Simulation de trajectoires de processus continus

TL;DR

This paper provides practical tools for simulating continuous-time stochastic processes, focusing on diffusion models relevant to finance and insurance, addressing discretization, parameter estimation, and random number generation.

Contribution

It introduces methods for the effective simulation of diffusion processes tailored for insurance applications, enhancing practical implementation.

Findings

Improved simulation techniques for diffusion processes.

Guidelines for discretization and parameter estimation.

Enhanced random number generation methods.

Abstract

Continuous time stochastic processes are useful models especially for financial and insurance purposes. The numerical simulation of such models is dependant of the time discrete discretization, of the parametric estimation and of the choice of a random number generator. The aim of this paper is to provide the tools for the practical implementation of diffusion processes simulation, particularly for insurance contexts.