Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/53796
Title: | Monte Carlo scalable algorithms for Computational Finance | Authors: | Alexandrov, V. N. Gonzalez Martel, Christian Strassburg, J. |
UNESCO Clasification: | 120302 Lenguajes algorítmicos | Keywords: | Scalable algorithms Computational finance Monte Carlo |
Issue Date: | 2011 | Publisher: | 1877-0509 | Journal: | Procedia Computer Science | Conference: | 11th International Conference on Computational Science, ICCS 2011 | Abstract: | With the latest developments in the area of advanced computer architectures, we are already seeing large scale machines at petascale level and we are faced with the exascale computing challenge. All these require scalability at system, algorithmic and mathematical model level. In particular, e_cient scalable algorithms are required to bridge the performance gap. In this paper, examples of various approaches of designing scalable algorithms for such advanced architectures will be given. We will briefly present our approach to Monte Carlo scalable algorithms for Linear Algebra and explain how these approaches are extended to the field of Computational Finance. Implementation examples will be presented using Linear Algebra Problems and problems from Computational Finance. Furthermore, the corresponding properties of these algorithms will be outlined and discussed. | URI: | http://hdl.handle.net/10553/53796 | ISSN: | 1877-0509 | DOI: | 10.1016/j.procs.2011.04.185 | Source: | Proceedings Of The International Conference On Computational Science (Iccs) [ISSN 1877-0509], v. 4, p. 1708-1715 |
Appears in Collections: | Actas de congresos |
SCOPUSTM
Citations
4
checked on Dec 15, 2024
WEB OF SCIENCETM
Citations
6
checked on Dec 15, 2024
Page view(s)
59
checked on Jan 27, 2024
Google ScholarTM
Check
Altmetric
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.