Quadratic optimal functional quantization of stochastic processes and numerical applications
Probability
2013-04-03 v1
Abstract
In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a Hilbert-valued random variable, using a nearest neighbour projection on a finite codebook. A special emphasis is made on the computational aspects and the numerical applications, in particular the pricing of some path-dependent European options.
Cite
@article{arxiv.0706.4450,
title = {Quadratic optimal functional quantization of stochastic processes and numerical applications},
author = {Gilles Pagès},
journal= {arXiv preprint arXiv:0706.4450},
year = {2013}
}