Title

Machine learning as an early warning system to predict financial crisis

Source of Publication

International Review of Financial Analysis

Abstract

© 2020 Elsevier Inc. 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.

Document Type

Article

Publication Date

10-1-2020

DOI

10.1016/j.irfa.2020.101507

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