Latency critical big data computing in finance

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)33-41
Number of pages9
JournalJournal of Finance and Data Science
Volume1
Issue number1
DOIs
Publication statusPublished - Dec 2015
Externally publishedYes

Keywords

  • Big data
  • Financial analytics
  • Latency

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