Exact simulation of first exit times for one-dimensional diffusion processes
Provides an exact simulation method for exit times, addressing a challenging problem in fields like finance and neuroscience where discretization errors are problematic.
The paper presents a new acceptance-rejection algorithm that exactly simulates first exit times for one-dimensional diffusion processes, avoiding discretization errors. Numerical examples demonstrate its efficiency.
The simulation of exit times for diffusion processes is a challenging task since it concerns many applications in different fields like mathematical finance, neuroscience, reliability... The usual procedure is to use discretiza-tion schemes which unfortunately introduce some error in the target distribution. Our aim is to present a new algorithm which simulates exactly the exit time for one-dimensional diffusions. This acceptance-rejection algorithm requires to simulate exactly the exit time of the Brownian motion on one side and the Brownian position at a given time, constrained not to have exit before, on the other side. Crucial tools in this study are the Girsanov transformation, the convergent series method for the simulation of random variables and the classical rejection sampling. The efficiency of the method is described through theoretical results and numerical examples.