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dc.contributor.authorDI GIROLAMO Francescaen_GB
dc.contributor.authorJOENSSON BENGT HENRIK BREDVADen_GB
dc.contributor.authorCAMPOLONGO Francescaen_GB
dc.contributor.authorSCHOUTENS Wimen_GB
dc.date.accessioned2014-01-24T01:02:47Z-
dc.date.available2014-01-23en_GB
dc.date.available2014-01-24T01:02:47Z-
dc.date.created2013-12-10en_GB
dc.date.issued2013en_GB
dc.date.submitted2013-09-25en_GB
dc.identifier.isbn978-1-119-96396-7en_GB
dc.identifier.urihttp://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119963966.htmlen_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC84740-
dc.description.abstractAsset-backed securities (ABSs) are securities created through a securitization process whose value and income payments are backed by a specific pool of underlying assets. A securitization credit rating is an assessment of the credit risk of securitization transaction, addressing how well the credit risk of the assets is mitigated by the structure. The rating process is based on both quantitative assessment and a qualitative analysis of how the transaction mitigates losses due to defaults. Typically the input parameters to the quantitative assessment are unknown and estimated from historical data or given by expert opinions. In either case, the values used for the parameters are uncertain and these uncertainties propagates through the model and generates uncertainty in the rating output. This introduces uncertainty into the assessment and it therefore becomes important to understand the ratings parameter sensitivity. The objectives of this chapter are twofold. Firstly, we advocate the use of uncertainty and sensitivity analysis techniques to enhance the understanding of the variability of the credit ratings due to the uncertainty in the input parameters. Uncertainty analysis quantifies the variability in the output of interest due to the variability in the inputs. Global sensitivity analysis assesses how the uncertainty in the output can be allocated to its different sources. Through global sensitivity analysis, we quantify the percentage of output variance that each input or combination of inputs accounts for. Secondly, we propose a novel rating approach called global rating, that takes this uncertainty in the output into account when assigning ratings to tranches. The global ratings should therefore become more stable and reduce the risk of cliff effects, that is, that a small change in one or several of the input assumptions generates a dramatic change in the rating. The global rating methodology proposed gives one answer of a way forward for the rating of structure finance products.en_GB
dc.description.sponsorshipJRC.G.1-Scientific Support to Financial Analysisen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherJohn Wiley & Sons Ltden_GB
dc.relation.ispartofseriesJRC84740en_GB
dc.titleGlobal Structured Finance Ratingen_GB
dc.typeArticles in periodicals and booksen_GB
JRC Directorate:Space, Security and Migration

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