SAFE: An Early Warning System for Systemic Banking Risk

Oet, Mikhail V.; Eiben, Ryan; Bianco, Timothy; Gramlich, Dieter; Ong, Stephen J.; Wang, Jing

doi:10.2139/ssrn.1914862

Cited by 8 publications

(3 citation statements)

References 56 publications

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“…", Ben S. Bernanke (2011), The Federal Reserve Bank of Boston, 56th Economic Conference. 2 Oet et al (2013) present an example of such "early warning systems" designed for the identification of systemic banking risk in the U.S financial system., which they refer to as "SAFE" (Systemic Assessment of Financial Environment).…”

Section: Introductionmentioning

confidence: 99%

Does linkage fuel the fire? The transmission of financial stress across the markets

Chau

Deesomsak

2014

International Review of Financial Analysis

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The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThis paper develops an indicator of financial stress transmission, called Financial Stress Spillover Index (FSSI), to monitor the condition of financial system and to identify periods of excessive spillover that may lead to financial instability. Specifically, using the "spillover index" approach of Diebold and Yilmaz (2012), we modify and extend the financial stress indices proposed by Oet et al. (2011) to track both total and directional stress spillovers across the U.S. equity, debt, banking, and foreign exchange markets. Unlike other previous studies, the important linkages among these four major financial sectors in an interconnected world are directly taken into account by considering the average and time-varying connectedness of each individual market. The evidence suggests that there are important stress episodes and fluctuations across markets; the total cross-market stress spillovers were rather limited until the onsets of financial crises. As the crises intensified, so too did the financial stress spillovers; with significant stress carrying over from debt and equity markets to the others. In addition, our results indicate that FSSI has a significant predictive power for the economic activity and provides useful information for dating financial crisis. JEL classification: G01; C03

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Section: Introductionmentioning

confidence: 99%

Does linkage fuel the fire? The transmission of financial stress across the markets

Chau

Deesomsak

2014

International Review of Financial Analysis

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“…Simultaneously, many research efforts are devoted to understand the role of banks or, broadly speaking, of financial institutions in the creation and in the consecutive spreading of systemic risk. Given the prominent importance of the topic and its multifaceted nature, the literature on evaluation and anticipation of systemic events is huge (see Demirgüç-Kunt and Detragiache, 1998;Kaminsky and Reinhart, 1999;Harrington, 2009;Scheffer et al, 2009;Barrell et al, 2010;Duttagupta and Cashin, 2011;Kritzman et al, 2011;Allen et al, 2012;Arnold et al, 2012;Bisias et al, 2012;Scheffer et al, 2012;Merton et al, 2013;Oet et al, 2013, among many contributions).…”

Section: Introductionmentioning

confidence: 99%

Assessing Systemic Risk Due to Fire Sales Spillover Through Maximum Entropy Network Reconstruction

2015

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Assessing systemic risk in financial markets is of great importance but it often requires data that are unavailable or available at a very low frequency. For this reason, systemic risk assessment with partial information is potentially very useful for regulators and other stakeholders. In this paper we consider systemic risk due to fire sales spillover and portfolio rebalancing by using the risk metrics defined by Greenwood et al. (2015). By using the Maximum Entropy principle we propose a method to assess aggregated and single bank's systemicness and vulnerability and to statistically test for a change in these variables when only the information on the size of each bank and the capitalization of the investment assets are available. We prove the effectiveness of our method on 2001-2013 quarterly data of US banks for which portfolio composition is available.JEL codes: C45;C80;G01;G33.

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“…While being few in number, previous works have accounted for the interconnectedness in assessing and predicting systemic risks. In particular, Oet et al (2013) used indicators of the cross-sectional dimension of systemic risk through connectivity indicators, such as CoVaR, in order to signal banking crises, Minoiu et al (2013) assess the link between overall cross-country financial connectedness and vulnerability to banking crises, and Peltonen et al (2014) analyze the impact of both cross-country and domestic interconnectedness in terms of four different financial instruments as vulnerability to banking crises. Yet, in relation to the present paper, these are all at the country level and compute only overall interconnectedness as a vulnerability rather than allowing for distress pass through in networks.…”

Section: Introductionmentioning

confidence: 99%

Network Linkages to Predict Bank Distress

2015

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractBuilding on the literature on systemic risk and financial contagion, the paper introduces estimated network linkages into an early-warning model to predict bank distress among European banks. We use multivariate extreme value theory to estimate equity-based tail-dependence networks, whose links proxy for the markets' view of bank interconnectedness in case of elevated financial stress. The paper finds that early warning models including estimated tail dependencies consistently outperform bank-specific benchmark models without networks. The results are robust to variation in model specification and also hold in relation to simpler benchmarks of contagion. Generally, this paper gives direct support for measures of interconnectedness in early-warning models, and moves toward a unified representation of cyclical and cross-sectional dimensions of systemic risk.Keywords: bank distress; bank networks; systemic risk JEL codes: G21, G33, C54, D85ECB Working Paper 1828, July 2015 1 Non-technical summaryIn recent years, considerable effort has been invested into research on analyzing the build-up of vulnerabilities for banks and timely predicting possible bank distress events that could impact the soundness of the European banking system. The motivation behind this lies with the recent global financial crisis of 2007-2009 and the subsequent sovereign debt crisis in Europe, which brought a large number of European banks to the brink of collapse and prompted government interventions that led to unprecedented bailout costs. An important contribution to the enormous impact of the financial crises came from the high interconnectivity of the European banking system, which functions as a potential propagation mechanism of bankspecific vulnerabilities, allowing for risks and contagion to flow through the system. Much of the empirical literature proposes early-warning models based on conventional statistical modeling methods, such as multivariate logit/probit models that deliver distress predictions for individual banks. However, these models do not account for possible bank interdependencies. This paper addresses this shortcoming by providing a general-purpose framework that enables combining potential contagion effects with bank distress models. In particular, the paper proposes a two-step estimation where the bank failure model of Betz et al. (2014) is complemented with different contagion variables that account for possible vulnerabili...

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SAFE: An Early Warning System for Systemic Banking Risk

Cited by 8 publications

References 56 publications

Does linkage fuel the fire? The transmission of financial stress across the markets

Does linkage fuel the fire? The transmission of financial stress across the markets

Assessing Systemic Risk Due to Fire Sales Spillover Through Maximum Entropy Network Reconstruction

Network Linkages to Predict Bank Distress

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