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Long-Run Growth of Financial Data Technology

Author

Listed:
  • Maryam Farboodi
  • Laura Veldkamp

Abstract

"Big data" financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others' information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others' demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies. However, in the long run, as data processing technology becomes increasingly advanced, both types of data continue to be processed. Two competing forces keep the data economy in balance: data resolve investment risk, but future data create risk. The efficiency results that follow from these competing forces upend two pieces of common wisdom: our results offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient.

Suggested Citation

  • Maryam Farboodi & Laura Veldkamp, 2020. "Long-Run Growth of Financial Data Technology," American Economic Review, American Economic Association, vol. 110(8), pages 2485-2523, August.
    • Handle: RePEc:aea:aecrev:v:110:y:2020:i:8:p:2485-2523
    DOI: 10.1257/aer.20171349
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    Citations

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    Cited by:

    1. Jérôme Dugast & Thierry Foucault, 2020. "Equilibrium Data Mining and Data Abundance," Post-Print hal-02933315, HAL.
    2. Alejandra Bellatin & Stephanie Houle, 2021. "Overlooking the online world: Does mismeasurement of the digital economy explain the productivity slowdown?," Staff Analytical Notes 2021-10, Bank of Canada.
    3. Luo, Sumei & Sun, Yongkun & Zhou, Rui, 2022. "Can fintech innovation promote household consumption? Evidence from China family panel studies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Lin William Cong & Danxia Xie & Longtian Zhang, 2021. "Knowledge Accumulation, Privacy, and Growth in a Data Economy," Management Science, INFORMS, vol. 67(10), pages 6480-6492, October.
    5. Yang Hao, 2023. "Financial Market with Learning from Price under Knightian Uncertainty," Working Papers hal-03686748, HAL.
    6. Zhou, Xuan & Kang, Junqing, 2023. "Searching for ESG Information: Heterogeneous Preferences and Information Acquisition," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    7. Xiaoman, Jin & Qing, Li & Jun, Wang & Jingmei, Zhao, 2023. "Voice or noise? Repetitive information and stock performance," Finance Research Letters, Elsevier, vol. 52(C).
    8. Boot, Arnoud & Hoffmann, Peter & Laeven, Luc & Ratnovski, Lev, 2021. "Fintech: what’s old, what’s new?," Journal of Financial Stability, Elsevier, vol. 53(C).
    9. Yannelis, Constantine & Zhang, Anthony Lee, 2023. "Competition and selection in credit markets," Journal of Financial Economics, Elsevier, vol. 150(2).
    10. Cheng, Maoyong & Qu, Yang, 2023. "The false prosperity and promising future: Effects of data resources on bank efficiency," International Review of Financial Analysis, Elsevier, vol. 89(C).
    11. Adlai Fisher & Charles Martineau & Jinfei Sheng, 2022. "Macroeconomic Attention and Announcement Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 35(11), pages 5057-5093.
    12. Russ, David, 2022. "Multidimensional noise and non-fundamental information diversity," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    13. Shiyang Huang & Yan Xiong & Liyan Yang, 2022. "Skill Acquisition and Data Sales," Management Science, INFORMS, vol. 68(8), pages 6116-6144, August.
    14. Kang, Junqing, 2022. "Comments on “Government intervention through informed trading in financial markets” by Shao’an Huang, Zhigang Qiu, Gaowang Wang and Xiaodan Wang," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).

    More about this item

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • 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
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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