Density Forecasts of Emerging Markets’ Exchange Rates Using Monte Carlo Simulation with Regime Switching

Abstract

We develop a novel method to produce density forecasts of foreign exchange rates using Monte Carlo simulation with regime-switching depending on global financial markets’ sentiment. Using multiple density forecast evaluation tools the proposed approach have been examined in one month ahead forecasting exercise for 22 emerging markets currencies rates vs. dollar. According to the log predictive density score criterion, in case of the majority of emerging markets’ foreign exchange rates, the forecasting performance of the proposed approach is superior to the random walk forecast and AR-GARCH benchmarks. Further analysis of the proposed approach using coverage rates and Knüppel test indicate correct calibration of the density model. The conducted evaluation of the proposed approach suggests that such tool can be suitable for economists, risk managers, econometricians, or policy makers focused on producing accurate density forecasts of foreign exchange rates. The proposed approach is a valuable contribution to the existing literature on foreign exchange density forecasting.