Universität zu Köln

Wang, Ze, Liu, Siyao, Han, Chengyuan, Huang, Shupei, Gao, Xiangyun, Tang, Renwu and Di, Zengru (2022). Motif Transition Intensity: A Novel Network-Based Early Warning Indicator for Financial Crises. Front. Physics, 9. LAUSANNE: FRONTIERS MEDIA SA. ISSN 2296-424X

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Abstract

Financial crisis, rooted in a lack of system resilience and robustness, is a particular type of critical transition that may cause grievous economic and social losses and should be warned against as early as possible. Regarding the financial system as a time-varying network, researchers have identified early warning signals from the changing dynamics of network motifs. In addition, network motifs have many different morphologies that unveil high-order correlation patterns of a financial system, whose synchronous change represents the dramatic shift in the financial system's functionality and may indicate a financial crisis; however, it is less studied. This paper proposes motif transition intensity as a novel method that quantifies the synchronous change of network motifs in detail. Applying this method to stock networks, we developed three early warning indicators. Empirically, we conducted a horse race to predict ten global crises during 1991-2020. The results show evidence that the proposed indicators are more efficient than the VIX and the other 39 network-based indicators. In a detailed analysis, the proposed indicators send sensitive and comprehensible warning signals, especially for the U.S. subprime mortgage crisis and the European sovereign debt crisis. Furthermore, the proposed method provides a new perspective to detect critical signals and may be extended to predict other crisis events in natural and social systems.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Wang, Ze UNSPECIFIED UNSPECIFIED UNSPECIFIED Liu, Siyao UNSPECIFIED UNSPECIFIED UNSPECIFIED Han, Chengyuan UNSPECIFIED UNSPECIFIED UNSPECIFIED Huang, Shupei UNSPECIFIED UNSPECIFIED UNSPECIFIED Gao, Xiangyun UNSPECIFIED UNSPECIFIED UNSPECIFIED Tang, Renwu UNSPECIFIED UNSPECIFIED UNSPECIFIED Di, Zengru UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-682506
DOI:	10.3389/fphy.2021.800860
Journal or Publication Title:	Front. Physics
Volume:	9
Date:	2022
Publisher:	FRONTIERS MEDIA SA
Place of Publication:	LAUSANNE
ISSN:	2296-424X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SYSTEMIC RISK; CONNECTEDNESS; FLOW Multiple languages Physics, Multidisciplinary Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68250