Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators - Gonçalo Faria; Fabio Verona (Bank of Finland, 2024)
We introduce a frequency-domain forecast combination method that leverages time- and frequencydependent predictability to enhance forecast accuracy. By decomposing both the target variables (equity premium and real GDP growth) and predictor variables into distinct frequency components, this method aligns forecasts with frequency-specific predictive relationships. This approach yields significantly higher accuracy than traditional time-domain methods, as evidenced by both statistical and economic out-of-sample metrics. Gains are particularly pronounced during recessions, where excluding low-frequency components further enhances forecast precision. Overall, these findings highlight the value of frequency-domain forecasting in capturing complex, time-varying patterns across varied macro-financial contexts.
urn:nbn:fi-fe2024112696785
Keywords: C58; G11; G17; 330; forecast combination; frequency domain; equity premium; GDP growth; Haar filter