American options and the LSM algorithm: quasi-random sequences and Brownian bridges

Suneal K. Chaudhary

Journal of Computational Finance

Abstract: ABSTRACT The least-squares Monte Carlo (LSM) algorithm of Longstaff and Schwartz (2001) is a method for Monte Carlo valuation of the price of American options. We use quasi-random sequences to generate asset prices which follow geometric Brownian motions, and obtain a significant increase in the rate of convergence of American min-puts and American–Bermuda–Asian calls. Using the Brownian-bridge formula, we present a method for reducing the memory requirements from O(N ×M × d) to O(Nd log(M)) for quasi-random sequences, where N is the number of paths, M is the number of timesteps and d is the number of assets, for example, in a min-put.

References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.risk.net/journal-of-computational-fina ... and-brownian-bridges (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:journ0:2160445

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 ().