Exploring the Effectiveness of ARIMA Models in Predicting Interest Rates in Slovakia

Research background: Predicting movements in interest rates is of paramount importance to financial and economic planning. Accurate predictions allow policymakers, financial institutions, and businesses to make efficient investment decisions, risk management, and fiscal policy. Predicting movements in interest rates assists in providing useful information for the realignment of monetary policies and the optimization of capital allocation during times of uncertainty. Purpose of the article: The aim of this paper is to fill a gap in the literature and examine the use of the ARIMA model to predict interest rates in Slovakia, a country subject to domestic as well as EU economic factors. Methods: The ARIMA model is utilized within this study to forecast Slovak interest rates to test how accurate it can be in measuring Slovak interest rate intricate dynamics, which arise due to both EU and local monetary policy interventions. Traditional calibration metrics such as MAE, RMSE, and MAPE are used to gauge its precision in forecasting. The result provides information about the efficiency and limitations of using ARIMA as an instrument of economic forecasting in the Slovak context. Findings & Value added: The ARIMA(2,1,1) model worked exceptionally well in interest rate prediction for Slovakia, explaining 99.1% of the variance with very low RMSE at 0.085 and MAPE at 1.864%. Significant coefficients, such as AR(1) 0.984 and MA(1) 0.692, indicate the success of the model in capturing the underlying time series dynamics. The Ljung-Box test also confirmed the existence of non-significant autocorrelation among the residuals, confirming the model's stability and reliability in economic forecasting. Practically, these findings are useful to policymakers, banks, and businesses in Slovakia, as accurate interest rate forecasts in guiding investment plans, credit risk, and fiscal policy. The findings underscore the need to utilize strong forecasting models like ARIMA to adjust policies in a setting dominated by both EU and domestic economics to enable economic choices to be guided by up-to-date information.