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Long Run Growth of Financial Technology

Listed author(s):
  • Maryam Farboodi
  • Laura Veldkamp

In most sectors, technological progress boosts efficiency. But financial technology and the associated data-intensive trading strategies have been blamed for market inefficiency. A key cause for concern is that better technology might induce traders to extract other's information from order flow data mining, rather than produce information themselves. Defenders of these new trading strategies argue that they provide liquidity by identifying uninformed orders and taking the other side of their trades. We adopt the lens of long-run growth to understand how improvements in financial technology shape information choices, trading strategies and market efficiency, as measured by price informativeness and market liquidity. We find that unbiased technological change can explain a market-wide shift in data collection and trading strategies. But our findings also cast doubt on common wisdom. First, although extracting information from order flow does crowd out production of fundamental information, this does not compromise price informativeness. Second, although taking the opposite side of uninformed trades is typically called "providing liquidity," the rise of such trading strategies does not necessarily improve liquidity in the market as a whole.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 23457.

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Date of creation: May 2017
Handle: RePEc:nbr:nberwo:23457
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  1. Manzano, Carolina & Vives, Xavier, 2011. "Public and private learning from prices, strategic substitutability and complementarity, and equilibrium multiplicity," Journal of Mathematical Economics, Elsevier, vol. 47(3), pages 346-369.
  2. Martin Lettau & Sydney C. Ludvigson & Jessica A. Wachter, 2008. "The Declining Equity Premium: What Role Does Macroeconomic Risk Play?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1653-1687, July.
  3. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," Review of Economic Studies, Oxford University Press, vol. 60(2), pages 249-282.
  4. Banerjee, Snehal & Green, Brett, 2015. "Signal or noise? Uncertainty and learning about whether other traders are informed," Journal of Financial Economics, Elsevier, vol. 117(2), pages 398-423.
  5. Marcin Kacperczyk & Jaromir B. Nosal & Luminita Stevens, 2014. "Investor Sophistication and Capital Income Inequality," NBER Working Papers 20246, National Bureau of Economic Research, Inc.
  6. Vincent Glode & Richard C. Green & Richard Lowery, 2012. "Financial Expertise as an Arms Race," Journal of Finance, American Finance Association, vol. 67(5), pages 1723-1759, October.
  7. Jayant Vivek Ganguli & Liyan Yang, 2009. "Complementarities, Multiplicity, and Supply Information," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 90-115, March.
  8. Vanasco, Victoria & Asriyan, Vladimir, 2014. "Informed Intermediation over the Cycle," Research Papers 3235, Stanford University, Graduate School of Business.
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