This article explores cross-market liquidity dynamics by estimating a vector autoregressive model for liquidity (bid-ask spread and depth, returns, volatility, and order flow in the stock and Treasury bond markets). Innovations to stock and bond market liquidity and volatility are significantly correlated, implying that common factors drive liquidity and volatility in these markets. Volatility shocks are informative in predicting shifts in liquidity. During crisis periods, monetary expansions are associated with increased liquidity. Moreover, money flows to government bond funds forecast bond market liquidity. The results establish a link between "macro" liquidity, or money flows, and "micro" or transactions liquidity.

This paper examines the cross-sectional implications of the inflation illusion hypothesis for the post-earnings-announcement drift. The inflation illusion hypothesis suggests that stock market investors fail to incorporate inflation in forecasting future earnings growth rates, and this causes firms whose earnings growths are positively (negatively) related to inflation to be undervalued (overvalued). We argue and show that the sensitivity of earnings growth to inflation varies monotonically across stocks sorted on standardized unexpected earnings (SUE) and, consistent with the inflation illusion hypothesis, show that lagged inflation predicts future earnings growth, abnormal returns, and earnings announcement returns of SUE-sorted stocks. Interestingly, controlling for the return predictive ability of inflation weakens the ability of lagged SUE to predict future returns of SUE-sorted stocks.

Daily returns for stocks listed on the New York Exchange (NYSE) are not serially correlated while order imbalances on the same stocks are highly persistent. These empirical facts can be reconciled if sophisticated investors react to order imbalances within the trading day by undertaking enough countervailing trades to remove serial dependence over a daily horizon. How long does this actually take? The pattern of intra-day serial dependence reveals that it takes more than five minutes but less than sixty minutes.

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.