Title :
Negative Binomial Model with an Application to Special Treatment Count Data
Author :
Ni, Zhongxin ; Li, Ting
Author_Institution :
Dept. of Finance, Shanghai Univ., Shanghai, China
Abstract :
Special Treatment (ST) is a particular regulation for the exchange to prompt the risk to investors. Since ST count data are discrete, traditional Orthogonal Least Square method cannot get better goodness of fitting. However, Poisson regression is appropriate to be used to analyze discrete data. In addition, once it is over-dispersed, Negative Binomial (NB) regression model is more suitable. In this paper, we study the influence of non-financial factors on ST occurrence event count with NB model. Result shows that China Interbank Offered Rate, Import, Export, Deposits of Enterprises and one-period lagged ST count are evidently associated with ST risk.
Keywords :
Poisson distribution; banking; binomial distribution; international trade; investment; regression analysis; risk management; China interbank offered rate; Poisson regression; ST risk management; discrete data analysis; export; import; investor risk; negative binomial regression model; nonfinancial factor; special treatment count data; Companies; Data models; Dispersion; Economics; Fitting; Niobium; Predictive models;
Conference_Titel :
Management and Service Science (MASS), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6579-8
DOI :
10.1109/ICMSS.2011.5998339
