This paper explores daily international portfolio flows into and out of 44 countries from 1994 through 1998. We find several facts concerning the behavior of flows and their relationship with equity returns. First, we detect regional flow factors that have increased in importance through time. Second, the flows appear to be stationary, but far more persistent than returns. Third, flows are strongly influenced by past returns, a finding consistent with positive feedback trading by international investors. Fourth, inflows have positive forecasting power for future equity returns, and this power is statistically significant in emerging markets. Fifth, the sensitivity of local stock prices to foreign inflows is positive and large. Sixth, prices seem consistent with flow persistence, in that transitory inflows impact future returns negatively.

We test the implications of a multi-asset equilibrium model in which a finite number of risk-averse liquidity providers accommodate non-informational trading imbalances. These imbalances generate predictable reversals in stock returns. An imbalance in one stock also affects the prices of other stocks. The magnitude of the cross-stock price pressure depends on the correlations of the stocks’ underlying cash flows. The model implies that non-informational trading increases the volatility of stock returns. We confirm the model's implications using data from the Taiwan Stock Exchange.

This paper mathematically transforms unobservable rational expectation equilibrium model parameters (information precision and supply uncertainty) into a single variable that is correlated with expected returns and that can be estimated with recently observed data. Our variable can be used to explain the cross section of returns in theoretical, numerical, and empirical analyses. Using Center for Research in Security Prices data, we show that a −1σ to +1σ change in our variable is associated with a 0.31% difference in average returns the following month (equaling 3.78% per annum). The results are statistically significant at the 1% level. Our results remain economically and statistically significant after controlling for stocks' market capitalizations, book-to-market ratios, liquidities, and the probabilities of information-based trading.