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. In this note we analyze the current levels and past history of default probabilities for Morgan Stanley (MS). As part of this analysis, we 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. On its web page the OCC states, "Under the revised regulations, to determine whether a security is 'investment grade,' banks must determine that the probability of default by the obligor is low and the full and timely repayment of principal and interest is expected." 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 Morgan Stanley ranging from one month to 10 years on an annualized basis.
We explain the source and methodology for the default probabilities below. On a cumulative basis, the default probabilities for Morgan Stanley range from 0.15% at 1 year to 2.17% at 10 years as shown in this graph:
Over the last 10 years, the 1 year and 5 year default probabilities for Morgan Stanley have varied as shown in the following graph.
On September 29, 2008, Morgan Stanley borrowings from the Federal Reserve peaked at $61.3 billion as documented in this report. Over the last decade, the legacy credit ratings for Morgan Stanley have changed only four times.
The macro-economic factors driving the historical movements in the default probabilities of Morgan Stanley 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:
Real disposable income growth
Nominal disposable income growth
U.S. 3 month Treasury bill yield
30 year fixed rate mortgage yield
S&P volatility index
5 international macro factors
These factors explain 88.0% of the movement in the 1 year default probability for Morgan Stanley. Morgan Stanley can be compared with its peers in the same industry sector. The definition of peer group is defined by Morgan Stanley and distributed by Compustat. For the diversified financial sector in the USA, Morgan Stanley has the following percentile ranking for its default probabilities among its peers at these maturities (100 = highest):
1 month 89th percentile
1 year 80th percentile
3 years 74th percentile
5 years 48th percentile
10 years 34th percentile
A comparison with the legacy credit rating for Morgan Stanley indicates that the company is overrated by 3 ratings grades. This calculation is based on 263,000 observable ratings over the period from 1990 to the present.
Morgan Stanley ranks in the riskiest half of USA diversified financials at all maturities from one month to three years. Morgan Stanley ranks in the least risky half of USA diversified financials for maturities from five years to ten years. Morgan Stanley's default probabilities have declined very substantially from the levels at the worst part of the financial crisis, however. Most investment professionals, using the current default probability levels and macro-factor sensitivity for Morgan Stanley, would indicate that the company is "investment grade" by the definition of the Comptroller of the Currency given above.
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.