Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/307140 
Year of Publication: 
2024
Series/Report no.: 
Bank of Finland Research Discussion Papers No. 14/2024
Publisher: 
Bank of Finland, Helsinki
Abstract: 
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.
Subjects: 
forecast combination
frequency domain
equity premium
GDP growth
Haar filter
JEL: 
C58
G11
G17
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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