Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume 280, Issue 1, Pages 279-294Publisher
ELSEVIER
DOI: 10.1016/j.ejor.2019.06.049
Keywords
OR in banking; Financial networks; Liquidity risk management; Systemic risk; Hidden Markov models
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Our paper contributes to the recent macroprudential policy addressing the resilience of financial systems in terms of their interconnectedness. We argue that beneath an interbank market, there is a fundamental latent network that affects the liquidity distributions among banks. To investigate the interbank market, we propose a framework that identifies such latent network using a statistical learning procedure. The framework reverse engineers overnight signals observed as banks conduct their reserve management on a daily basis. Our simulation-based results show that possible disruptions in funds supply are highly affected by the interconnectedness of the latent network. Hence, the proposed framework serves as an early warning system for regulators to monitor the overnight market and to detect ex-ante possible disruptions based on the inherent network characteristics. (C) 2019 Elsevier B.V. All rights reserved.
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