Optimizing composite early warning indicators

Daniel Beltran, Vihar M. Dalal, Mohammad R. Jahan-Parvar and Fiona A. Paine

The North American Journal of Economics and Finance, 2024, vol. 74, issue C

Abstract: Research on predicting financial crises has produced various composite early warning indicators (EWIs) using macroeconomic and financial time-series. Much of the focus has been on identifying the best leading indicators for financial crises (e.g., credit-to-GDP ratios, financial asset prices, etc.). This paper instead focuses on how to optimally extract and combine signals from multiple cyclical indicators. We find that when combining multiple indicators into a composite EWI, jointly optimizing the indicators improves performance relative to optimizing individually and combining their signals. The performance of our jointly optimized EWIs is robust to the key modelling choices inherent in their design including the trend-cycle decomposition method and the preference for false positives over false negatives.

Keywords: Business cycle; Credit cycle; Early warning indicators; Equity prices; Financial crisis; Optimization; Trend-cycle decomposition (search for similar items in EconPapers)
JEL-codes: C22 E39 G28 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:74:y:2024:i:c:s106294082400175x

DOI: 10.1016/j.najef.2024.102250

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