Model and Measure the Volatility of the Iraqi Dinar’s Exchange Rate Against the US Dollar Using the AR(1)-GARCH(1,1) Model Under the Student’s *t*-Distribution for the Period 2015–2024

Abstract

This study aims to model and measure the volatility of the Iraqi dinar’s exchange rate against the US dollar for the period 2015–2024, using modern standard methods for financial time series. The research problem stems from the inadequacy of traditional linear models, such as Ordinary Least Squares (OLS), and the assumption of a normal distribution in capturing the extreme shocks experienced by the Iraqi economy. To overcome this limitation, the study employed an autoregressive model with conditional heteroscedasticity (AR(1)-GARCH(1,1)) model, assuming a Student’s t-distribution. The results of the statistical tests showed a decisive rejection of the normality hypothesis based on the Jarque–Bera test, and provided mathematical evidence of the presence of a clustering phenomenon in volatility based on the ARCH-LM test. The estimation results also confirmed that the probability distribution of the dinar exchange rate returns is characterised by heavy tails with a degree of freedom of (ν=5.24), implying a high probability of severe shocks. The study concludes that conditional variance models are the most effective in measuring the exchange rate risk of the Iraqi dinar.