Long-Run Growth of Financial Data Technology
研究大数据金融技术如何影响交易者的信息选择和市场效率，发现技术进步会改变数据收集和交易策略，但长期中两种数据仍被处理，且效率结果颠覆了关于价格信息性和流动性提供作用的传统观点。
“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.