000			01530nam a22001457a 4500
999			_c515653 _d515653
008			210203b ||||| |||| 00| 0 eng d
100			_aFarboodi, Maryam and Veldkamp, Laura _924072
245			_aLong-run growth of financial data technology
260			_aThe American Economic Review
300			_a110(8), Aug, 2020: p.2485-2523
520			_a"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. – Reproduced
773			_aThe American Economic Review
906			_aFINANCE - DATA PROCESSING
942			_cAR