Valentin Mena Morales, Pierre-Henri Horrein, Amer Baghdadi, Erik Hochapfel, Sandrine Vaton
Energy efficiency of financial computations is a performance criterion that can no longer be dismissed, and is as crucial as raw acceleration and accuracy of the solution. In order to reduce the energy consumption of financial accelerators, FPGAs offer a good compromise with low power consumption and high parallelism. However, designing and prototyping an application […]
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Ketsarin Rungraung, Putchong Uthayopas
The task of trading orders matching in financial markets is a very challenging task since due to the speed of arriving request. In this paper, the GPUs technology and CUDA programming is explored as a potential technology to accelerate this task. The trading method in Automatic Order Matching (AOM) of Stock Exchange of Thailand (SET) […]
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Michael Benguigui, Francoise Baude
This article presents a multi-GPU adaptation of a specific Monte Carlo and classification based method for pricing American basket options, due to Picazo. The first part relates how to combine fine and coarse-grained parallelization to price American basket options. A dynamic strategy of kernel calibration is proposed. Doing so, our implementation on a reasonable size […]
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Shih Hau Tan
Value-at-Risk (VaR) provides information about global risk in trading. The request for high speed calculation about VaR is rising because financial institutions need to measure the risk in real time. Researchers in HPC also recently turned their attention on this kind of demanding applications. In this master thesis, we introduce two complementary and different strategies […]
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Ying Peng, Hui Liu, Shuzhen Yang, Bin Gong
In this paper, we explore the opportunity for solving high dimensional Backward Stochastic Differential Equations (BSDEs) on the GPU with application in high dimensional American option pricing. A Least Square Monte Carlo method based numerical algorithm for solving the BSDEs is studied and summarized in four phases. For the parallel GPU algorithms of different phases, […]
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Matthew Anker
We have seen more and more interest in taking advantage of GPUs to accelerate simulations. However, the RNGs driving these simulations tend to be existing CPU generators that have been converted for use on GPUs. The result is a generator that does not efficiently utilise the resources and constraints of that architecture. Consequently, the performance […]
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Ryan Saunders
Computer modelling has been used for a number of years already to aid financial institutions in making business decisions. One such decision that financial firms are often faced with involves setting fair prices for financial options. Since the process of option pricing can be computationally expensive, methods of optimising it are sought after. One popular […]
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Blesson Varghese, Andrew Rau-Chaplin
Aggregate Risk Analysis is a computationally intensive and a data intensive problem, thereby making the application of high-performance computing techniques interesting. In this paper, the design and implementation of a parallel Aggregate Risk Analysis algorithm on multi-core CPU and many-core GPU platforms are explored. The efficient computation of key risk measures, including Probable Maximum Loss […]
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Isaiah Hull
I introduce and evaluate a new stochastic simulation method for dynamic economic models. It is based on recent work in the operations research and engineering literatures (Van Roy et. al, 1997; Powell, 2007; Bertsekas, 2011). The baseline method involves rewriting the household’s dynamic program in terms of post-decision states. This makes it possible to choose […]
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Di Zhao, Jinhang Yu
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 […]
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Alexandru Voicu
Solving linear systems remains a key activity in of economics modelling, therefore making fast and accurate methods for computing solutions highly desirable. In this paper, a proof of concept C++ AMP implementation of an iterative method for solving linear systems, BiConjugate Gradient Stabilized (henceforth BiCGSTAB), is presented. The method relies on matrix and vector operations, […]
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Michael Bedford Taylor
Recently, the Bitcoin cryptocurrency has been an international sensation. This paper tells the story of Bitcoin hardware: how a group of early-adopters self-organized and financed the creation of an entire new industry, leading to the development of machines, including ASICs, that had orders of magnitude better performance than what Dell, Intel, NVidia, AMD or Xilinx […]
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