Mark S. Seasholes

The portfolio flows of international investors

This paper explores the behavior of daily, international portfolio flows into and out of 46 countries from 1994 through 1998. Our data are from State Street Bank & Trust and encompass over 3 million trades by client institutions. We find a number of interesting facts. First, we detect regional factors within the flows. Second, the flows are strongly persistent -- the persistence decays only slowly over time. Third, flows are strongly influenced by past returns, so that investor trend-following is apparent. Fourth forecasting power for future emerging market returns, but not for developed country returns. Fifth, we find the sensitivity of local stock prices to foreign inflows to be positive and determine that transitory inflows impact future returns negatively. Finally, we examine and reject that the positive covariance of returns and inflows is associated with an information disadvantage on the part of international investors.

Market Predictability and Non-Informational Trading

This paper studies the ability of non-informational order imbalances (buy minus sell volume) to predict daily stock returns at the market level. Using a model with three types of participants (an informed trader, liquidity traders, and a finite number of arbitrageurs), we derive predictions relating returns to lagged returns and lagged order imbalances. Empirical tests using New York Stock Exchange non-informational basket/portfolio trading data provide results consistent with adverse selection at the market-level, but no evidence of limited risk-bearing capacity. Finally, we establish that these market-wide non-informational order imbalances also affect individual stock return comovement by examining additions to the S&P500 Index.

Asset Price Dynamics with Limited Attention

We study how limited attention and inefficient risk sharing relate to stock prices deviating from a (random walk) efficient price. The Duffie (2010) inattention model is extended to include multiple investor types with varying attention levels. The model’s predictions are tested with New York Stock Exchange data. Eight percent of a stock’s daily idiosyncratic return variance and 25% of its monthly idiosyncratic variance are due to transitory price changes. The trading variables explain 32% of these changes. The model further explains contemporaneous, lead, and lag correlations among returns and the trading by institutions, individuals, and market makers.

Information Precision, Noise, and the Cross-Section of Stock Returns

We derive a cross-sectional asset pricing measure from a noisy multi-asset rational expectations equilibrium model. The measure is based on the time-series covariance of an asset’s returns and security prices. Empirically, stocks with a measure one standard deviation above and below the average have returns that dier by 0.36% the following month (4.44% per annum) which is statistically signicant at the 1%-level. Results remain signicant after including variables such as stock market capitalization, book-to-market ratio, and the probability of information-based trading. Our measure can be understood as a proxy for information risk and/or supply uncertainty. We show the two explanations are theoretically intertwined.

Trading Imbalances and the Relative Prices of Stock Pairs

This paper studies the relative prices of dual-class shares - i.e., equities from the same company that are listed on two different markets. Theoretically, frictions such as short-sale constraints and limited risk-bearing capacity can lead identical securities trading in different markets to experience large and volatile price differences. Using a sample of 43 companies with stocks listed in China (mainland) and Hong Kong, we link trading imbalances to these large and volatile price differences. A one standard deviation shock to imbalances in China (or Hong Kong) leads to 166 bp (or 122 bp) change in the stocks transitory price (at a weekly frequency). We further show that transitory variance represents 45% of a stocks total return variance in Hong Kong. Such a magnitude is surprisingly large considering the average companys market capitalization is over USD 12 billion and Hong Kong is considered to have a developed stock market.

Trading Imbalances, Liquidity, and the Law of One Price

This paper studies trading and prices of dual/cross-listed stocks (i.e., equities from a single company that trade in more than one country). We focus on PRC rms with shares listed in Shanghai and Hong Kong. well-publicized index tracks the average price disparity across the two exchanges and shows signi cant variation over time. We show that di erences in order imbalances (in Shanghai vs Hong Kong) explain contemporaneous changes in relative prices at daily and weekly frequencies. Our results help clarify liquidity-driven explanations from sentiment-based ones.