Pricing path-dependent Bermudan options using Wiener chaos expansion: an embarrassingly parallel approach

Jérôme Lelong

Journal of Computational Finance

Abstract: In this work, we propose a new policy iteration algorithm for pricing Bermudan options when the payoff process cannot be written as a function of a lifted Markov process. Our approach is based on a modification of the well-known Longstaff–Schwartz algorithm: we basically replace the standard least squares regression with a Wiener chaos expansion. This not only allows us to deal with a non-Markovian setting but also breaks the bottleneck induced by the least squares regression, as the coefficients of the chaos expansion are given by scalar products on the L2(Ω) space and can therefore be approximated by independent Monte Carlo computations. This key feature enables us to propose an embarrassingly parallel algorithm to efficiently handle non-Markovian payoff.

References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.risk.net/journal-of-computational-fina ... ly-parallel-approach (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rsk:journ0:7714001

Access Statistics for this article

More articles in Journal of Computational Finance from Journal of Computational Finance
Bibliographic data for series maintained by Thomas Paine ().