Today's focus is on the risk and return from the bonds of General Electric Co. (NYSE:GE) based on July 10, 2013 trades. Although General Electric Capital Corporation had 1,592 trades in its bonds on July 10, 16 times more than trading in its parent's bonds, we defer analysis of GECC to another day. A sophisticated investor who has moved beyond legacy ratings seeks to maximize revenue per basis point of default risk from each incremental investment, subject to risk limits on macro-factor exposure on a fully default-adjusted basis. All other things being equal, maximizing the ratio of credit spread to the matched maturity default probability will achieve this objective. We analyze the premium in credit spreads over default probabilities for General Electric Co. based on 102 trades in the firm's bonds on July 10, 2013. As part of this analysis, we also consider whether or not a reasonable investor would judge the firm to be "investment grade" under the June 2012 rules mandated by the Dodd-Frank Act of 2010.
Definition of Investment Grade
On June 13, 2012, the Office of the Comptroller of the Currency published the final rules defining whether a security is "investment grade," in accordance with Section 939A of the Dodd-Frank Act of 2010. The main focus of the new rules is on default probabilities, not legacy credit ratings. The web page explaining the Office of the Comptroller of the Currency's new rules defining investment grade and related guidance can be found here.
Term Structure of Default Probabilities
Maximizing the ratio of credit spread to matched maturity default probabilities requires that default probabilities be available at a wide range of maturities. This graph shows the current default probabilities for General Electric Co. ranging from one month to 10 years on an annualized basis.
Annualized default probabilities for GE range from 0.06% at one year to 0.41% at a ten year maturity. We explain the source and methodology for the default probabilities below.
Summary of Recent Bond Trading Activity
The National Association of Securities Dealers launched the TRACE (Trade Reporting and Compliance Engine) in July 2002 in order to increase price transparency in the U.S. corporate debt market. The system captures and information on secondary market transactions in publicly traded securities (investment grade, high yield and convertible corporate debt) representing all over-the-counter market activity in these bonds. TRACE data for General Electric Co. shows 102 trades in four distinct bonds on July 10, 2013.
The table compares the highest, lowest and average credit spread at each maturity with the interpolated Kamakura default probabilities for that maturity. The table and the graph below shows that the bond with the shortest maturity offers an average of 7.07 basis points of credit spread for each basis point of default probability. The 7.07 ratio of credit spread to default probability then declines and levels out at a 2.15 ratio for a maturity of 29 years. Note that we have assumed the 10 year Kamakura default probability applies to longer maturities in making this calculation.
The Depository Trust & Clearing Corporation reports weekly on new credit default swap trading volume by reference name. For the week ended July 5, 2013 (the most recent week for which data is available), the credit default swap trading volume on General Electric Co. was zero. GECC, by contrast, had 20 contracts for a notional value of $162 million change hands.
On a cumulative basis, the default probabilities for General Electric Co. range from 0.06% at 1 year to 4.01% at 10 years.
Over the last 10 years, the 1 year and 5 year default probabilities for General Electric Co. have varied as shown in the following graph.
Note that, in 2009, the one year default probability for General Electric peaked near 4.00%. Note also that the General Electric Co. family borrowed a peak of $16.1 billion over 115 days under the Federal Reserve's Commercial Paper Funding Facility. Details of borrowings of GE and other firms under this program from 2008 to 2010 are documented in this report. In spite of the recent credit drama at General Electric, the legacy credit rating of General Electric has changed only once since 1956 (in March 2009).
The macro-economic factors driving the historical movements in the default probabilities of General Electric Co. over the period from 1990 to the present include the following factors among those included by the Federal Reserve in its 2013 Comprehensive Capital Analysis and Review:
- Nominal gross domestic product
- U.S. Treasury 3 month bill rate
- The yield on BBB rated corporate bonds
- The yield on 30 year fixed rate mortgages
- The VIX volatility index
- Home prices
- Commercial real estate prices
- 2 international macro factors
These factors jointly explain 91.6% in the variation of the 1 year default probability of General Electric.
General Electric Co. can be compared with its peers in the same industry sector, as defined by Morgan Stanley and reported by Compustat. For the US "industrials" sector, General Electric Co. has the following percentile ranking for its default probabilities among its peers at these maturities:
1 month 74th percentile
1 year 56th percentile
3 years 38th percentile
5 years 30th percentile
10 years 29th percentile
An analysis of the legacy credit rating for General Electric Co. indicates that the company is overrated by 7 ratings grades.
General Electric Co. is in the riskier half of its industrial peers from a default risk perspective for maturities of one year and shorter. GE moves into the safer half of the peer group for maturities of 3 years and longer. As of July 10, bond data from TRACE indicated that GE bonds with 2.25 years to maturity offered more than 7 basis points of credit spread for each basis point of default risk, nearly triple the ratio observed on GE bonds with a 29 year maturity. We believe the majority of credit analysts, on the basis of this information, would classify General Electric Co. as "investment grade" by the Comptroller of the Currency definition.
Background on Default Probabilities Used
The Kamakura Risk Information Services version 5.0 Jarrow-Chava reduced form default probability model 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. An overview of the full suite of related 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.