10577

Multi-GPU Acceleration of Black-Scholes Equation based Option Pricing

Di Zhao, Jinhang Yu
Ohio State University, Columbus, OH 43210
Ohio State University, 2013

@article{zhao2013multi,

   title={Multi-GPU Acceleration of Black-Scholes Equation based Option Pricing},

   author={Zhao, Di and Yu, Jinhang},

   year={2013}

}

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In high-frequency trading of option, "milliseconds earn or lose millions", the computational speed of predicting option price is the crucial factor for option traders to efficiently decide the price and evaluate the corresponding risk.Black-Scholes equation is a mathematical equation describing the option pricing over time. Multi-GPU is a recently developed platform for high-performance computing, which can be applied to high-efficient solving partial differential equation. In this paper, besides the conventional tridiagonal matrix algorithm, we develop multi-GPU block cyclic reduction based implicit scheme and multi-GPU block cyclic reduction based Crank-Nicolson scheme for Black-Scholes equation.Computational results show that, multi-GPU block cyclic reduction based schemes for Black-Scholes equation provides highly efficient prediction of option price along with iterations (time).Computational results also show that, multi-GPU significantly accelerate the solution speed of Black-Schole equations for option pricing.
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