 Toward real-time pricing of complex financial derivativesS. Ninomiya and S. Tezuka Applied Mathematical Finance, 1996, vol. 3, issue 1, 1-20 Abstract: In this paper, we investigate the feasibility of using low-discrepancy sequences to allow complex derivatives, such as mortgage-backed securities (MBSs) and exotic options, to be calculated considerably faster than is possible by using conventional Monte Carlo methods. In our experiments, we examine classical classes of low-discrepancy sequences, such as Halton, Sobol', and Faure sequences, as well as the very recent class called generalized Niederreiter sequences, in the light of the actual convergence rate of numerical integration with practical numbers of dimensions. Our results show that for the problems of pricing financial derivatives that we tested: (1) generalized Niederreiter sequences perform markedly better than both classical sequences and Monte Carlo methods; and (2) classical low-discrepancy sequences often perform worse than Monte Carlo methods. Finally, we discuss several important research issues from both practical and theoretical viewpoints. Keywords: low-discrepancy sequences; generalized Niederreiter sequences; Faure sequences; Sobol' sequences; financial derivatives (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:apmtfi:v:3:y:1996:i:1:p:1-20 Ordering information: This journal article can be ordered from DOI: 10.1080/13504869600000001 Access Statistics for this article Applied Mathematical Finance is currently edited by Professor Ben Hambly and Christoph Reisinger More articles in Applied Mathematical Finance from Taylor & Francis Journals |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.