I study how arbitrage affects liquidity by analyzing several billion trades in the American Depositary Receipt (ADR) market from 2001 to 2016. Price deviations persist, on average, for 12 min, and mainly arise because of price pressure. Impulse response functions estimated at 1 min intervals indicate that a positive shock to arbitrage—simultaneous trades of the ADR and the home-market share in the opposite direction—decreases deviations and bid-ask spreads. I confirm these findings by exploiting institutional details that create exogenous variation in the impediments to arbitrage across days. Overall, these results suggest that arbitrage decreases price pressure and provides liquidity.

We propose a new private information measure based on a model of strategic trade optimization in the cross section of securities. Investors receive liquidity and private information shocks and optimize trading across securities, accounting for price impact (Kyle’s λ). The model yields a simple private information measure: λ×OIB (order imbalance). Intuitively, order imbalance is more likely to be information-driven when trading is expensive. We validate our measure by showing that it is greater for smaller firms with higher analyst dispersion, peaks with insider trades, helps explain return reversals, predicts return volatility, and increases before M&A announcements and after analyst coverage terminations.

We study the dynamics of high-frequency market efficiency measures. We provide evidence that these measures comove across stocks and with each other, suggesting the existence of a systematic market efficiency component. In vector autoregressions, we show that shocks to funding liquidity (the TED spread), hedge fund assets under management, and a proxy for algorithmic trading are significantly associated with systematic market efficiency. Thus, stock market efficiency is prone to systematic fluctuations, and, consistent with recent theories, events and policies that impact funding liquidity can affect the aggregate degree of price efficiency.

We study the dynamics of high-frequency market efficiency measures. We provide evidence that these measures comove across stocks and with each other, suggesting the existence of a systematic market efficiency component. In vector autoregressions, we show that shocks to funding liquidity (the TED spread), hedge fund assets under management, and a proxy for algorithmic trading are significantly associated with systematic market efficiency. Thus, stock market efficiency is prone to systematic fluctuations, and, consistent with recent theories, events and policies that impact funding liquidity can affect the aggregate degree of price efficiency.

The capital asset pricing model (CAPM) performs poorly overall, as market risk (beta) is weakly related to 24-h returns. This is because stock prices behave very differently with respect to their sensitivity to beta when markets are open for trading versus when they are closed. Stock returns are positively related to beta overnight, whereas returns are negatively related to beta during the trading day. These day-night relations hold for beta-sorted portfolios and individual stocks in the US and internationally as well as for industry and book-to-market portfolios and cash flow and discount rate beta-sorted portfolios. In addition to the change in slope of returns with respect to beta, the implied risk-free rate differs significantly between night and day. Consistent with this, returns on US Treasury futures differ significantly between night and day.

Short-term traders could affect the informativeness of stock prices about long-run fundamentals. Less (more) short-termism may thus induce managers to rely more (less) on stock prices in real investment decisions. Supporting this notion, we show that the investment-to-price sensitivity is inversely related to two short-termism proxies (controlling for firm size): institutional churn and liquidity. We confirm this finding using decimalization and an increase in mutual fund disclosure frequency as exogenous shocks to short-termism. Furthermore, short-termism is associated with an increased likelihood of voluntary capital expenditure forecasts by managers, suggesting a greater tendency to solicit market feedback when short-termism is high.

Using limit order books across all US exchanges, we show that while liquidity for small orders (e.g., the quoted and effective spreads) decreases, liquidity for large orders (e.g., the cumulative depth and the price impact of multiple trades) improves after the implementation of the Tick Size Pilot Program. We find significant spillover effects on liquidity for small and large orders that extend beyond the top of the book. Finally, we show that the pilot program results in an improvement in pricing efficiency, an increase in trade size, and a decrease in the number of trades.