Long Run Growth of Financial Technology

Maryam Farboodi and Laura Veldkamp

No 23457, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: E2 G14 (search for similar items in EconPapers)
Date: 2017-05
New Economics Papers: this item is included in nep-dcm, nep-mac and nep-mst
Note: AP EFG
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Published as Maryam Farboodi & Laura Veldkamp, 2020. "Long-Run Growth of Financial Data Technology," American Economic Review, vol 110(8), pages 2485-2523.

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