Measuring the Information Content of Stock Trades



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    • Department of Finance, Leonard N. Stern School of Business, New York University. For comments on an earlier draft I am indebted to Larry Harris, Robert Wood, and seminar participants at Columbia University, Duke University, Pennsylvania State University, Southern Methodist University, and the Securities and Exchange Commission. I am especially indebted to the referee Larry Glosten for the illustrative microstructure model used in Section II and for his help in framing the argument of Section III. All errors are my own responsibility.


This paper suggests that the interactions of security trades and quote revisions be modeled as a vector autoregressive system. Within this framework, a trade's information effect may be meaningfully measured as the ultimate price impact of the trade innovation. Estimates for a sample of NYSE issues suggest: a trade's full price impact arrives only with a protracted lag; the impact is a positive and concave function of the trade size; large trades cause the spread to widen; trades occurring in the face of wide spreads have larger price impacts; and, information asymmetries are more significant for smaller firms.