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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach

The signals approach as an early warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it does not distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful and statistically significant results and (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach, even where most individual indicators are not statistically significant on their own.

12. April 2012

Authors Makram El-Shagi Tobias Knedlik Gregor von Schweinitz

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Predicting Financial Crises: The (Statistical) Significance of the Signals Approach

Makram El-Shagi Tobias Knedlik Gregor von Schweinitz

in: Journal of International Money and Finance, No. 35, 2013

Abstract

The signals approach as an early-warning system has been fairly successful in detecting crises, but it has so far failed to gain popularity in the scientific community because it cannot distinguish between randomly achieved in-sample fit and true predictive power. To overcome this obstacle, we test the null hypothesis of no correlation between indicators and crisis probability in three applications of the signals approach to different crisis types. To that end, we propose bootstraps specifically tailored to the characteristics of the respective datasets. We find (1) that previous applications of the signals approach yield economically meaningful results; (2) that composite indicators aggregating information contained in individual indicators add value to the signals approach; and (3) that indicators which are found to be significant in-sample usually perform similarly well out-of-sample.

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