Efficient High Performance Computing Framework for Short Rate Models

T. P. Dampahala, H. D. D. D. Premadasa, P. W. W. Ranasinghe, J. N. P. Weerasinghe, K. Wimalawarne
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Abstract

Many mathematical calculations in the field of computational finance consume a lot of time and resources for processing. Some of the Short rate models used in quantitative finance which have been taken into consideration in this paper have been optimized for performance within a cluster computing environment. The back-end cluster has been seamlessly integrated with an easy-to-use front-end which can be used by finance professionals who are not aware of the details of the computational and database cluster. Furthermore, many techniques that have been utilized to improve the efficiency of the models have also been described. This paper also describes the generalization of a High Performance Computing Cluster designed for One-factor Short rate models and how it can be used easily to be further extended for other mathematical models in quantitative finance. The ultimate objective is to come up with a generalized framework for quantitative finance.
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短期利率模型的高效高性能计算框架
计算金融领域的许多数学计算需要耗费大量的时间和资源进行处理。本文所考虑的定量金融中使用的一些短期利率模型已经在集群计算环境下进行了性能优化。后端集群已经与一个易于使用的前端无缝集成,可以供不了解计算和数据库集群细节的金融专业人士使用。此外,还描述了许多用于提高模型效率的技术。本文还描述了为单因素短期利率模型设计的高性能计算集群的泛化,以及如何轻松地将其进一步扩展到定量金融中的其他数学模型。最终目标是提出一个量化金融的通用框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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