Latency critical big data computing in finance

Xinhui Tian*, Rui Han, Lei Wang, Gang Lu, Jianfeng Zhan

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

46 引用 (Scopus)

摘要

Analytics based on big data computing can benefit today's banking and financial organizations on many aspects, and provide much valuable information for organizations to achieve more intelligent trading, which can help them to gain a great competitive advantage. However, the large scale of data and the critical latency analytics requirement in finance poses a great challenge for current system architecture. In this paper, we first analyze the challenges brought by the financial latency critical big data computing, then propose a discussion on how to handle these challenges from a perspective of multi-level system. We also talk about current researches on low latency in different system levels. The discussions and conclusions in the paper can be useful to the banking and financial organizations with the critical latency requirement of big data analytics.

源语言英语
页(从-至)33-41
页数9
期刊Journal of Finance and Data Science
1
1
DOI
出版状态已出版 - 12月 2015
已对外发布

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Tian, X., Han, R., Wang, L., Lu, G., & Zhan, J. (2015). Latency critical big data computing in finance. Journal of Finance and Data Science, 1(1), 33-41. https://doi.org/10.1016/j.jfds.2015.07.002