We use information from over 2 million trading strategies randomly generated using real data and from strategies that survive the publication process to infer the statistical properties of the set of strategies that could have been studied by researchers. Using this set, we compute t-statistic thresholds that control for multiple hypothesis testing, when searching for anomalies, at 3.8 and 3.4 for time-series and cross-sectional regressions, respectively. We estimate the expected proportion of false rejections that researchers would produce if they failed to account for multiple hypothesis testing to be about 45%.

This paper explores liquidity movements in stock and Treasury bond markets over a period of more than 1800 trading days. Cross-market dynamics in liquidity are documented by estimating a vector autoregressive model for liquidity (that is, bid-ask spreads and depth), returns, volatility, and order flow in the stock and bond markets. We find that a shock to quoted spreads in one market affects the spreads in both markets, and that return volatility is an important driver of liquidity. Innovations to stock and bond market liquidity and volatility prove to be significantly correlated, suggesting that common factors drive liquidity and volatility in both markets. Monetary expansion increases equity market liquidity during periods of financial crises, and unexpected increases (decreases) in the federal funds rate lead to decreases (increases) in liquidity and increases (decreases) in stock and bond volatility. Finally, we find that flows to the stock and government bond sectors play an important role in forecasting stock and bond liquidity. The results establish a link between 'macro' liquidity, or money flows, and 'micro' or transactions liquidity.

Prices of the highly liquid S&P 500 exchange-traded fund (SPY) and the E-mini future (ES) respond to macroeconomic announcement surprises within five milliseconds, with trading intensity increasing over 100-fold following the news release. However, profits from trading quickly are relatively small, roughly $$$19,000 ($$$50,000) per event for SPY (ES). Although the speed of information incorporation has increased in recent years, profits have not. Order flow has become less informative, consistent with prices responding directly to news rather than indirectly through trading. Our evidence indicates that low-latency liquidity demanders do not benefit materially from short-term monopolistic access to information. Received April 18, 2017; editorial decision November 4, 2017 by Editor Andrew Karolyi.