Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/212382 
Year of Publication: 
2017
Series/Report no.: 
Bank of Finland Research Discussion Papers No. 11/2017
Publisher: 
Bank of Finland, Helsinki
Abstract: 
We propose a wavelet-based approach for construction of a financial cycle proxy. Specifically, we decompose three key macro-financial variables – private credit, house prices, and stock prices – on a frequency-scale basis using wavelet multiresolution analysis. The resulting "wavelet-based" sub-series are aggregated into a composite index representing our cycle proxy. Selection of the sub-series deemed most relevant is done by emphasizing early warning properties. The wavelet-based financial cycle proxy is shown to perform well in detecting banking crises in out-of-sample exercises, outperforming the credit-to-GDP gap and a financial cycle proxy derived using the approach of Schüler et al. (2015).
JEL: 
C49
E32
E44
Persistent Identifier of the first edition: 
ISBN: 
978-952-323-165-8
Document Type: 
Working Paper

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