Downturn model risk: Another view of the global financial crisis

Roesch, D; Scheule, H

Downturn model risk: Another view of the global financial crisis

Roesch, D Scheule, H

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Publisher:: Risk Books
Publication Type:: Chapter
Citation:: Model risk - Identification, measurement and management, 2010, 1st, pp. 3 - 18
Issue Date:: 2010-01

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Field	Value	Language
dc.contributor.author	Roesch, D	en_US
dc.contributor.author	Scheule, H https://orcid.org/0000-0001-7283-5654	en_US
dc.contributor.editor	Scheule, H https://orcid.org/0000-0001-7283-5654	en_US
dc.contributor.editor	Roesch, D	en_US
dc.date.issued	2010-01	en_US
dc.identifier.citation	Model risk - Identification, measurement and management, 2010, 1st, pp. 3 - 18	en_US
dc.identifier.isbn	978-1-906348-25-0	en_US
dc.identifier.uri	http://hdl.handle.net/10453/29931
dc.description.abstract	Researchers and practitioners have spent ample resources modelling credit, explaining correlations between risk models as well as inputs and outputs. One popular example is asset correlation, which describes the co-movement between the asset value returns of corporate borrowers or issuers. Other examples are default correlations, correlations between default and recovery processes and correlations between risk categories such as credit, interest, liquidity or market risk. In statistical terms, correlations are often placeholders for relationships which cannot be explained and are also known as "seeming correlations". The 2008-9 global financial crisis caught us by surprise and showed that, starting with US subprime mortgage markets, other markets such as equity, credit and commodity markets have declined globally. These links have not been included into existing risk models, and this chapter identifies these links and shows . how to address these relationships in risk models.	en_US
dc.publisher	Risk Books	en_US
dc.relation.ispartof	Model risk - Identification, measurement and management	en_US
dc.title	Downturn model risk: Another view of the global financial crisis	en_US
dc.type	Chapter
utslib.location	London, UK	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
utslib.citation.edition	1st	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.edition	1st	en_US
pubs.place-of-publication	London, UK	en_US

Abstract:

Researchers and practitioners have spent ample resources modelling credit, explaining correlations between risk models as well as inputs and outputs. One popular example is asset correlation, which describes the co-movement between the asset value returns of corporate borrowers or issuers. Other examples are default correlations, correlations between default and recovery processes and correlations between risk categories such as credit, interest, liquidity or market risk. In statistical terms, correlations are often placeholders for relationships which cannot be explained and are also known as "seeming correlations". The 2008-9 global financial crisis caught us by surprise and showed that, starting with US subprime mortgage markets, other markets such as equity, credit and commodity markets have declined globally. These links have not been included into existing risk models, and this chapter identifies these links and shows . how to address these relationships in risk models.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/29931