A multi-point distributed random variable accelerator for Monte Carlo simulation in finance

Liberati, NB; Platen, E; Martini, F; Piccardi, M

A multi-point distributed random variable accelerator for Monte Carlo simulation in finance

Liberati, NB Platen, E

Martini, F Piccardi, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 5th International Conference on Intelligent Systems Design and Applications 2005, ISDA '05, 2005, 2005 pp. 532 - 537
Issue Date:: 2005-12-01

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Field	Value	Language
dc.contributor.author	Liberati, NB	en_US
dc.contributor.author	Platen, E https://orcid.org/0000-0003-4595-3123	en_US
dc.contributor.author	Martini, F	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2005-12-01	en_US
dc.identifier.citation	Proceedings - 5th International Conference on Intelligent Systems Design and Applications 2005, ISDA '05, 2005, 2005 pp. 532 - 537	en_US
dc.identifier.isbn	0769522866	en_US
dc.identifier.isbn	9780769522869	en_US
dc.identifier.uri	http://hdl.handle.net/10453/3026
dc.description.abstract	The pricing and hedging of complex derivative securities via Monte Carlo simulations of stochastic differential equations constitutes an intensive computational task. To achieve "real time" execution, as often required by financial institutions, one needs highly efficient implementations of the multi-point distributed random variables underlying the simulations. In this paper a fast and flexible dedicated hardware solution is proposed. A comparative performance analysis demonstrates that the hardware solution is bottleneck-free and flexible, and significantly increases the computational efficiency of the software solution. © 2005 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0343913
dc.relation.ispartof	Proceedings - 5th International Conference on Intelligent Systems Design and Applications 2005, ISDA '05	en_US
dc.relation.isbasedon	10.1109/ISDA.2005.11	en_US
dc.title	A multi-point distributed random variable accelerator for Monte Carlo simulation in finance	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2005	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Wroclaw, Poland	en_US
dc.location.activity	Wroclaw, POLAND
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	2005	en_US

Abstract:

The pricing and hedging of complex derivative securities via Monte Carlo simulations of stochastic differential equations constitutes an intensive computational task. To achieve "real time" execution, as often required by financial institutions, one needs highly efficient implementations of the multi-point distributed random variables underlying the simulations. In this paper a fast and flexible dedicated hardware solution is proposed. A comparative performance analysis demonstrates that the hardware solution is bottleneck-free and flexible, and significantly increases the computational efficiency of the software solution. © 2005 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/3026