J. P. Morgan Asset Management has released an important fixed income strategy study by Managing Director Douglas Niemann that features Kamakura Risk Information Services default probabilities. Mr. Niemann, Managing Director of Global Insurance Solutions, demonstrates how the decline in market-making in the bond markets in recent years has created special opportunities for fixed income investors who can invest for the longer term. The key, Mr. Niemann argues, is the ability to parse the total credit spread on a bond into its pure credit component, driven by the issuer default probability and the recovery rate on the bond issue, and the liquidity component that rewards the buyer for providing long term liquidity. Kamakura Corporation research is featured prominently in the article. Mr. Niemann provides a roadmap for investors who are making the transition from qualitative credit ratings to more modern and more accurate quantitative default probabilities.
Mr. Niemann's article "Making the Most of Interesting Times in the Bond Markets" is available on the J. P. Morgan web site. Mr. Niemann is featured in a separate video presentation that is featured here:
Kamakura Corporation has embedded its extensive research on the relationship between credit spreads and default risk in its risk information and risk management software products:
- KRIS default probabilities are available for public firms, non-public firms, sovereigns, retail mortgages and a number of other counterparty types that have not yet been publicly announced. The KRIS default probability service spans 34,000 public firms in 61 countries, and the sovereign default probability service covers 183 countries. Kamakura's combined default probability estimation data bases include a total of more than 15 million observations and more than 45,000 defaults.
- The KRIS service contains an "implied spread" calculation the provides the best available estimate of fair pricing on a five year credit default swap for 34,000 publicly traded companies, compared to an average of only 900 firms for which there is at least one credit default swap trade in an average week.
- Kamakura Managing Director Prof. Robert Jarrow has provided key guidance on the relationship between modern reduced form default probabilities and credit spreads at Kamakura for nearly two decades. References are given below.
- Kamakura Risk Manager seamlessly loads the Kamakura Risk Information Services default probabilities and their statistical linkages to macro-economic risk factors for stress testing, credit adjusted value at risk, capital adequacy assessment, asset and liability management, credit-adjusted transfer pricing, regulatory capital analysis and forecasting, and liquidity risk measurement.
Martin Zorn, President and Chief Operating Officer for Kamakura Corporation, said Monday, "We think there is tremendous opportunity for portfolio managers that adopt modern credit risk technology and incorporate the tools into their investing strategies to earn excess returns. Advising clients in that regard and providing them with the risk information and risk management software to achieve that objective is what Kamakura Corporation is all about. For more information about the paper, please contact Mr. Niemann at douglas.niemann@JPMorgan.com."
Key Analytical Insights and Examples of the Relationships Between Credit Spreads and Default Probabilities
Kamakura Corporation strongly recommends that investors explore the modern quantitative research that documents the high degree of accuracy that modern default probabilities have achieved. The Kamakura Risk Information Services version 5.0 Jarrow-Chava reduced form default probability model (abbreviated KDP-jc5) makes default predictions using a sophisticated combination of financial ratios, stock price history, and macro-economic factors. The version 5.0 model was estimated over the period from 1990 to 2008, and includes the insights of the worst part of the recent credit crisis. Kamakura default probabilities are based on 1.76 million observations and more than 2000 defaults. The term structure of default is constructed by using a related series of econometric relationships estimated on this data base. KRIS covers 35,000 firms in 61 countries, updated daily. Free trials are available at Info@Kamakuraco.com. An overview of the full suite of Kamakura default probability models is available here.
General Background on Reduced Form Models
For a general introduction to reduced form credit models, Hilscher, Jarrow and van Deventer (2008) is a good place to begin. Hilscher and Wilson (2013) have shown that reduced form default probabilities are more accurate than legacy credit ratings by a substantial amount. Van Deventer (2012) explains the benefits and the process for replacing legacy credit ratings with reduced form default probabilities in the credit risk management process. The theoretical basis for reduced form credit models was established by Jarrow and Turnbull (1995) and extended by Jarrow (2001). Shumway (2001) was one of the first researchers to employ logistic regression to estimate reduced form default probabilities. Chava and Jarrow (2004) applied logistic regression to a monthly database of public firms. Campbell, Hilscher and Szilagyi (2008) demonstrated that the reduced form approach to default modeling was substantially more accurate than the Merton model of risky debt. Bharath and Shumway (2008), working completely independently, reached the same conclusions. A follow-on paper by Campbell, Hilscher and Szilagyi (2011) confirmed their earlier conclusions in a paper that was awarded the Markowitz Prize for best paper in the Journal of Investment Management by a judging panel that included Prof. Robert Merton.
Recent Kamakura Bond Risk and Return Studies
A wide array of bond risk and return studies has been released in recent months. A few examples are listed here, with associated links:
Best Value Bond Investment Strategy
Individual Issuer Credit Assessment
Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.