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SunTrust Bank 1 Year Default Probability 0.60% Versus SunTrust Banks, Inc. 2007-2015

|Includes: SunTrust Banks, Inc. (STI)


The chart displays the default probabilities as of today for both the parent company and subsidiary U.S. banking legal entities.

The blue line is the banking subsidiary's one year default probability using the Kamakura Risk Information Services U.S. Bank Model, Version 1.0, released in August 2014. The yellow line is the one year default probability of the publicly-held parent company.

The default probabilities can differ widely because there is a substantial difference in information available at the bank level. In general, the bank level financial statements in the Quarterly Report of Condition (also known as "call reports") are much more banking-specific than the parent firm's financial statements. On the other hand, the privately held bank subsidiaries have no stock price so insights from the stock price are not available.

Background on the Kamakura U.S. Bank Model

The Kamakura U.S. Bank Model (abbreviated "KDP-BK1" for Kamakura Default Probability, Bank Model Version 1.0) was launched in 2014 after three years of development by Kamakura Risk Information Services. The model was developed using the insights of Prof. Robert A. Jarrow, Kamakura Managing Director of Research and Senior Fellow at the Federal Deposit Insurance Corporation. In his role at the Federal Deposit Insurance Corporation, Prof. Jarrow co-authored the FDIC's 2003 Loss Distribution Model, which correctly forecast that the FDIC deposit insurance fund was significantly under-funded. The new model uses more than 2 million monthly observations of U.S. commercial banks and a time period that spans the full credit crisis experience for maximum accuracy. The KDP-BK1 model is even more accurate than the widely respected Kamakura public firm models. The Kamakura U.S. Bank Model is a modern reduced form model developed using the insights gleaned from Kamakura's public firm models, non-public firm models, and sovereign models.

Background on the Kamakura Public Firm Default Probability Models

For an example of how to apply modern default probabilities for risk management and portfolio selection, please see the introduction to Kamakura's premium service The Corporate Bond Investor and this week's ranking of the most heavily traded corporate bond issues by "best value."

The Kamakura Risk Information Services version 6.0 Jarrow-Chava reduced form default probability model (abbreviated KDP-jc6) makes default predictions using a sophisticated combination of financial ratios, stock price history, and macro-economic factors. The version 6.0 model was estimated over the period from 1990 to 2014, and includes the insights of the recent credit crisis. Kamakura default probabilities are based on 2.2 million observations and more than 2,700 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 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.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.