

M Shirzadi, M Dehghan, AF Bastani - Communications in Nonlinear …, 2020 - Elsevier
Communications in Nonlinear Science and Numerical Simulation, 2020Elsevier
The moving least-squares (MLS) approximation is a powerful numerical scheme widely
used in the meshfree literature to construct local multivariate polynomial basis functions for
expanding the solution of a given differential or integral equation. For partial integro-
differential equations arising from the valuation of multi-asset options written on correlated
Lévy-driven assets, we propose here an MLS-based collocation scheme in conjunction with
implicit-explicit (IMEX) temporal discretization to numerically solve the problem. We apply …
Abstract
The moving least-squares (MLS) approximation is a powerful numerical scheme widely used in the meshfree literature to construct local multivariate polynomial basis functions for expanding the solution of a given differential or integral equation. For partial integro-differential equations arising from the valuation of multi-asset options written on correlated Lévy-driven assets, we propose here an MLS-based collocation scheme in conjunction with implicit-explicit (IMEX) temporal discretization to numerically solve the problem. We apply the method to price both European and American options and compute the option hedge parameters. In the case of American options, we use an operator splitting approach to solve the linear complementarity formulation of the problem. Our numerical experiments show the efficiency of the proposed scheme in comparison with some competing approaches, specially finite difference methods.
Elsevier
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