We investigate long-run stock–bond correlation using a model that combines the dynamic conditional correlation model with the mixed-data sampling approach and allows long-run correlation to be affected by macro-finance factors (historical and forecasts). We use macro-finance factors related to inflation and interest rates, illiquidity, state of the economy, and market uncertainty. Macro-finance factors, particularly their forecasts, are good at forecasting long-run stock–bond correlation. Supporting the flight-to-quality phenomenon, long-run correlation tends to be small and negative when the economy is weak.