Estimating the parameters of the GARCH model for the Polya distribution with a practical application
DOI:
https://doi.org/10.31272/jae.i142.1035Keywords:
autoregression conditional on heterogeneity of variance, maximum likelihood method (MLE), Polya distributionAbstract
The research aims to study time series with high volatility (volatility) , in which the problem of autoregressive conditional on the heterogeneity of variance in the case of intermittent distributions , that is when its observations have integer values . The INGARCH model was studied when the series follows the Polya distribution , which was Studying the model theoretically and practically , and then estimating the model parameters using the maximum likelihood method (MLE) , and in the applied aspect , data on the number of transactions of the Sumer Commercial Bank in the Iraqi Stock Exchange was used , where the presence of the ARCH effect was tested using the Ljung - Box Test and (ARCH Test) It became clear from the two tests that the data suffers from the problem of heterogeneity of variance (ARCH) , and finally it was concluded that the model that explains the fluctuations in the number of transactions of Sumer Commercial Bank is the INGARCH (2.0) model , based on the results of the two standards AIC and BIC .
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