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Welcome
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My name is Vladimir Surkov and I am a 3rd year PhD student at the Department of Computer Science, University of Toronto. My research is in the area of numerical methods for partial integro-differential equations in conjunction with optimal control problems, arising in mathematical finance. My supervisors are Ken Jackson and Sebastian Jaimungal.
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Parallel Option Pricing with Fourier Space Time-stepping Method on Graphics Processing Units (October 8, 2007) [SSRN]
With the evolution of Graphics Processing Units (GPUs) into powerful and cost-efficient computing architectures, their range of application has expanded tremendously, especially in the area of computational finance. Current research in the area, however, is limited in terms of options priced and complexity of stock price models. This paper presents algorithms, based on the Fourier Space Time-stepping (FST) method, for pricing single and multi-asset European and American options with Levy underliers on a GPU. Furthermore, the single-asset pricing algorithm is parallelized to attain greater efficiency.
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Option Pricing with Regime Switching Levy Processes Using Fourier Space Time-stepping (with Ken Jackson and Sebastian Jaimungal) (April 30, 2007) [PDF] [BIB]
Although jump-diffusion and Levy models have been widely used in industry, the pricing partial-integro differential equations poses various difficulties for valuation. Diverse finite-difference schemes for solving the problem have been introduced in the literature. Invariably, the integral and diffusive terms are treated asymmetrically, large jumps are truncated and the methods are difficult to extend to higher dimensions. We present a new efficient transform approach for regime-switching Levy models which is applicable to a wide class of path-dependent options (such as Bermudan, barrier, and shout options) and options on multiple assets.
more...
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