Conditional hitting time estimation in a nonlinear filtering model by the Brownian bridge method
Probability
2012-11-20 v1
Abstract
The model consists of a signal process which is a general Brownian diffusion process and an observation process , also a diffusion process, which is supposed to be correlated to the signal process. We suppose that the process is observed from time 0 to at discrete times and aim to estimate, conditionally on these observations, the probability that the non-observed process crosses a fixed barrier after a given time . We formulate this problem as a usual nonlinear filtering problem and use optimal quantization and Monte Carlo simulations techniques to estimate the involved quantities.
Cite
@article{arxiv.1211.4553,
title = {Conditional hitting time estimation in a nonlinear filtering model by the Brownian bridge method},
author = {Christophe Pofeta and Abass Sagna},
journal= {arXiv preprint arXiv:1211.4553},
year = {2012}
}