Forecasting exchange rate dynamics in developing countries

Given that volatility influences decisions about currency rates, monetary policy, and macroeconomic it is crucial to predict anticipate in emerging economies. The study employed generalized autoregressive conditional heteroskedasticity (GARCH) asymmetric models estimate forecast exchange rate dynamics developing countries. We found South Africa model had similar variance covariance proportion of 0.99356 percent 0.995901 respectively the could rise or fall by 2 6 units rand, for USD. In Kenya, rates continually exhibited steady monthly with extremely low mean absolute percentage error 0.01568 this demonstrates how strongly predicts Kenya’s future while chart supports absence persistence. Ghana, are projected increase significantly as 99.5 unsystematic was un accounted model. Volatility highly persistent Nigeria; hence forecasting reported a high taking 1.06 symmetric into cognizance. Mauritius asymmetry volatility, revealing turbulence when bad news hit market. Hence, local currencies rendered worthless foreign