TRIUM Exam Question
Professor Edward Altman
In August 2017, Tesla Motors raised $1.8 billion in corporate bonds,
priced at 5.3%, 8-year notes. The bonds were subordinated to more senior
debt and received a B- rating from S&P and a B3 rating from Moody’s.
(1) Using the credit analytics discussed in our class, and traditional
metrics, what does your group think should be Tesla’s bond rating
before and just after the new bond issue?
(2) Would your answer change if the firm raised an additional $3 billion in
bonds to meet production objectives?
(3) What is your estimate of the Bond Rating Equivalent (BRE) as of the
most recent (Q1-2019) financials and latest (June 26, 2019) stock
(4) Given your answers #1 and #2 above, what are your expected
cumulative PD (Probability of Default) and LGD (Loss Given Default)
for Tesla for one-year and five (5) years?
(5) What are the bonds issued in 2017 now (June 26, 2019) selling at
and what is the bond’s yield to maturity?
(6) Which of the two Z-Score models (Z or Z”) is most applicable to a firm
like Tesla? Why?
(7) What are the main differences between Z and Z”? List up to four
Please work on this question with no less than two (2) members and no
more than three (3). Do not confer with other groups with respect to any
aspect of this question. Limit your answer to no more than three (3) pages,
(double-spaced) plus Exhibits (no Appendices). Please make sure the
typeface is clear and large enough so it is easily legible.
TRIUM Class of 2020: Module 4 − Pack 3: Credit
TRIUM Global Executive MBA
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TRIUM Class of 2020: Module 4 − Pack 3: Credit Risk
Table of Contents
“Toward a Botton−Up Approach to Assessing Sovereign Default Risk: An
Update” by Altman, Edward I; Rijken, Herbert
“The Fate of the Euro: It is Still Italia!” by Altman, Edward I
“Defaults and Returns in the High−Yield Bond and Distressed Debt Market:
The Year 2018 in Review and Outlook” by Altman, Edward I; Kuehne,
“The Investment Performance and Market Dynamics of Defaulted and
Distressed Corporate Bonds and Bank Loans: 2018 Review and 2019
Outlook” by Altman, Edward I; Kuehne, Brenda J
“A 50−Year Retrospective on Credit Risk Models, the Altman Z−Score
Family of Models and Their Applications to Financial Markets and
Managerial Strategies” by Altman, Edward I
Toward A Bottom-Up Approach to Assessing Sovereign Default Risk: An Update*
Edward I. Altman, New York University Stern School of Business, Herbert Rijken, Vrije
We propose a totally new approach toward assessing sovereign risk
by examining rigorously the health and aggregate default risk of a nation’s
private corporate sector. Models such as our new Z-Metrics™ approach can
be utilized to measure the median probability of default of the non-financial
sector cumulatively for five years, both as an absolute measure of corporate
risk vulnerability and a relative measure compared to other sovereigns and
to the market’s assessment via the now liquid credit-default-swap market.
Specifically, we measure the default probabilities of listed corporate entities
in nine European countries, and the U.S.A., as of 2009 and 2010. These
periods coincide with the significant rise in concern with sovereign default
risk in the Euro country sphere. We conclude that our corporate health
index of the private sector measured at periods prior to the explicit
recognition by most credit professionals, not only gave an effective early
warning indicator but provided a mostly appropriate hierarchy of relative
sovereign risk. Policy officials should, we believe, nurture, not penalize, the
tax revenue paying and jobs generating private sector when considering
austerity measures of distressed sovereigns.
Key Words: Sovereign Risk, Financial Crisis, Default Probability, Z-Metrics
JEL classification: F34, F36
This is an updated version of the article originally published in The Journal of Applied Corporate Finance, vol.23,
No. 3, Winter, 2011.
**The authors would like to thank Dan Balan and Matthew Watt of RiskMetrics Group, a subsidiary of MSCI, Inc.,
for computational assistance, and Brenda Kuehne of the NYU Salomon Center for her research assistance.
During the past four years, bank executives, government officials, and many others have been
sharply criticized for failing to anticipate the global financial crisis. The speed and depth of the
market declines shocked the public. And no one seemed more surprised than the credit rating
agencies that assess the default risk of sovereign governments as well as corporate issuers
operating within their borders.
Although the developed world had suffered numerous recessions in the past 150 years,
this most recent international crisis raised grave doubts about the ability of major banks and even
sovereign governments to honor their obligations. Several large financial institutions in the U.S.
and Europe required massive state assistance to remain solvent, and venerable banks like
Lehman Brothers even went bankrupt. The cost to the U.S. and other sovereign governments of
rescuing financial institutions believed to pose “systemic” risk was so great as to result in a
dramatic increase in their own borrowings.
The general public in the U.S. and Europe found these events particularly troubling
because they had assumed that elected officials and regulators were well-informed about
financial risks and capable of limiting serious threats to their investments, savings, and pensions.
High-ranking officials, central bankers, financial regulators, ratings agencies, and senior bank
executives all seemed to fail to sense the looming financial danger.
This failure seemed even more puzzling because it occurred years after the widespread
adoption of advanced risk management tools. Banks and portfolio managers had long been using
quantitative risk management tools such as Value at Risk (“VaR”). And they should also have
benefited from the additional information about credit risk made publicly available by the new
market for credit default swaps (“CDS”).
But, as financial market observers have pointed out, VaR calculations are no more
reliable than the assumptions underlying them. Although such assumptions tend to be informed
by statistical histories, critical variables such as price volatilities and correlations are far from
constant and thus difficult to capture in a model. The market prices of options—or of CDS
contracts, which have options “embedded” within them—can provide useful market estimates of
volatility and risk. And economists have found that CDS prices on certain kinds of debt
securities increase substantially before financial crises become full-blown. But because there is
so little time between the sharp increase in CDS prices and the subsequent crisis, policy makers
and financial managers typically have little opportunity to change course.1
Most popular tools for assessing sovereign risk are effectively forms of “top-down”
analysis. For example, in evaluating particular sovereigns, most academic and professional
analysts use macroeconomic indicators such as GDP growth, national debt-to-GDP ratios, and
trade and budget deficits as gauges of a country’s economic strength and well-being. But, as the
recent Euro debt crisis has made clear, such “macro” approaches, while useful in some settings
and circumstances, have clear limitations
In this paper, we present a totally new method for assessing sovereign risk, a type of
“bottom-up” approach that focuses on the financial condition and profitability of an economy’s
private sector. The assumption underlying this approach is that the fundamental source of
national wealth, and of the financial health of sovereigns, is the economic output and
productivity of their companies. To the extent we are correct, such an approach could provide
financial professionals and policy makers with a more effective means of anticipating financial
See, for example, Hekran Neziri’s “Can Credit Default Swaps predict Financial Crises?” in the Spring 2009
Journal of Applied Economic Sciences, Volume IV/Issue 1(7). Neziri found that CDS prices had real predictive
power for equity markets, but that the lead time was generally on the order of one month.
trouble, thereby enabling them to understand the sources of problems before they become
In the pages that follow, we introduce Z-Metrics™, as a practical and effective tool for
estimating sovereign risk. Developed in collaboration with the Risk Metrics Group, now a
subsidiary of MSCI, Inc., Z-Metrics is a logical extension of the Altman Z-Score technique that
was introduced in 1968 and has since achieved considerable scholarly and commercial success.
Of course, no method is infallible, or represents the best fit for all circumstances. But by
focusing on the financial health of private enterprises in different countries, our system promises
at the very least to provide a valuable complement to, or reality check on, standard “macro”
But before we delve into the details of Z-Metrics, we start by briefly reviewing the
record of financial crises to provide some historical perspective. Next we attempt to summarize
the main findings of the extensive academic and practitioner literature on sovereign risk,
particularly those studies designed to test the predictability of sovereign defaults and crises.
With that as background, we then present our new Z-Metrics system for estimating the
probability of default for individual (non-financial) companies and show how that system might
have been used to anticipate many developments during the current EU debt crisis. In so doing,
we make use of the most recent (2009 and 2010) publicly available corporate data for nine
European countries, both to illustrate our model’s promise for assessing sovereign risk and to
identify scope of reforms that troubled governments must consider not only to qualify for
bailouts and subsidies from other countries and international bodies, but to stimulate growth in
More specifically, we examine the effectiveness of calculating the median company fiveyear probability of default of the sovereign’s non-financial corporate sector, both as an absolute
measure of corporate risk vulnerability and a relative health index comparison among a number
of European sovereigns, and including the U.S. as well. Our analysis shows that this health
index, measured at periods prior to the explicit recognition of the crisis by market professionals,
not only gave a distinct early warning of impending sovereign default in some cases, but also
provided a sensible hierarchy of relative sovereign risk. We also show that, during the current
European crisis, our measures not only compared favorably to standard sovereign risk measures,
notably credit ratings, but performed well even when compared to the implied default rates built
into market pricing indicators such as CDS spreads (while avoiding the well-known volatility of
Our aim here is not to present a “beauty contest” of different methods for assessing
sovereign risk in which one method emerges as the clear winner. What we are suggesting is that
a novel, bottom-up approach that emphasizes the financial condition and profitability of a
nation’s private sector can be effectively combined with standard analytical techniques and
market pricing to better understand and predict sovereign health. And our analysis has one clear
implication for policy makers: that the reforms now being contemplated should be designed, as
far as possible, to preserve the efficiency and value of a nation’s private enterprises.
Modern History Sovereign Crises
When thinking about the most recent financial crisis, it is important to keep in mind how
common sovereign debt crises have been during the last 150 years—and how frequently such
debacles have afflicted developed economies as well as emerging market countries. Figure 1
shows a partial list of financial crises (identified by the first year of the crisis) that have occurred
in “advanced” countries. Overall, Latin America seems to have had more recent bond and loan
defaults than any other region of the world (as can be seen in Figure 2). But if we had included a
number of now developed Asian countries among the “advanced” countries, the period 19971999 period would be much more prominent.
Financial Crises, Advanced Countries 1870-2010
Crisis events (first year)
1914, 1931, 1939
1921, 1931, 1987
1930, 1935, 1990
1931, 1978, 2008
1907, 1922, 1931, 1991
1893, 1907, 1929, 1984, 2008
Source: IMF Global Financial Stability Report (2010), Reinhart and Rogoff (2010), and various other
sources, such as S&P’s economic reports.
Source: Compilation by Ingo Walter, NYU Stern School of Business
The clear lesson from Figures 1 and 2 is that sovereign economic conditions appear to
spiral out of control with almost predictable regularity and then require massive debt
restructurings and/or bailouts accompanied by painful austerity programs. Recent examples
include several Latin American countries in the 1980s, Southeast Asian nations in the late 1990s,
Russia in 1998, and Argentina in 2000. In most of those cases, major problems originating in
individual countries not only imposed hardships on their own people and markets, but had major
financial consequences well beyond their borders. We are seeing such effects now as financial
problems in Greece and other southern European countries not only affect their neighbors, but
threaten the very existence of the European Union.
Such financial crises have generally come as a surprise to most people, including even
those specialists charged with rating the default risk of sovereigns and the enterprises operating
in these suddenly threatened nations. For example, it was not long ago that Greek debt was
investment grade, and Spain was rated Aaa as recently as June 2010.2 And this pattern has been
seen many times before. To cite just one more case, South Korea was viewed in 1996 as an
“Asian Tiger” with a decade-long record of remarkable growth and an AA- rating. Within a year
however, the country was downgraded to BB-, a “junk” rating, and the county’s government
avoided default only through a $50 billion bailout by the IMF. And it was not just the rating
agencies that were fooled; most of the economists at the brokerage houses also failed to see the
problems looming in Korea.
What Do We Know about Predicting Sovereign Defaults?
There is a large and growing body of studies on the default probability of sovereigns, by
practitioners as well as academics.3 A large number of studies, starting with Frank and Cline’s
1971 classic, have attempted to predict sovereign defaults or rescheduling using statistical
classification and predicting methods like discriminant analysis as well as similar econometric
techniques.4 And in a more recent development, some credit analysts have begun using the
“contingent claim” approach5 to measure, analyze, and manage sovereign risk based on Robert
Merton’s classic “structural” approach (1974). But because of its heavy reliance on market
On April 27, 2010, Standard & Poor’s Ratings Services lowered its long- and short-term credit ratings on the
Hellenic Republic (Greece) to non-investment grade BB+; and on June 14, 2010, Moody’s downgraded Greece debt
to Ba1 from A2 (4 notches), while Spain was still Aaa and Portugal was A1. Both of the latter were recently
downgraded. S&P gave similar ratings.
One excellent primer on sovereign risk is Babbel’s (1996) study, which includes an excellent annotated
bibliography by S. Bertozzi on external debt capacity that describes many of these studies. Babbel lists 69
potentially helpful explanatory factors for assessing sovereign risk, all dealing with either economic, financial,
political, or social variables. Except for the political and social variables, all others are macroeconomic data and this
has been the standard until the last few years. Other work worth citing include two practitioner reports—Chambers
(1997) and Beers et al (2002)—and two academic studies—Smith and Walter (2003), and Frenkel, Karmann and
Scholtens (2004). Full citations of all studies can be found in References section at the end of the article.
Including Grinols (1976), Sargen (1977), Feder and Just (1977), Feder, Just and Ross (1981), Cline (1983),
Schmidt (1984), and Morgan (1986).
Gray, Merton and Bodie (2006, 2007)
indicators, this approach to predicting sovereign risk and credit spreads has the drawback of
producing large—and potentially self-fulfilling—swings in assessed risk that are attributable
solely to market volatility.
A number of recent studies have sought to identify global or regional common risk
factors that largely determine the level of sovereign risk in the world, or in a region such as
Europe. Some studies have shown that changes in both the risk factor of individual sovereigns
and in a common time-varying global factor affect the market’s repricing of sovereign risk.6
Other studies, however, suggest that sovereign credit spreads are more related to global
aggregate market indexes, including U.S. stock and high-yield bond market indexes, and global
capital flows than to their own local economic measures.7 Such evidence has been used to
justify an approach to quantifying sovereign risk that uses the local stock market index as a
proxy for the equity value of the country.8 Finally, several very recent papers focus on the
importance of macro variables such as debt service relative to tax receipts and the volatility of
trade deficits in explaining sovereign risk premiums and spreads.9
A number of studies have also attempted to evaluate the effectiveness of published credit
ratings in predicting defaults and expected losses, wit ...
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