DP13278 Long Run Growth of Financial Data Technology
|Author(s):||Maryam Farboodi, Laura Veldkamp|
|Publication Date:||October 2018|
|Keyword(s):||Big Data, financial analysis, Fintech, growth, Information Acquisition, liquidity|
|Programme Areas:||Financial Economics, Macroeconomics and Growth|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=13278|
"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.