Dating the financial cycle with uncertainty estimates: a wavelet proposition

Diego Ardila and Didier Sornette

Finance Research Letters, 2016, vol. 19, issue C, 298-304

Abstract: We propose to date and analyze the financial cycle using the Maximum Overlap Discrete Wavelet Transform (MODWT). Our presentation points out limitations of the methods derived from the classical business cycle literature, while stressing their connection with wavelet analysis. The fundamental time-frequency uncertainty principle imposes replacing point estimates of turning points by interval estimates, which are themselves function of the scale of the analysis. We use financial time series from 19 OECD countries to illustrate the applicability of the tool.

Keywords: Financial cycle; Wavelet transform; Multi-scale analysis; BBQ algorithm; Turning points; Interval estimates (search for similar items in EconPapers)
JEL-codes: C1 C14 C5 E3 E32 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:19:y:2016:i:c:p:298-304

DOI: 10.1016/j.frl.2016.09.004

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