Stock price discreteness and clustering: decimals and ordered probit model
Journal of Financial Regulation and Compliance
ISSN: 1358-1988
Article publication date: 4 February 2014
Abstract
Purpose
The purpose of this paper is to revisit the ordered probit model of Hausman et al. after the NYSE decimalization.
Design/methodology/approach
The changed ordered probit model.
Findings
The model can somewhat capture the different impact of trading-related “explanatory” variables on price changes among three different decimals but does not explain much about price discreteness and irregular transaction intervals among the existing models of stock price discreteness. Overall 1/16th and 1/24th range of the dependent variable is better explained by trading-related explanatory variables than 1/8th range of the dependent variable for small firms and there is not much difference in large firms among three decimals. The results imply that finer specification in decimalization and smaller firm size matters in trading after the decimalization project.
Originality/value
First paper to revisit the ordered probit model of Hausman et al. after the NYSE decimalization.
Keywords
Acknowledgements
The author would like to thank investment seminar participants at the Louisiana State University in 2005 for helpful comments. The initial project started when the author was at the Louisiana State University. The author is responsible for all the errors.
Citation
Kim, H. (2014), "Stock price discreteness and clustering: decimals and ordered probit model", Journal of Financial Regulation and Compliance, Vol. 22 No. 1, pp. 49-60. https://doi.org/10.1108/JFRC-07-2012-0025
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited