D. Hendricks, D. Cieslakiewicz, D. Wilcox, T. Gebbie
During times of stock market turbulence, monitoring the intraday clustering behaviour of financial instruments allows one to better understand market characteristics and systemic risks. While genetic algorithms provide a versatile methodology for identifying such clusters, serial implementations are computationally intensive and can take a long time to converge to the global optimum. We implement a […]
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Scott Grauer-Gray, William Killian, Robert Searles, John Cavazos
The QuantLib library is a popular library used for many areas of computational finance. In this work, the parallel processing power of the GPU is used to accelerate QuantLib financial applications. Black-Scholes, Monte-Carlo, Bonds, and Repo code paths in QuantLib are accelerated using hand-written CUDA and OpenCL codes specifically targeted for the GPU. Additionally, HMPP […]
Mark Joselli, Jose Ricardo Silva Junior, Marcelo Zamith, Esteban Clua, Eduardo Soluri
The volume of banks data calculation is increasing each year with extraordinary scale and with that, new forms of computation is needed. High performance computing is a very attractive field for optimization such bank calculous, which can give promising results. This paper shows a implementation of know model for assessing the credit risk of a […]
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Qasim Nasar-Ullah
We describe a high performance parallel implementation of a derivative pricing model, within which we introduce a new parallel method for the calibration of the industry standard SABR (stochastic-alpha beta rho) stochastic volatility model using three strike inputs. SABR calibration involves a non-linear three dimensional minimisation and parallelisation is achieved by incorporating several assumptions unique […]
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Raj B Krishnamurthy, Ikubin Chin, Anjil Chinnapatlolla
This paper presents a comparison of parallelization frameworks for efficient execution of computational finance workloads. We use a Value-at-Risk (VaR) workload to evaluate OpenCL and OpenMP parallelization frameworks on multi-core CPUs as opposed to GPUs. In addition, we study the impact of SMT on performance using GCC (4.4) and IBM XLC (11.01) compilers for both […]
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Verche Cvetanoska, Toni Stojanovski
High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very significant in computational finance; their valuation is very challenging, especially when the Monte Carlo simulation techniques are […]
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Bhanu Pratap Sharma
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 […]
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Wen-mei W. Hwu
This is the second volume of Morgan Kaufmann’s GPU Computing Gems, offering an all-new set of insights, ideas, and practical ";hands-on"; skills from researchers and developers worldwide. Each chapter gives you a window into the work being performed across a variety of application domains, and the opportunity to witness the impact of parallel GPU computing […]
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Anson H.T. Tse, David B. Thomas, K.H. Tsoi, Wayne Luk
Arithmetic Asian options are financial derivatives which have the feature of path-dependency: they depend on the entire price path of the underlying asset, rather than just the instantaneous price. This path-dependency makes them difficult to price, as only computationally intensive Monte-Carlo methods can provide accurate prices. This paper proposes an FPGA-accelerated Asian option pricing solution, […]
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Bowen Zhang, Cornelis W. Oosterlee
In this paper, acceleration on the GPU for option pricing by the COS method is demonstrated. In particular, both European and Bermudan options will be discussed in detail. For Bermudan options, we consider both the Black-Scholes model and Levy processes of infinite activity. Moreover, the influence of the number of terms in the Fourier-cosine expansion, […]
Ren-Shuo Liu, Yun-Cheng Tsai, Chia-Lin Yang
Option pricing is an important problem in computational finance due to the fast-growing market and increasing complexity of options. For option pricing, a model is required to describe the price process of the underlying asset. The GARCH model is one of the prominent option pricing models since it can model stochastic volatility of the underlying […]
C.C. Douglas, Hyoseop Lee, Dongwoo Sheen
We introduce an inverse problem for the local volatility model in option pricing. We solve the problem using the Levenberg-Marquardt algorithm and use the notion of the Frechet derivative when calculating the Jacobian matrix. We analyze the existence of the Frechet derivative and its numerical computation. To reduce the computational time of the inverse problem, […]
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