Paper Title
Analyzing Intra-Day Stock Transactions using the NGINAR(1) Time series Model

This paper analyzes the number of intra-day stock transactions of the Mauritius Commercial Bank (MCB) on the Stock Exchange of Mauritius (SEM) using the integer-valued autoregressive process of order (1) (INAR(1)) with inflated geometric marginal counting series based on the negative binomial (NB) thinning operator (NGINAR(1)). The statistical properties of this new time series process are developed and a flexible and computationally stable quasi-likelihood (QL) method of estimation is used to obtain estimates of the mean, serial and other parameters. The performance of this estimation method is tested through a Monte Carlo simulation study. The method is also applied to analyze the intra-day stock transactions of MCB collected over the period 1st March to 30th March 2018, which are influenced by some time-dependent covariates such as news effect, Friday effect and time of the day effect.