Portfolio Management Using Particle Swarm Optimization on GPU

Mathematical models like the Black-Scholes-Merton model used to price options approximately for simple and plain options in the form of closed form solution. The market is flooded with various styles of options, which are difficult to price. Numerical techniques used for pricing take exorbitant time...

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Bibliographic Details
Published in:2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications pp. 103 - 110
Main Authors: Sharma, B., Thulasiram, R. K., Thulasiraman, P.
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2012
Subjects:
Contracts
Europe
GPU
Graphics processing unit
Instruction sets
Mathematical model
Normalized PSO
Option Pricing
Particle Swarm Optimization (PSO)
Portfolio Management
Portfolios
Pricing
ISBN:1467316318, 9781467316316
ISSN:2158-9178
Online Access:Get full text
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Summary:Mathematical models like the Black-Scholes-Merton model used to price options approximately for simple and plain options in the form of closed form solution. The market is flooded with various styles of options, which are difficult to price. Numerical techniques used for pricing take exorbitant time for reasonable accuracy in pricing results. Heuristic approaches such as Particle swarm optimization (PSO) have been proposed for option pricing, which provide same or better results for simple options than that of numerical techniques at much less computational cost (time). In this work, we first investigate the characteristics of PSO for option pricing and propose improvements to PSO modeling, which reduces the number of PSO parameters without loss of generality of the financial application under study. We have used our improved PSO (called NPSO) model to price complex chooser option, one of the complicated options in the market. Cooperation among particles of the NPSO helps reach the solution in less time. Interest in diversifying investments stems from the necessity to avert risk involved in any single type of investments. The complex chooser option is shown to exhibit the characteristics of a financial portfolio. As a further study, we have used NPSO for portfolio optimization. We have implemented our NPSO model in the state-of-the-art multi-core Graphics processing units (GPU) platform and show that the computational time can be significantly reduced.
ISBN:1467316318
9781467316316
ISSN:2158-9178
DOI:10.1109/ISPA.2012.22