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Wavelet decomposition of the financial cycle: An early warning system for financial tsunamis

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  • Voutilainen, Ville

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).

Suggested Citation

  • Voutilainen, Ville, 2017. "Wavelet decomposition of the financial cycle: An early warning system for financial tsunamis," Bank of Finland Research Discussion Papers 11/2017, Bank of Finland.
    • Handle: RePEc:zbw:bofrdp:rdp2017_011
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    References listed on IDEAS

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    1. Hiebert, Paul & Peltonen, Tuomas A. & Schüler, Yves S., 2015. "Characterising the financial cycle: a multivariate and time-varying approach," Working Paper Series 1846, European Central Bank.
    2. Claudio Borio, 2014. "The financial cycle and macroeconomics: what have we learned and what are the policy implications?," Chapters, in: Ewald Nowotny & Doris Ritzberger-Grünwald & Peter Backé (ed.), Financial Cycles and the Real Economy, chapter 2, pages 10-35, Edward Elgar Publishing.
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    4. Gallegati, Marco, 2008. "Wavelet analysis of stock returns and aggregate economic activity," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3061-3074, February.
    5. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    6. António Rua, 2011. "A wavelet approach for factor‐augmented forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(7), pages 666-678, November.
    7. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    8. Detken, Carsten & Peltonen, Tuomas A. & Schudel, Willem & Behn, Markus, 2013. "Setting countercyclical capital buffers based on early warning models: would it work?," Working Paper Series 1604, European Central Bank.
    9. Sarlin, Peter, 2013. "On policymakers’ loss functions and the evaluation of early warning systems," Economics Letters, Elsevier, vol. 119(1), pages 1-7.
    10. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    11. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    12. Borio, Claudio, 2014. "The financial cycle and macroeconomics: What have we learnt?," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 182-198.
    13. David Aikman & Andrew G. Haldane & Benjamin D. Nelson, 2015. "Curbing the Credit Cycle," Economic Journal, Royal Economic Society, vol. 125(585), pages 1072-1109, June.
    14. Demirguc, Asli & Detragiache, Enrica, 2000. "Monitoring Banking Sector Fragility: A Multivariate Logit Approach," The World Bank Economic Review, World Bank, vol. 14(2), pages 287-307, May.
    15. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    16. repec:zbw:bofrdp:2017_001 is not listed on IDEAS
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    Cited by:

    1. Martin Mandler & Michael Scharnagl, 2022. "Financial Cycles in Euro Area Economies: A Cross‐Country Perspective Using Wavelet Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(3), pages 569-593, June.
    2. Mandler, Martin & Scharnagl, Michael, 2022. "Financial cycles across G7 economies: A view from wavelet analysis," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    3. Wang, Bo & Xiao, Yang, 2023. "The term effect of financial cycle variables on GDP growth," Journal of International Money and Finance, Elsevier, vol. 139(C).
    4. Mundra, Sruti & Bicchal, Motilal, 2024. "Financial cycle comovement with monetary and macroprudential policy and global factors: Evidence from India," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).

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    More about this item

    JEL classification:

    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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