Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators

Gonçalo Faria and Fabio Verona

No 14/2024, Bank of Finland Research Discussion Papers from Bank of Finland

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.

Keywords: forecast combination; frequency domain; equity premium; GDP growth; Haar filter (search for similar items in EconPapers)
JEL-codes: C58 G11 G17 (search for similar items in EconPapers)
Date: 2024
New Economics Papers: this item is included in nep-ets and nep-for
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