| EPSRC Reference: |
GR/R80131/01 |
| Title: |
A Statistical Approach to Default Correlation |
| Principal Investigator: |
Davis, Professor M |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Mathematics |
| Organisation: |
Imperial College London |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 October 2002 |
Ends: |
30 September 2005 |
Value (£): |
161,112
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| EPSRC Research Topic Classifications: |
| Mathematical Aspects of OR |
Statistics & Appl. Probability |
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| EPSRC Industrial Sector Classifications: |
| Financial Services |
No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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Investment decisions rest on various considerations such as the expected returns from the bonds and the viability of the companies issuing them. The latter, which determines the likelihood of bond defaults, is affected by the overall macroeconomic climate, to which all companies are subject, but also on narrower aspects focussed on the particular industry sector in which the company operates. Certain rating agencies give credit scores to companies and assign them to various rating categories. Over time, such scoring has demonstrating a degree of reliability and thus proved useful to investors.A primary question is how a portfolio of investments is to be diversified between different industry sectors. The defaults in any one sector tend to be correlated, making it less risky to spread investment over more than one sector. However, some sectors are likely to return higher yields than others, making them a more attractive proposition.Different rating agencies have tackled the issue of correlation in various rather ad-hoc ways that produce possibilities for the number of defaults over a fixed time period but do not take into account the times at which defaults occur. We intend to apply modern statistical methodology to the problem. Our proposal is to develop certain stochastic models for default correlation and use them for prediction of bond default.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.imperial.ac.uk |