Institutional investors around the world are required to prove to their audit committees, senior management, and regulators that their investments are in fact "investment grade." Even computer users take note of the financial strength of key vendors like Microsoft Corporation (MSFT). For many investors, "investment grade" is an internal definition; for many banks and insurance companies "investment grade" is also defined by regulators. In this note we analyze the current levels and past history of default probabilities for Microsoft Corporation. We also measure the reward, in terms of credit spread, for taking on the default risk of Microsoft Corporation bonds. On August 19, Microsoft Corporation non-call fixed rate bonds were traded 125 times for $6.5 million in volume. We use that data in this analysis.
Assuming the recovery rate in the event of default would be the same on all bond issues, 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. We analyze the maturities where the credit spread/default probability ratio is highest for Microsoft Corporation. We also consider whether or not a reasonable U.S. bank investor would judge the firm to be "investment grade" under the June 13, 2012 rules mandated by the Dodd-Frank Act of 2010, which requires that credit rating references be eliminated. The new rules delete references to legacy credit ratings and replace them with default probabilities as explained 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. The graph below shows the current default probabilities for Microsoft Corporation ranging from one month to 10 years on an annualized basis. The default probabilities range from 0.11% at one month to 0.04% at 1 year and 0.26% at ten years.
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 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 Microsoft Corporation included 125 trades in 13 fixed-rate non-callable bonds of the firm on August 19, 2013. We used all of those trades in this note.
The graph below shows 5 different yield curves that are relevant to a risk and return analysis of Microsoft Corporation bonds. These curves reflect the noise in the TRACE data, as some of the trades are small odd-lot trades. The lowest curve, in dark blue, is the yield to maturity on U.S. Treasury bonds, interpolated from the Federal Reserve H15 statistical release for that day, which matches the maturity of the traded bonds of Microsoft Corporation. The second lowest curve, in the lighter blue, shows the yields that would prevail if investors shared the default probability views outlined above, assumed that recovery in the event of default would be zero, and demanded no liquidity premium above and beyond the default-adjusted risk-free yield. The third line from the bottom (in orange) graphs the lowest yield reported by TRACE on that day on Microsoft Corporation bonds. The fourth line from the bottom (in green) displays the average yield reported by TRACE on the same day. The highest yield is obviously the maximum yield in each Microsoft Corporation issue recorded by TRACE.
The data make it clear that there is a stable but slender liquidity premium built into the yields of Microsoft Corporation above and beyond the "default-adjusted risk free curve" (the risk-free yield curve plus the matched maturity default probabilities for the firm). The credit spreads are relatively smooth across the maturity spectrum with the exception of the longest maturity bond issues. The credit spreads generally widen with maturity, the normal pattern for a high quality credit.
The high, low and average credit spreads at each maturity are graphed below. Credit spreads are gradually increasing with the maturity of the bonds, with the exception of both the very short maturities and the longest maturities.
Using default probabilities in addition to credit spreads, we can analyze the number of basis points of credit spread per basis point of default risk at each maturity. This ratio of spread to default probability is shown in the following table for Microsoft Corporation. At all maturities, the reward from holding the bonds of Microsoft Corporation, relative to the matched maturity default probability, is between 2.50 and 5.65 basis points of credit spread reward for every basis point of default risk. The ratio of spread to default probability increases with maturity once the maturity of the bonds exceeds 5 years.
The credit spread to default probability ratios are shown in graphic form here:
The Depository Trust & Clearing Corporation reports weekly on new credit default swap trading volume by reference name. For the week ended August 9, 2013 (the most recent week for which data is available), the credit default swap trading volume on Microsoft Corporation was zero. The number of credit default swap contracts traded on Microsoft Corporation in the 155 weeks ended June 28, 2013 is also zero; Microsoft Corporation credit default swaps did not trade even once during that three year period.
On a cumulative basis, the default probabilities for Microsoft Corporation range from 0.04% at 1 year to 2.59% at 10 years, as shown in the following graph.
Over the last decade, the 1 year and 5 year default probabilities for Microsoft Corporation have varied as shown in the following graph. The one year default probability peaked at just under 0.25% and the 5 year default probability has risen strongly in the last 3 months, closing at 0.16% on August 19.
The macro-economic factors driving the historical movements in the default probabilities of Microsoft Corporation include the following factors among those listed by the Federal Reserve in its 2013 Comprehensive Capital Analysis and Review:
- Unemployment rate
- 3 month U.S. Treasury bill rates
- Dow Jones Industrials stock index
- The VIX volatility index
- Home price index
- 3 international macro factors
These macro factors explain 89.9% of the variation in the default probability of Microsoft Corporation.
Microsoft Corporation can be compared with its peers in the same industry sector, as defined by Morgan Stanley (MS) and reported by Compustat. For the USA software and services sector, Microsoft Corporation has the following percentile ranking for its default probabilities among its 444 peers at these maturities:
1 month 70th percentile
1 year 45th percentile
3 years 23rd percentile
5 years 15th percentile
10 years 15th percentile
Although Microsoft Corporation is highly rated by legacy rating agencies, the percentile rankings of its default probabilities range from the 15th to the 70th percentile, with the percentile rank improving as the maturity lengthens to the 15th percentile. A comparison of the legacy credit rating for Microsoft Corporation with predicted ratings indicates that the statistically predicted rating is eight notches lower than the actual credit rating. Microsoft Corporation is one of the most overrated public firms in the world.
Microsoft boasts an excellent legacy credit rating in spite of default probabilities that are mediocre except at 5 and 10 year maturities. Since the firm is overrated by 8 notches according to the best possible statistical estimates, the reward to Microsoft Corporation bond holders has been compressed to levels that are also mediocre, 2.5 to 5.65 basis points of credit spread per basis point of default risk. We believe that the overwhelming majority of analysts would rate Microsoft Corporation as investment grade. We also believe that bond investors who are not seduced by a supremely optimistic legacy credit rating will find better value in the bonds of other issuers covered in these series of notes.
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.