Research on Nonlinear Correlation Tracking Technology of Financial Data Mining Based on Cloud Computing

Haozhe Jiao, Juntao Lin, Shibo Xu, Mingyang Zhou
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Abstract

Cloud computing is a commercial computing model that distributes computing tasks on a resource pool composed of a large number of computers, and can provide users with on-demand computing capabilities, storage capabilities, and application service capabilities; cloud computing provides storage and analysis of massive data Cheap and efficient solution. Financial data mining is a challenging research direction in the information society. The random nature of financial data makes it difficult to find the inherent rules hidden in the data. Furthermore, the properties of high-order correlation coefficients are discussed, and it is proved that high-order correlation can not only describe hidden nonlinear correlation information, but also describe the gap between linear correlation and independence. Therefore, the computational simplicity of high-order correlation can be used to track the time-varying nonlinear correlation characteristics in financial data in real time.
基于云计算的金融数据挖掘非线性相关跟踪技术研究
云计算是一种商业计算模型,它将计算任务分布在由大量计算机组成的资源池上,可以为用户提供按需计算能力、存储能力和应用服务能力;云计算为海量数据的存储和分析提供了廉价高效的解决方案。金融数据挖掘是信息社会中一个具有挑战性的研究方向。金融数据的随机性使得人们很难发现隐藏在数据中的内在规律。进一步讨论了高阶相关系数的性质,证明了高阶相关不仅可以描述隐藏的非线性相关信息,还可以描述线性相关与独立性之间的差距。因此,利用高阶相关的计算简单性,可以实时跟踪金融数据中的时变非线性相关特征。
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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