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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A Normalized Particle Swarm Optimization Algorithm to Price Complex Chooser Option and Accelerating its Performance with GPU

Sharma, Bhanu 07 December 2011 (has links)
An option is a financial instrument which derives its value from an underlying asset. There are a wide range of options traded today. Some are simple and plain, like the European options, while others are very difficult to evaluate. Both buyers and sellers continue to look for efficient algorithms and faster technology to price options for profit. In this thesis, I will first map the PSO parameters to the parameters in the option pricing problem. Then, I extend this to study pricing of complex chooser option. Further, I design a parallel algorithm that avails of the inherent concurrency in PSO while searching for a optimum solution. For implementation of my algorithm I used graphics processor unit (GPU). Analyzing the characteristics of PSO and option pricing, I propose a strategy to normalize some of the PSO parameters that helps in better understanding the sensitivity of various parameters on option pricing results.
2

A Normalized Particle Swarm Optimization Algorithm to Price Complex Chooser Option and Accelerating its Performance with GPU

Sharma, Bhanu 07 December 2011 (has links)
An option is a financial instrument which derives its value from an underlying asset. There are a wide range of options traded today. Some are simple and plain, like the European options, while others are very difficult to evaluate. Both buyers and sellers continue to look for efficient algorithms and faster technology to price options for profit. In this thesis, I will first map the PSO parameters to the parameters in the option pricing problem. Then, I extend this to study pricing of complex chooser option. Further, I design a parallel algorithm that avails of the inherent concurrency in PSO while searching for a optimum solution. For implementation of my algorithm I used graphics processor unit (GPU). Analyzing the characteristics of PSO and option pricing, I propose a strategy to normalize some of the PSO parameters that helps in better understanding the sensitivity of various parameters on option pricing results.

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