Does collecting regulatory financial information with the help of automated computer algorithms (robots) affect the stock market? Using the EDGAR Server Log data set, I construct rm-level measures of information acquisition by robots and non-robots and show that robots are extensively used for information acquisition when new information becomes available. The SEC's mandate regarding interactive data leads to a notable increase in information demand, consistent with decreased information acquisition costs for standardized regulatory financial information in XBRL-format. A higher relative importance of robots acquiring information about a firm combined with the XBRL adoption is associated with a consequent increase in trading volume, smaller bid-ask spreads, lower volatility, positive cumulative abnormal return and increased volume coefficient of variation. The findings are consistent with the idea that automation and standardization benets informed investors disproportionately more than uninformed traders.
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We investigate how the structure of liabilities affects financial intermediaries’ asset holdings. Following a change in regulation that made prime money market funds’ liabilities less money-like, safer funds exited the industry. The remaining funds increased the riskiness of their portfolios in response to an increase in the sensitivity of flows to performance. Consequently, issuers with lower credit risk have less access to funding from US money market funds. These findings indicate that regulation is crucial for liquidity creation and provide evidence for theories highlighting that financial intermediaries’ assets and liabilities are jointly determined.
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Mandatory second year course for the BSc Program in Business and Economics at the Stockholm School of Economics.