Forecasting Nominal Exchange Rate in Emerging and Leading‐Frontier Sub‐Saharan African Economies

ABSTRACT Purpose This study investigates the forecasting performance of nominal exchange rates in Emerging and Leading‐Frontier Sub‐Saharan African Economies (EMSSAEs and LFSSAEs) and explores how financial integration, liquidity conditions, and institutional quality influence predictability. It provides insights relevant to multinational firms, currency risk managers, and policymakers navigating currency volatility in frontier markets. Methodology The study employs ARIMA, ARDL, and the Monetary Model using MZM liquidity proxy to forecast exchange rates using long‐term annual data. Forecast performance is evaluated through RMSE, MAE, and Diebold‐Mariano statistics, incorporating structural and policy dynamics across heterogeneous financial markets. Findings Results show that monetary‐based models demonstrate superior long‐horizon forecasting power in financially deepened and globally integrated markets, while ARIMA and ARDL models perform better in structurally constrained economies. Evidence of partial market efficiency is observed, with significant variation based on institutional strength and financial openness. Practical Implications The findings offer practical guidance for cross‐border investors, firms engaged in international trade, and policymakers in designing currency risk management strategies, exchange rate targeting mechanisms, and improving financial integration policies. Originality/Value This study extends exchange rate forecasting literature to emerging and frontier African markets, demonstrating how varying levels of market maturity and financial globalization impact model performance and predictability, with direct implications for international business strategy and policy formulation.