Predictability beyond accuracy: A correlation-based evaluation of survey forecasts of the Chilean exchange rate - Pablo Pincheira; Lorenzo Reus; Andrea Bentancor; Martin Flores (PLoS ONE, 2026)
Floating exchange rates are widely considered difficult—if not impossible—to predict. While traditional evaluations focus on out-of-sample accuracy measures such as Mean Squared Prediction Error (MSPE), recent literature argues that predictability is better understood as a form of dependence. Following this view, we assess the ability of Chile’s Survey of Professional Forecasters (SPF) to predict the Chilean peso (CLP) across multiple horizons. We find that SPF forecasts maintain stable and statistically significant predictive correlations with CLP returns, indicating meaningful predictability. However, forecast accuracy varies over time, mainly due to a persistent positive bias in the survey. We propose an adjustment aimed at removing this and other inefficiencies, which greatly improves accuracy, particularly at medium and long horizons. Finally, and contrary to common wisdom, we find that the most difficult benchmark to beat in the Chilean case is the random walk with drift—not the driftless random walk.