An Ordered Probit Analysis of Transaction Stock Prices
Jerry A. Hausman
Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER)
Andrew W. Lo
Massachusetts Institute of Technology (MIT) - Sloan School of Management; Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); National Bureau of Economic Research (NBER)
A. Craig Mackinlay
University of Pennsylvania - Finance Department; National Bureau of Economic Research (NBER)
NBER Working Paper No. w3888
We estimate the conditional distribution of trade-to-trade price changes using ordered probit, a statistical model for discrete random variables. Such an approach takes into account the fact that transaction price changes occur in discrete increments, typically eighths of a dollar, and occur at irregularly spaced time intervals. Unlike existing continuous-time/discrete-state models of discrete transaction prices, ordered probit can capture the effects of other economic variables on price changes, such as volume, past price changes, and the time between trades. 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.
Number of Pages in PDF File: 74working papers series
Date posted: December 27, 2006
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo5 in 0.406 seconds