Quadratic Optimal Functional Quantization of Stochastic Processes and Numerical Applications

Gilles Pagès ()
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Gilles Pagès: Université Paris 6, Laboratoire de Probabilités et Modèles aléatoires, UMR 7599

A chapter in Monte Carlo and Quasi-Monte Carlo Methods 2006, 2008, pp 101-142 from Springer

Abstract: Summary 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.

Keywords: Brownian Motion; Gaussian Process; Voronoi Diagram; Fractional Brownian Motion; Quantization Error (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-74496-2_6

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DOI: 10.1007/978-3-540-74496-2_6

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