Does Algorithmic Trading Reduce Information Acquisition?
研究发现算法交易虽然有助于将已有信息融入价格，但会减少价格中的信息总量，每增加一个标准差，价格信息含量下降9%到13%。
I demonstrate an important tension between acquiring information and incorporating it into asset prices. As a salient case, I analyze algorithmic trading (AT), which is typically associated with improved price efficiency. Using a new measure of the information content of prices and a comprehensive panel of 54, 879 stock-quarters of Securities and Exchange Commission (SEC) market data, I establish instead that the amount of information in prices decreases by 9% to 13% per standard deviation of AT activity and up to a month before scheduled disclosures. AT thus may reduce price informativeness despite its importance for translating available information into prices. Received May 21, 2016; editorial decision October 25, 2017 by Editor Itay Goldstein. Authors have furnished an Internet Appendix, which is available on the Oxford University PressWeb site next to the link to the final published paper online.