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Big Data in Finance
[Institutional order handling and broker-affiliated trading venues]

Author

Listed:
  • Itay Goldstein
  • Chester S Spatt
  • Mao Ye

Abstract

Big data is revolutionizing the finance industry and has the potential to significantly shape future research in finance. This special issue contains papers following the 2019 NBER-RFS Conference on Big Data. In this introduction to the special issue, we define the “big data” phenomenon as a combination of three features: large size, high dimension, and complex structure. Using the papers in the special issue, we discuss how new research builds on these features to push the frontier on fundamental questions across areas in finance—including corporate finance, market microstructure, and asset pricing. Finally, we offer some thoughts for future research directions.

Suggested Citation

  • Itay Goldstein & Chester S Spatt & Mao Ye, 2021. "Big Data in Finance [Institutional order handling and broker-affiliated trading venues]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3213-3225.
    • Handle: RePEc:oup:rfinst:v:34:y:2021:i:7:p:3213-3225.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhab038
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    Citations

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    Cited by:

    1. Edmans, Alex & Fernandez-Perez, Adrian & Garel, Alexandre & Indriawan, Ivan, 2022. "Music sentiment and stock returns around the world," Journal of Financial Economics, Elsevier, vol. 145(2), pages 234-254.
    2. Mahsa Samsami & Ralf Wagner, 2021. "Investment Decisions with Endogeneity: A Dirichlet Tree Analysis," JRFM, MDPI, vol. 14(7), pages 1-19, July.
    3. Li, Ang & Liu, Mark & Sheather, Simon, 2023. "Predicting stock splits using ensemble machine learning and SMOTE oversampling," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    4. Wang, Yichen & Hu, Jun & Chen, Jia, 2023. "Does Fintech facilitate cross-border M&As? Evidence from Chinese A-share listed firms," International Review of Financial Analysis, Elsevier, vol. 85(C).
    5. Niu, Yuhao & Wang, Sai & Wen, Wen & Li, Sifei, 2023. "Does digital transformation speed up dynamic capital structure adjustment? Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    6. Nam, Rachel J., 2022. "Open banking and customer data sharing: Implications for FinTech borrowers," SAFE Working Paper Series 364, Leibniz Institute for Financial Research SAFE.
    7. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    8. Sun, Yue & Chai, Nana & Dong, Yizhe & Shi, Baofeng, 2022. "Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision-making approach," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1158-1172.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G3 - Financial Economics - - Corporate Finance and Governance

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