Abstract

We estimate the conditional distribution of trade-to-trade price changes using ordered probit, a statistical model for discrete random variables. This approach recognizes that transaction price changes occur in discrete increments, typically eighths of a dollar, and occur at irregularly-spaced time intervals. Unlike existing models of discrete transactions prices, ordered probit can quantify the effects of other economic variables like volume, past price changes, and the time between trades on price changes. Using 1988 transactions data for over 100 randomly chosen U.S. stocks, we estimate the ordered probit model via maximum likelihood and use the parameter estimates to measure several transaction-related quantities, such as the price impact of trades of a given size, the tendency towards price reversals from one transaction to the next, and the empirical significance of price discreteness.

Keywords

EconometricsOrdered probitEconomicsProbit modelProbitLiberian dollarTransaction costStock (firearms)Database transactionTransaction dataMicroeconomicsComputer scienceFinance

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Year
2003
Type
article
Citations
436
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Jerry A. Hausman, Andrew W. Lo, A. Craig MacKinlay (2003). An ordered probit analysis of transaction stock prices. DSpace@MIT (Massachusetts Institute of Technology) .