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Long Run Growth of Financial Data Technology

Maryam Farboodi and Laura Veldkamp

No 13278, CEPR Discussion Papers from C.E.P.R. Discussion Papers

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 produce information themselves. We allow agents to choose how much to learn about future asset values or about others' demands, and 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 more and more advanced, both types of data continue to be processed. What keeps the data economy in balance is two competing forces: Data resolves investment risk, but future data creates risk. The efficiency results that follow from these competing forces upend common wisdom. They offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient.

Keywords: Big Data; financial analysis; Fintech; growth; Information Acquisition; liquidity (search for similar items in EconPapers)
JEL-codes: E2 G14 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-big and nep-mac
Date: 2018-10
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