Kamakura Corporation Releases Version 5.0 Public Firm Default Probabilities To Clients Worldwide

New York - 30 September 2010

Kamakura Corporation announced Thursday that version 5.0 of Kamakura’s industry-leading public firm default probability models has been released to clients around the world. The models released include a new version of Kamakura’s Jarrow-Chava reduced form default model, an enhanced implementation of the Merton model, and a new hybrid model which combines Merton default probabilities with the powerful explanatory variables used in the Jarrow-Chava approach. The new models have been in development for more than two years. The version 5.0 default models are based on 1.76 million observations of public firms and 2,046 defaults. Separately, Kamakura has provided the Kamakura Risk Information Services Version 5.0 Technical Guide to clients and financial services regulators around the globe. The Technical Guide provides a complete description of model inputs and coefficients and a full suite of Basel II-compliant tests of model accuracy.

The chart reports the ROC accuracy ratio for the three new models and compares them to the KRIS version 4.0 Jarrow-Chava model and to the version 4.0 implementation of the Merton model of risky debt. The ROC accuracy ratio is based on the comparison of 3 billion pairs of one defaulting observation and one non-defaulting observation. The ROC accuracy ratio is the percentage of the time that the defaulting observation is correctly ranked as more risky than the non-defaulting observation. The chart below shows the ROC accuracy ratio for all models for the accuracy of predicting default in month N, conditional on surviving through month N-1.

The graph shows that the version 5 models have a 1month accuracy ratio of 95.10. The version 5 models are dramatically more accurate than legacy ratings and Kamakura’s version 4.1 models at all maturities, particularly at the longer maturities. In fact, the 73.13 accuracy for predicting default in month 120 conditional on surviving 119 months is higher than the Merton model’s accuracy, 72.49, in predicting default in month 15 conditional on surviving 14 months. The reduced form Jarrow-Chava model, therefore, provides 105 months of “earlier warning” than the Merton models at a comparable level of accuracy. The dramatic improvements in long run accuracy stem from significant suggestions from the diverse KRIS client base, including insights previously announced from First Rand Bank in Johannesburg.

“During the credit crisis, it became starkly apparent to many market participants that legacy Merton default technology was inconsistent with the many failures of financial institutions around the world,” reported Dr. Donald R. van Deventer, Kamakura Corporation founder and CEO. “In a crisis, cash is king, and the reduced form framework can take advantage of this insight that is ignored in the Merton framework. By extending the maturities of the KRIS default term structures to 10 years, we can now show early warning of the next ‘business cycle in the making’ to KRIS clients. One of the reasons for the very high model accuracy is the distinction that FNMA and FHLMC failed and then were rescued for some but not all liability holders. The major rating agencies, contrary to credit default swap market ‘default’ definitions, ignored these failures of AAA-rated firms in their self-assessments released in February. KRIS 5.0 is based on the recognition that these failures, and those of many other firms, are too important to ignore.”

The KRIS default probabilities are available for 29,400 public firms in 33 countries. The KRIS service also includes implied ratings and credit default swap spreads for all 29,400 firms. KRIS default probabilities are available via the web site www.kris-online.com. KRIS default probabilities are also made available via the Reuters 3000Xtra service for 2,000 firms and via file transfer protocol for KRIS “power users.” The KRIS default probabilities are integrated seamlessly in the KRIS-cpm credit portfolio manager simulation engine embedded in KRIS and with Kamakura’s enterprise wide risk management system, Kamakura Risk Manager. In KRIS-cpm, forward looking default probabilities are driven by econometric links to macro-economic factors. In Kamakura Risk Manager, these linkages can be supplied by either the user or from the KRIS data base. These relationships define the degree of correlation between the default probabilities and events of default for all pairs of companies.

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