research-article

Efficient reconfigurable design for pricing asian options

Authors:

Anson H.T. Tse,

David B. Thomas,

K. H. Tsoi,

Wayne LukAuthors Info & Claims

ACM SIGARCH Computer Architecture News, Volume 38, Issue 4

Pages 14 - 20

https://doi.org/10.1145/1926367.1926371

Published: 14 January 2011 Publication History

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Abstract

Arithmetic Asian options are financial derivatives which have the feature of path-dependency: they depend on the entire price path of the underlying asset, rather than just the instantaneous price. This path-dependency makes them difficult to price, as only computationally intensive Monte-Carlo methods can provide accurate prices. This paper proposes an FPGA-accelerated Asian option pricing solution, using a highly-optimised parallel Monte-Carlo architecture. The proposed pipelined design is described parametrically, facilitating its re-use for different technologies. An implementation of this architecture in a Virtex-5 xc5vlx330t FPGA at 200MHz is 313 times faster than a multi-threaded software implementation running on a Intel Xeon E5420 quad-core CPU at 2.5GHz; it is also 2.2 times faster than the Tesla C1060 GPU at 1.3 GHz.

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Foroughi MBagherzadeh ARahmati DForoughi MGorgin S(2022)Financial Market Prediction Using Deep Neural Networks with Hardware Acceleration2022 12th International Conference on Computer and Knowledge Engineering (ICCKE)10.1109/ICCKE57176.2022.9959984(375-381)Online publication date: 17-Nov-2022
https://doi.org/10.1109/ICCKE57176.2022.9959984
Li YZhang LDai YSun Y(2021)A Word-length Optimized Parallel Framework for Accelerating Option Pricing Model2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00109(654-661)Online publication date: Dec-2021
https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00109
Tavakkoli AThomas D(2018)A High-Level Design Framework for the Automatic Generation of High-Throughput Systolic Binomial-Tree SolversIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2017.276155426:2(341-354)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1109/TVLSI.2017.2761554
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Efficient reconfigurable design for pricing asian options

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cover image ACM SIGARCH Computer Architecture News

ACM SIGARCH Computer Architecture News Volume 38, Issue 4

September 2010

96 pages

ISSN:0163-5964

DOI:10.1145/1926367

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Association for Computing Machinery

New York, NY, United States

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Published: 14 January 2011

Published in SIGARCH Volume 38, Issue 4

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Foroughi MBagherzadeh ARahmati DForoughi MGorgin S(2022)Financial Market Prediction Using Deep Neural Networks with Hardware Acceleration2022 12th International Conference on Computer and Knowledge Engineering (ICCKE)10.1109/ICCKE57176.2022.9959984(375-381)Online publication date: 17-Nov-2022
https://doi.org/10.1109/ICCKE57176.2022.9959984
Li YZhang LDai YSun Y(2021)A Word-length Optimized Parallel Framework for Accelerating Option Pricing Model2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys)10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00109(654-661)Online publication date: Dec-2021
https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00109
Tavakkoli AThomas D(2018)A High-Level Design Framework for the Automatic Generation of High-Throughput Systolic Binomial-Tree SolversIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2017.276155426:2(341-354)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1109/TVLSI.2017.2761554
Fabry PThomas D(2017)Efficient Reconfigurable Architecture for Pricing Exotic OptionsACM Transactions on Reconfigurable Technology and Systems10.1145/315822810:4(1-22)Online publication date: 22-Dec-2017
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Pham NAung KKumar A(2016)Automatic framework to generate reconfigurable accelerators for option pricing applications2016 International Conference on ReConFigurable Computing and FPGAs (ReConFig)10.1109/ReConFig.2016.7857157(1-8)Online publication date: Nov-2016
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Crookes DTrainor SJiang R(2016)An Environment for Rapid Derivatives Design and ExperimentationIEEE Journal of Selected Topics in Signal Processing10.1109/JSTSP.2016.259261910:6(1073-1082)Online publication date: Sep-2016
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Brugger CVarela JWehn NTang SKorn RNebel WAtienza D(2015)Reverse longstaff-schwartz american option pricing on hybrid CPU/FPGA systemsProceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition10.5555/2755753.2757182(1599-1602)Online publication date: 9-Mar-2015
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Varela JBrugger CSchryver CWehn NTang SOmland S(2015)Exploiting the brownian bridge technique to improve longstaff-schwartz american option pricing on FPGA systems2015 International Conference on ReConFigurable Computing and FPGAs (ReConFig)10.1109/ReConFig.2015.7393306(1-6)Online publication date: Dec-2015
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Varela JBrugger CTang SWehn NKorn R(2015)Pricing High-Dimensional American Options on Hybrid CPU/FPGA SystemsFPGA Based Accelerators for Financial Applications10.1007/978-3-319-15407-7_7(143-166)Online publication date: 2015
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Reconfigurable Control Variate Monte-Carlo Designs for Pricing Exotic Options

Exploring Reconfigurable Architectures for Tree-Based Option Pricing Models

Improved Parallel Randomized Quasi Monte Carlo Algorithm of Asian Option Pricing on MIC Architecture

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Reconfigurable Control Variate Monte-Carlo Designs for Pricing Exotic Options

Exploring Reconfigurable Architectures for Tree-Based Option Pricing Models

Improved Parallel Randomized Quasi Monte Carlo Algorithm of Asian Option Pricing on MIC Architecture

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