Principal Components as a Measure of Systemic Risk

Kritzman, Mark; Page, Sébastien; Rigobón, Roberto

doi:10.2139/ssrn.1582687

Cited by 45 publications

(58 citation statements)

References 28 publications

(20 reference statements)

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“…A major challenge to performing quality systemic analysis is the paucity of data for the entire system. Current approaches rely on a few proprietary data sets of limited scope [1,2,6,20]. Midas addresses this challenge in a major way by leveraging unstructured or semi-structured public data archived by SEC and FDIC to provide much richer information across the entire system of financial institutions.…”

Section: Systemic Risk Analysismentioning

confidence: 99%

Extracting, Linking and Integrating Data from Public Sources: A Financial Case Study

Burdick¹,

Hernández²,

Ho³

et al. 2015

SSRN Journal

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Section: Systemic Risk Analysismentioning

confidence: 99%

Extracting, Linking and Integrating Data from Public Sources: A Financial Case Study

Burdick¹,

Hernández²,

Ho³

et al. 2015

SSRN Journal

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“…These include the liquidity measures of Lo (2011) andHu, Pan, andWang (2010), the Mahalanobis distance metric of , and the absorption ratio of Kritzman, Li, Page, and Rigobon (2010). In addition, a number of the models cited above as short-horizon forecasting or fragility measures might also be deployed as contemporaneous monitoring tools; these include Brunnermeier (2010), International Monetary Fund (2009b), Segoviano andGoodhart (2009), Capuano (2008), and Duffie (2011).…”

Section: Contemporaneous Measures: Crisis Monitoringmentioning

confidence: 99%

“…For example, if we specify the returns of publicly traded financial institutions for R t , and define a systemic event as simultaneous losses among multiple financial institutions, then Adrian and Brunnermeier's (2010) focus is on the network topology of the asset returns of the financial system, then the Granger-causality network measure of Billio, Getmansky, Lo, and Pelizzon (2010) and the absorption ratio of Kritzman, Li, Page, and Rigobon (2010) are more relevant. By narrowing 18 We note two key assumptions implicit in this framework.…”

mentioning

confidence: 99%

A Survey of Systemic Risk Analytics

Bisias

Flood

et al. 2012

Annu. Rev. Financ. Econ.

524

180

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The Office of Financial Research (OFR) Working Paper Series allows staff and their co-authors to disseminate preliminary research findings in a format intended to generate discussion and critical comments. Papers in the OFR Working Paper Series are works in progress and subject to revision. We provide a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. We motivate these measures from the supervisory, research, and data perspectives in the main text, and present concise definitions of each risk measure-including required inputs, expected outputs, and data requirements-in an extensive appendix. To encourage experimentation and innovation among as broad an audience as possible, we have developed open-source Matlab code for most of the analytics surveyed, which can be accessed through the Office of Financial Research (OFR) at http://www.treasury.gov/ofr.

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“…On the empirical side, there is a large literature which focuses on measuring credit risk interconnectedness from market data (Kritzman, Yuanzhen, Page, andRigobon (2011), Zhang et al (2012), Barigozzi and Brownlees (2013), Podlich and Wedow (2014) and Betz et al 1 (2014)). However, it seems unclear why high frequency market data should reflect bank fundamentals (actual balance sheet information), that -at best -are only available annually.…”

Section: Introductionmentioning

confidence: 99%

Credit Risk Interconnectedness: What Does the Market Really Know?

et al. 2015

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Reproduction permitted only if source is stated. ISBN Non-technical summary Research questionThe identification and quantification of the systemic component of financial risk require an in-depth understanding of the channels through which shocks can spread and amplify, thereby jeopardizing the stability of a financial system. Our understanding of these links as a whole is, however, hampered by the absent comprehension of the key determinants of financial institutions' interconnections. This has been due to the lack of comprehensive datasets on a from-whom-to-whom basis that are sufficient for analyses of this kind. Therefore, a number of recent studies have suggested network estimation techniques based on market information to overcome this hurdle. In this paper, we examine the relationship between market-based measures of credit risk interconnectedness and actual common exposures of banks through their funding and securities holdings. ContributionWe use CDS prices to measure market-implied interconnectedness between banks employing a correlation-based approach and use a unique proprietary dataset for the period 2006-2013 to evaluate how much market information-based measures capture actual balance sheet linkages and risks associated with banks' funding, security investment, and credit provision behavior. ResultsTwo main results emerge from our analysis. First, we find that our market-based interconnectedness measure strongly reflects the information on banks' exposure to the wholesale funding market and assets associated with securities investments and credit supply. Second, we show that the relation between our market-based interconnectedness measure and the balance sheet positions exhibits asymmetries both over time and cross-sectionally. For instance, we find that interbank lending is a relevant driver of our measure during crisis times as other sources of financing become hard to obtain. And, bank pairs with higher exposures to the troubled security classes show up as more interconnected. On the contrary, commonality in securities investments related to crisis-unaffected security classes does not induce higher dependency. These results show that market information-based measures of interdependence can serve well as a risk monitoring tool in the absence of disaggregated highfrequency bank fundamental data. Abstract We analyze the relation between market-based credit risk interconnectedness among banks during the crisis and the associated balance sheet linkages via funding and securities holdings. For identification, we use a proprietary dataset that has the funding positions of banks at the bank-to-bank level for 2006-13 in conjunction with investments of banks at the security level and the credit register from Germany. We find asymmetries both cross-sectionally and over time: when banks face di culties to raise funding, the interbank lending a↵ects market-based bank interconnectedness. Moreover, banks with investments in securities related to troubled classes have a higher credit risk interconnectedness. ...

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Principal Components as a Measure of Systemic Risk

Cited by 45 publications

References 28 publications

Extracting, Linking and Integrating Data from Public Sources: A Financial Case Study

Extracting, Linking and Integrating Data from Public Sources: A Financial Case Study

A Survey of Systemic Risk Analytics

Credit Risk Interconnectedness: What Does the Market Really Know?

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