Stochastic Differential Equations (SDEs) have attracted the interest of many researchers due to their applications in several disciplines, such as physics, chemistry, quantitative finance, epidemiology, biology and, in general, in all fields describing a dynamics affected by random perturbations. In particular, based on the idea of continuous-time extension of one-step methods for the numerical solution of the SDE of Ito type, this talk aims to provide an efficient procedure to estimate the local truncation error for selected numerical methods to solve this problem. As known in the deterministic case, this is the first building block in order to assess a variable stepsize solver, that may be useful to solve stiff SDE. Numerical tests will be carried out in order to confirm the theoretical results.
Local error estimation of selected one-step numerical methods for Stochastic Differential Equations
Dajana Conte;Giuseppe Giordano
;Beatrice Paternoster
2022-01-01
Abstract
Stochastic Differential Equations (SDEs) have attracted the interest of many researchers due to their applications in several disciplines, such as physics, chemistry, quantitative finance, epidemiology, biology and, in general, in all fields describing a dynamics affected by random perturbations. In particular, based on the idea of continuous-time extension of one-step methods for the numerical solution of the SDE of Ito type, this talk aims to provide an efficient procedure to estimate the local truncation error for selected numerical methods to solve this problem. As known in the deterministic case, this is the first building block in order to assess a variable stepsize solver, that may be useful to solve stiff SDE. Numerical tests will be carried out in order to confirm the theoretical results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
