Comparison Between the Simulated Prediction Methods of the Markov and Mixed Models - Riyadh Thanoon, Shaymaa (Al-Nahrain Journal of Science, 2024)
The aim of this study is to make a comparison between the Markov model and the mixed model to predict future values, based on monthly data of the exchange rates of the US dollar against the Iraqi dinar for the period from January 2017 to December 2022. By comparing the two models using MAD, RMSE, and MAPE prediction accuracy measures to find the most appropriate model for analyzing the data of interest, the study concluded that the mixed model (ARIMA) (0,2,1) with the lowest values of the prediction accuracy measures is the most suitable and appropriate model for analyzing the study data, in order to predict the future exchange rates of the US dollar against the Iraqi dinar compared to the Markov model. Based on this model, the exchange rates of the US dollar against the Iraqi dinar were predicted until the end of June 2023 AD, and the predictive values were consistent with the original values of the series, which indicates the efficiency of the model. Two statistical models were used: the Markov model, the autoregressive model, and ARIMA. The two models were applied to the data under study in order to compare them with the exchange rates of the dollar against the Iraqi dinar the importance of studying.