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Option pricing using Particle Swarm Optimization

Authors:

Parimala Thulasiraman,

Ruppa K. ThulasiramanAuthors Info & Claims

C3S2E '09: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering

Pages 267 - 272

https://doi.org/10.1145/1557626.1557669

Published: 19 May 2009 Publication History

Abstract

Option pricing is one of the challenging areas of computational finance. In this paper an attempt is made to apply Particle Swarm Optimization (PSO) for pricing options. PSO is one of the novel global search algorithm based on swarm intelligence. It is shown that PSO could be effectively used for single variate option pricing problem. The results are compared with standard classical Black-Scholes model for simple European options. With the current understanding from these initial experiments we suggest various avenues for further exploration.

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Cited By

Thulasiram RThulasiraman PPrasain HJha G(2016)Nature-inspired soft computing for financial option pricing using high-performance analyticsConcurrency and Computation: Practice & Experience10.1002/cpe.336028:3(707-728)Online publication date: 10-Mar-2016
https://dl.acm.org/doi/10.1002/cpe.3360
Prasain HJha GThulasiraman PThulasiram R(2010)A parallel Particle swarm optimization algorithm for option pricing2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)10.1109/IPDPSW.2010.5470706(1-7)Online publication date: Apr-2010
https://doi.org/10.1109/IPDPSW.2010.5470706
Swain A(undefined)American Put Option Pricing Using a Hybrid Evolutionary Computation and Monte-Carlo Simulation MethodSSRN Electronic Journal10.2139/ssrn.2975418
https://doi.org/10.2139/ssrn.2975418

Index Terms

Option pricing using Particle Swarm Optimization
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction

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cover image ACM Other conferences

C3S2E '09: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering

May 2009

266 pages

ISBN:9781605584010

DOI:10.1145/1557626

Editors:
Bipin C. Desai
Concordia University
,
Carson K. Leung
University of Manitoba

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 May 2009

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C3S2E '09

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Concordia University

C3S2E '09: Proceedings of the 2009 C3S2E conference

May 19 - 21, 2009

Quebec, Montreal, Canada

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Cited By

Thulasiram RThulasiraman PPrasain HJha G(2016)Nature-inspired soft computing for financial option pricing using high-performance analyticsConcurrency and Computation: Practice & Experience10.1002/cpe.336028:3(707-728)Online publication date: 10-Mar-2016
https://dl.acm.org/doi/10.1002/cpe.3360
Prasain HJha GThulasiraman PThulasiram R(2010)A parallel Particle swarm optimization algorithm for option pricing2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)10.1109/IPDPSW.2010.5470706(1-7)Online publication date: Apr-2010
https://doi.org/10.1109/IPDPSW.2010.5470706
Swain A(undefined)American Put Option Pricing Using a Hybrid Evolutionary Computation and Monte-Carlo Simulation MethodSSRN Electronic Journal10.2139/ssrn.2975418
https://doi.org/10.2139/ssrn.2975418

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