Machine learning as an early warning system to predict financial crisis

Aristeidis Samitas, Elias Kampouris and Dimitris Kenourgios

International Review of Financial Analysis, 2020, vol. 71, issue C

Abstract: This paper studies on “Early Warning Systems” (EWS) by investigating possible contagion risks, based on structured financial networks. Early warning indicators improve standard crisis prediction models performance. Using network analysis and machine learning algorithms we find evidence of contagion risk on the dates where we observe significant increase in correlations and centralities. The effectiveness of machine learning reached 98.8%, making the predictions extremely accurate. The model provides significant information to policymakers and investors about employing the financial network as a useful tool to improve portfolio selection by targeting assets based on centrality.

Keywords: Financial crisis; Social network analysis; Contagion; Forecasting; Machine learning (search for similar items in EconPapers)
JEL-codes: E37 G01 Z13 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:71:y:2020:i:c:s1057521920301514

DOI: 10.1016/j.irfa.2020.101507

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