Online Program

Friday, October 21
Knowledge
Community
Influence
Fri, Oct 21, 10:00 AM - 11:00 AM
Salon 2
Speed Session 2

Modeling Discrete Stock Price Changes Using a Mixture of Poisson Distributions (303187)

Ryan Gill, University of Louisville 
*Rasitha R Jayasekare, Butler University 
Kiseop Lee, University of Louisville 

Keywords: Poisson mixture model, asymptotic confidence estimation, liquidity risk, market microstructure

Mixture models have attracted many fields in recent decades. This presentation uses an application of mixture models to model discrete changes in the stock market price with respect to the "tick size." We study how the changes in the stock price are associated with the order size of the transaction. The parameters are estimated using the expectation – maximization (EM) algorithm with a constant mixing probability, as well as mixing probabilities that depend on order size. Consistency and asymptotic normality of a sequence of estimators are proved, and asymptotic confidence intervals for functions of the parameters are derived. The model is tested using stock transactions data from Federal Express.