Forecasting of Iran’s Official Exchange Rate Using the Autoregressive ARIMA Intervention Model

The exchange rate is one of the most important economics’ variables which could impact the foreign trade and balance of payments and other macroeconomic variables such as GDP, inflation, and employment. Given the dependency of Iranian economy on foreign exchange and its high volatility  over the past thirty-five years, forecasting the exchange rates and their volatility help reduce the risk in business and government plans.  In this paper, we model the Iran’s official exchange rate using the autoregressive ARIMA intervention approach and compare its results with the random walk model. We use the official exchange rates data from 1357 to 1394 to estimate the models and forecast for the period 1395 to 1404 using R. The results show that the ARIMA model with intervention performs better than the random walk model.