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Early Warning Signals of Financial Stress: A “Wavelet-Based” Composite Indicators Approach

In: Advances in Non-linear Economic Modeling

Author

Listed:
  • Marco Gallegati

    (Polytechnic University of Marche)

Abstract

In this paper we exploit the usefulness of wavelet multi resolution analysis in providing early warning signals of financial stress (conditions). The proposed “wavelet-based” approach gives rise to a composite indicator obtained by aggregating several “scale-based” sub-indexes whose individual components are selected on the basis of their cross-correlations properties at different frequency bands. The performance of the “wavelet-based” composite indicator is assessed by evaluating its predictive power relative to the individual financial variables taken in isolation through an out-of-sample forecasting exercise for the US financial stress index. The findings indicate that the wavelet-based composite indicator largely outperforms any individual financial variable taken in isolation in early detecting financial stress at every horizon and that the gain tends to increase as the time horizon increases.

Suggested Citation

  • Marco Gallegati, 2014. "Early Warning Signals of Financial Stress: A “Wavelet-Based” Composite Indicators Approach," Dynamic Modeling and Econometrics in Economics and Finance, in: Frauke Schleer-van Gellecom (ed.), Advances in Non-linear Economic Modeling, edition 127, pages 115-138, Springer.
  • Handle: RePEc:spr:dymchp:978-3-642-42039-9_3
    DOI: 10.1007/978-3-642-42039-9_3
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    Cited by:

    1. Oet, Mikhail V. & Gramlich, Dieter & Sarlin, Peter, 2016. "Evaluating measures of adverse financial conditions," Journal of Financial Stability, Elsevier, vol. 27(C), pages 234-249.
    2. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.

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