Autoregressive modelling of the heterogeneous threshold of the shares traded for some companies in the Iraqi Stock Exchange with a practical application
DOI:
https://doi.org/10.31272/jae.i132.672Keywords:
Bayesian Information Criterion, Ljung-Box, maximum, Likelihood Method , ForecastingAbstract
Although linear time series models have wide applications for economic phenomena in general, they are not able to capture the behaviour of many economic phenomena and applications, especially financial ones. This type of series is characterized by modelling the kinetic state of the phenomena of asymmetry, structural changes, threshold, and others. Therefore, this shortcoming in linear modelling led to the emergence of non-linear models, which are models of various formats and not a model in one general format, as is the case in linear modelling.
In order to overcome this shortcoming, most recent studies have adopted non-linear modelling, and (Tong, 1978) was one of the first who made a qualitative leap in the application of this type of model that depends on the analysis of the dynamics of financial and monetary time series and others, including the threshold model for non-self-regression homogeneous (HTAR).
Our research aims to apply the (HTAR) model to a sample that represents the series of percentage changes in the shares of the Iraq Stock Exchange for the index (ISX60) for a group of companies. Research extracted from a master's thesis
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