Publications
The Impact of Coronavirus (COVID-19) on Iraq Stock Market (Industrial Sector): An Event Study
Dec 1, 2021Journal Tikrit Journal of Administrative and Economic Sciences
Publisher university of tikrit
DOI https://doi.org/10.25130/tjaes.17.56.4.34
Issue 56
Volume 17
This research aims to give an overview of the study of events, and study the impact of the Corona virus (COVID19) on the Iraqi stock market. As well as discussing the necessary steps to apply the event methodology, and the study problem was represented by the following question: What is the impact of the covid-19 epidemic on the returns of the industrial sector in the Iraqi stock market, the study was applied to (5) companies from the industrial sector companies for a daily data series for the period from 1-1- 2019 to 12-31-2020. The data of the industrial sector in the Iraqi Stock Market was analyzed by studying the event using (Excel) program, and the results showed that most of the windows of the events that were examined, have negative abnormal cumulative returns (CAR); It was also noted that quite a few companies had positive reviews. Despite the different rates of abnormal return in different windows of events, the highest loss was in the Baghdad Company for Soft Drinks, in addition, Al-Mansour Company for Pharmaceutical Industries recorded the highest profit different and for a certain period of time.
Bayesian Nonlinear Latent variable Models with Mixed Non-normal Variables and Covariates for Multi-sample Psychological Data
Sep 1, 2019Journal Pakistan Journal of Statistics and Operation Research
Publisher university of tikrit
DOI https://doi.org/10.18187/pjsor.v15i3.2689
Issue III2019
Volume XV
The purpose of this paper is to develop a latent variable model with nonlinear covariates and latent variables. Mixed ordered categorical and dichotomous variables and covariates with two different types of thresholds (with equal and unequal spaces) are used in Bayesian multi-sample nonlinear latent variable models and the Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) and (truncated normal distribution with known parameters) are used to handle the problem of mixed ordered categorical and dichotomous data. Hidden continuous normal distribution (truncated normal distribution with known parameters) is used to handle the problem of mixed ordered categorical and dichotomous data in covariates. Statistical analysis, which involves the estimation of parameters, standard deviations and their highest posterior density, are discussed. The proposed procedure is illustrated using psychological data with the results obtained from the OpenBUGS program