Liquidity, Information, and Infrequently Traded Stocks






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    • Easley and Kiefer are from the Department of Economics, Cornell University. O'Hara is from the Johnson Graduate School of Management, Cornell University. Paperman is from the Department of Accounting, University of Washington. We thank an anonymous referee, Yakov Amihud, Joel Hasbrouck, Bruce Lehman, Ananth Madhavan, René Stulz, and seminar participants at Cornell University, the London Business School, Erasmus University, the Western Finance Association Meetings, and the JFI Conference on Market Microstructure, Northwestern University for helpful comments. We thank Colin Moriarity and James Shapiro of the New York Stock Exchange for technical assistance, and the Symposium on Infrequently Traded Stocks held at the London Business School for providing the impetus for this research. Easley and O'Hara gratefully acknowledge research support from Churchill College and the Department of Applied Economics, University of Cambridge, and Kiefer gratefully acknowledges support from the Center for Nonlinear Econometrics, University of Aarhus. This research is supported by National Science Foundation Grant SBR93–20889.


This article investigates whether differences in information-based trading can explain observed differences in spreads for active and infrequently traded stocks. Using a new empirical technique, we estimate the risk of information-based trading for a sample of New York Stock Exchange (NYSE) listed stocks. We use the information in trade data to determine how frequently new information occurs, the composition of trading when it does, and the depth of the market for different volume-decile stocks. Our most important empirical result is that the probability of information-based trading is lower for high volume stocks. Using regressions, we provide evidence of the economic importance of information-based trading on spreads.