摘要翻译:
高性能计算(HPC)是一个非常有吸引力和相对较新的研究领域,在许多应用中取得了很好的结果。本文将HPC用于美式期权的定价。虽然美式期权在计算金融中非常重要;它们的估值非常具有挑战性,尤其是当使用蒙特卡罗模拟技术时。为了得到这类期权的最准确的价格,我们使用了准蒙特卡罗模拟,它给出了最佳的收敛性。并在GPU和CPU上实现了该算法。另外,采用CUDA架构来利用GPU的能力和能力来并行执行算法,并将其与CPU上的串行实现进行了比较。最后,本文给出了计算金融中应用高性能计算的原因和优势。
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英文标题:
《Using high performance computing and Monte Carlo simulation for pricing
american options》
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作者:
Verche Cvetanoska, Toni Stojanovski
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最新提交年份:
2012
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Distributed, Parallel, and Cluster Computing 分布式、并行和集群计算
分类描述:Covers fault-tolerance, distributed algorithms, stabilility, parallel computation, and cluster computing. Roughly includes material in ACM Subject Classes C.1.2, C.1.4, C.2.4, D.1.3, D.4.5, D.4.7, E.1.
包括容错、分布式算法、稳定性、并行计算和集群计算。大致包括ACM学科类C.1.2、C.1.4、C.2.4、D.1.3、D.4.5、D.4.7、E.1中的材料。
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一级分类:Quantitative Finance 数量金融学
二级分类:Computational Finance 计算金融学
分类描述:Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法,包括蒙特卡罗,偏微分方程,格子和其他数值方法,并应用于金融建模
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英文摘要:
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 used. For getting the most accurate price for these types of options we use Quasi Monte Carlo simulation, which gives the best convergence. Furthermore, this algorithm is implemented on both GPU and CPU. Additionally, the CUDA architecture is used for harnessing the power and the capability of the GPU for executing the algorithm in parallel which is later compared with the serial implementation on the CPU. In conclusion this paper gives the reasons and the advantages of applying HPC in computational finance.
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PDF链接:
https://arxiv.org/pdf/1205.0106