Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/21440
DC Field | Value | Language |
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dc.contributor.author | Ghosh, Pulak | |
dc.contributor.author | Murthy, Shashidhar | |
dc.date.accessioned | 2022-07-26T08:46:20Z | - |
dc.date.available | 2022-07-26T08:46:20Z | - |
dc.date.issued | 2012-06-10 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/21440 | - |
dc.description.abstract | While correlation (and diversification) is important to all investments, it is especially important to credit-sensitive securities as evidenced by the role of correlated defaults in the recent credit crisis. Correlation in the context of credit is a difficult issue because of sparse historical data on individual, and especially multiple, defaults. Hence, researchers and market participants have used market prices to construct forward-looking estimates of correlation. However, the only known ways of doing so are from multi-name securities (such as indexes, or collateralized debt obligations). Such instruments are far fewer in number than possible pairs of single-names (i.e. individual stocks, bonds, etc) – i.e. they are non-existent for most pairs. For these reasons, the modeling of correlations is termed by many as an extremely important problem in credit risk pricing. | |
dc.publisher | Indian Institute of Management Bangalore | |
dc.relation | Default correlations | |
dc.relation.ispartofseries | IIMB_PR_2012-13_008 | |
dc.subject | Statistics | |
dc.subject | Correlations | |
dc.title | Default correlations | |
dc.type | Project-IIMB | |
Appears in Collections: | 2012-2013 |
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