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Internet big data and capital markets: a literature review

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  • Minjian Ye

    (Sun Yat-Sen University)

  • Guangzhong Li

    (Sun Yat-Sen University)

Abstract

Background Research in various academic disciplines has undergone tremendous changes in the era of big data. Everyone is talking about big data nowadays, but how exactly is it being applied in research on financial studies? Results This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature. In addition, it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets. Conclusion (1) Internet big data sources related to present capital market research can be categorized into forum-type data, microblog-type data and search class data. (2) As for research about investors’ sentiments on the basis of Internet big data, the main methods of sentiment analysis include building an inventory of lexical categories, using dictionaries for analysis of lexical categories, and machine learning. (3) Many studies address whether Internet big data can predict capital markets. However, they reach no consistent conclusions, which could be due to limitations of sample and analysis method used. (4) Data collection technique and analysis methods require further improvements.

Suggested Citation

  • Minjian Ye & Guangzhong Li, 2017. "Internet big data and capital markets: a literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-18, December.
    • Handle: RePEc:spr:fininn:v:3:y:2017:i:1:d:10.1186_s40854-017-0056-y
    DOI: 10.1186/s40854-017-0056-y
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    6. Manik Sharma & Samriti Sharma & Gurvinder Singh, 2018. "Performance Analysis of Statistical and Supervised Learning Techniques in Stock Data Mining," Data, MDPI, vol. 3(4), pages 1-16, November.

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