Forecasting exchange rate dynamics in developing countries

Abstract

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