INVESTIGATING THE NIGERIAN NAIRA PER US-DOLLAR EXCHANGE RATE (NGNUSD) USING ARMA-GARCH MODELS - Adenomon, M O; Ibrahim, Ahmed; Muhammed, Inuwa Yahaya; Maijama'a, Bilkisu (Economics and Statistics Research Journal (ESRJ), 2025)
Exchange rate volatility plays a crucial role in economic stability, trade balance, and investment decisions. The Nigerian Naira to US Dollar (NGN/USD) exchange rate has experienced significant fluctuations due to macroeconomic factors, global oil price movements, and monetary policies. This study investigates the statistical properties, dynamics, and volatility clustering of the NGN/USD exchange rate using Autoregressive Moving Average (ARMA) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models. This study uses historical daily exchange rate data from July 1995 to June 2024, sourced from the Central Bank of Nigeria (CBN) and other financial institutions. The methodology involves time-series econometric techniques, including stationarity tests, ARMA modeling for mean dynamics, and GARCH modeling for volatility estimation. Model selection criteria, such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to identify the best-fitting model. The results indicate that the NGN/USD exchange rate exhibits volatility clustering, where periods of high volatility are followed by further fluctuations. The ARMA (1,1)-GARCH(1,1) model was found to be the most suitable model for capturing both the mean and variance structure of the exchange rate. The persistence of volatility suggests that external shocks, speculative trading, and macroeconomic conditions significantly impact Naira stability. The study concludes that exchange rate volatility in Nigeria poses a key economic challenge that requires strategic policy interventions. Based on these findings, adopt robust foreign exchange management strategies, financial institutions should integrateadvanced risk assessment models, and future research should explore additional macroeconomic factors affecting exchange rate dynamics