This study examined the macroeconomic determinants of exchange rate volatility based on evidence from Kenya from 1971 to 2024. The study employed Autoregressive Distributed Lag (ARDL) bounds testing for co-integration and estimated the error correction model. Furthermore, ARCH and GARCH models were analyzed to measure the volatility of a time series by fitting an autoregressive model to the squared residuals of the time series. The ARCH and GARCH results suggest the volatility of the exchange rate markets in Kenya is not random. The speed of adjustment of the volatility in the Kenyan economy's exchange rate is 59.7%. The study found that in the long run, a unit increase in foreign direct investment (FDI) and government expenditure reduced exchange rate volatility by 36.4% and 341.5%, respectively, while inflation and money supply increased by 55.2% and 239.7%, respectively. Short-run results showed that a 1% increase in FDI, money supply and inflation rate increased volatility by 18.31%, 19.26%, and 111.83%, respectively, while government spending and public debt reduced volatility by 90.65% and 42.18%, respectively. To reduce or stabilise exchange rate volatility, the study recommended a combination of monetary policy interventions to policymakers. These included foreign exchange operations, interest rate adjustments, hedging strategies, and export diversification. Additionally, the central bank is advised to regulate the growth of the money supply to prevent excessive inflation and currency depreciation, which could exacerbate exchange rate fluctuations. Keywords: Exchange rate volatility, macroeconomic factors, GARCH, ARDL, JEL
Joseph Ngigi Kinuthia (Sun,) studied this question.