Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data

Authors

  • JOEL HASBROUCK

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    • Hasbrouck is with the Stern School of Business, New York University. For comments and suggestions I am grateful to the editor, the referee, Yakov Amihud, L̆ubos̆ Pástor, Bill Schwert, Jay Shanken, Kumar Venkataraman, Sunil Wahal, and seminar participants at the University of Rochester, the NBER Microstructure Research Group, the Federal Reserve Bank of New York, Yale University, the University of Maryland, the University of Utah, Emory University, and Southern Methodist University. All errors are my own responsibility. Earlier versions of this paper and an SAS data set containing the long-run Gibbs sampler estimates are available on my web site at http://www.stern.nyu.edu/~jhasbrou.


ABSTRACT

The effective cost of trading is usually estimated from transaction-level data. This study proposes a Gibbs estimate that is based on daily closing prices. In a validation sample, the daily Gibbs estimate achieves a correlation of 0.965 with the transaction-level estimate. When the Gibbs estimates are incorporated into asset pricing specifications over a long historical sample (1926 to 2006), the results suggest that effective cost (as a characteristic) is positively related to stock returns. The relation is strongest in January, but it appears to be distinct from size effects.

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