I consider a market microstructure model in which the rates of public and private informa? tion arrival are probabilistic. The latter depends on the availability of private information that is stochastically changing over time. In equilibrium, traders estimate the availability of private information using past periods' trading volume and use this information to adjust their strategies. The time-series properties include contemporaneous correlation between price variability and volume and autocorrelation in price variability (similar to GARCH). The model explains why trading volume contains useful information for predicting volatil? ity and provides predictions on the limit and market order placement strategies of traders.

We present a theory of the linkages between corporate governance, corporate finance, and the real sector of an economy. Using a structural model of industry equilibrium with endogenous entry, we show that poor corporate governance leads to low levels of competition, and to firms with high insider ownership and leverage. In contrast, good corporate governance promotes the adoption of more efficient technologies and development of sectors more exposed to moral hazard. We use our model to study equity market liberalization, and we show that liberalizations facilitate entry and adoption of more productive technologies, especially in countries with good corporate governance.

We show that an increase in a stock’s breadth of institutional ownership or turnover is followed by a significant, but temporary, increase in its CAPM beta estimate and a decrease in its CAPM alpha. The increasing effect of breadth of ownership on beta estimates is mainly driven by short-term investors. These transitory trading-activity-driven components of beta estimates contribute to the empirical failure of the CAPM and the large returns to long-short portfolios that bet against beta. Relations between ownership breadth, turnover, and betas, which we document, help explain the puzzling fact that, on average, betas increase after seasoned equity offerings and stock splits and decrease after stock repurchases.Received November 26, 2015; editorial decision February 17, 2017 by Editor Jeffrey Pontiff.

We measure funding constraints in currency markets by deviations in the covered interest rate parity and funding risk by the standard deviation of the magnitude of the funding constraints. Empirically, funding risk is driven by financial sector conditions in the low interest rate countries, oil price, and the actions of the main central banks. Since 2008, funding risk has affected currency carry trading activity, carry trade returns, correlation between carry trade long and short currencies, relative equity returns, and the economic growth in the carry trade long and short countries. We develop a theory of currency markets under funding constraints to explain the phenomena. The model has additional testable implications: For instance, as funding constraints start to bind, it predicts that both the investment and the funding currencies crash relative to a safe asset. This result is observable empirically when we use gold to proxy for the safe asset.

In this paper, we study a two-country general equilibrium model with partially segmented financial markets, where hedge funds emerge endogenously. Empirically, we show that the hedge fund investment strategy predicted by our model, which we call the “risk-adjusted carry trade” strategy, explains more than 16% of the overall hedge fund index returns and more than 33% of the fixed income arbitrage sub-index returns. The flow of new money to hedge funds affects market interest rates, exchange rates, and both the hedge funds’ contemporaneous and expected future returns as predicted by the model.

We document a new phenomenon in bond and equity markets that we call cross-asset time series momentum. Using data from 20 countries, we show that past bond market returns are positive predictors of future equity market returns and past equity market returns are negative predictors of future bond market returns. We use this predictability to construct a diversified cross-asset time series momentum portfolio that yields a Sharpe ratio 45% higher than a standard time series momentum portfolio. We present evidence that time series momentum and cross-asset time series momentum are driven by slow-moving capital in bond and equity markets.

Some mutual funds act as contrarian traders, earning returns in the stock market by providing liquidity, while others demand liquidity and suffer costs of immediacy. The funds’ liquidity demand has increased over time. On average, the mutual funds’ costs of immediacy exceed their returns from providing liquidity by 1.9% pa. High market beta funds, large cap funds, and funds exposed to momentum suffer over 2.5% pa. in costs of immediacy. Other results are that mutual funds’ average alpha becomes insignificant when the costs of immediacy are accounted for and in the cross-section, the funds’ costs of immediacy predict their alphas.

Regressing hedge funds’ returns on returns to a long–short contrarian trading strategy, a measure of the returns from providing liquidity, we find that hedge funds typically supply liquidity in the stock market. In the cross-section, strict redemption restrictions and large fund size increase funds’ propensity to supply liquidity. In time series, poor market liquidity and good funding conditions increase funds’ propensity to supply liquidity. Although the hedge funds typically supply liquidity, during crises they demand liquidity. We also find that increases in the amount of speculative capital improve market liquidity and reduce the amount of short-term return reversals and volatility.

We present broad-based evidence that the monthly payment cycle induces systematic patterns in liquid markets around the globe. First, we document temporary increases in the costs of debt and equity capital that coincide with key dates associated with month-end cash needs. Second, we present direct and indirect evidence on the role of institutions in the genesis of these patterns and derive estimates of the associated costs borne by market participants. Third, and finally, we investigate the limits to arbitrage that prevent markets from functioning efficiently. Our results indicate that many investors and their agents, including mutual funds, suffer from liquidity-related trading. Received January 16, 2018; editorial decision January 2, 2019 by Editor Robin Greenwood.