Journal of Applied Corporate Finance
S P R I N G
20 0 2
Toward a More Complete Model of Optimal Capital Structure
by Roger Heine and Fredric Harbus,
Deutsche Bank Securities Inc.
V O L U M E
15 . 1
TOWARD A MORE
COMPLETE MODEL
OF OPTIMAL CAPITAL
STRUCTURE
by Roger Heine and Fredric Harbus,
Deutsche Bank Securities Inc.*
iability management plays an important but often overlooked
L
role in creating shareholder value. Classic capital structure
theory tends to focus on the level of debt relative to total firm
value and typically balances the potential value of interest tax
shields against the expected costs associated with financial distress.1 Consistent
with this theory, most corporate finance practitioners understand the trade-off
involved in making effective use of debt capacity while safeguarding the firm’s
ability to execute its business strategy without disruption. But quantifying that
trade-off to arrive at an optimal level of debt can be a complicated and
challenging task. Moreover, there are a host of questions about the structure of
the firm’s debt—for example, whether the debt should be fixed or floating, longterm or short-term, and denominated in local or a foreign currency—that must be
considered when determining a company’s value-maximizing capital structure.
In an article published in this journal in 1997, Tim Opler, Michael Saron,
and Sheridan Titman presented an economic model that simulates the effect of
different capital structure choices on shareholder value.2 The basic insight of the
model (henceforth referred to as “Opler et al.”) is that while judicious use of debt
can add value by reducing corporate taxes and strengthening management
incentives to increase efficiency, too much debt can result in underinvestment,
a loss of business, and perhaps a costly reorganization. The Opler et al. model
aims to identify the value-maximizing debt-equity ratio (as well as the optimal
percentage of fixed vs. floating)—one that does the best job of balancing the
value of the tax shield from debt against the expected cost of financial distress.
*This paper does not express the views of Deutsche Bank Securities Inc. or any of its affiliates.
1. See, for example, Richard Brealey and Stewart Myers, Principles of Corporate Finance, 6th Edition (McGraw-Hill, 2000)
for a comprehensive review of traditional capital structure theory.
2. Tim Opler, Michael Saron, and Sheridan Titman, “Designing Capital Structure to Create Shareholder Value,” Journal
of Applied Corporate Finance, Vol. 10 No. 1 (Spring 1997), pp. 21-32.
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JOURNAL OF APPLIED CORPORATE FINANCE
We have developed a capital structure optimization model (the Deutsche Bank Liability Structure
Model, or “DBLSM”) that expands on the work of
Opler et al. in several ways. We provide a more
comprehensive capital structure framework that is
integrated with a detailed set of interest rate and
foreign exchange simulation models that have many
features in common with contemporary value-at-risk
(VaR) techniques. We also model financial distress
costs in terms of several new components. In
DBLSM, the distress costs of too much debt include
the costs associated with missed investment opportunities when capital expenditures cannot be fully
funded, the reduced operating cash flows and higher
working capital needs that occur at lower ratings,
and the potential signaling costs of cutting the
dividend. DBLSM also allows for a broader set of
capital structure decision variables. For example,
where the model of Opler et al. produces a single
optimal debt ratio, the output of DBLSM includes
both a “target” and a “fallback” debt structure. The
basic idea is that when a company is doing well and
its cash flows are strong, debt is paid down to a level
consistent with the firm’s target credit rating. But if
conditions worsen and cash flows turn down, management is prepared to allow its leverage ratio to move
to a temporarily higher level (corresponding to a
lower “fallback” rating) in order to fund capital
expenditures or dividends that might otherwise have
to be cut. Thus, the company’s target credit rating
determines its “permanent” debt capacity, while the
fallback rating can be thought of as determining the
optimal amount of cost-effective reserve debt capacity
that the firm can draw upon when needed.
Besides producing target and fallback credit
ratings, DBLSM can be used to simulate the effects
of using floating versus fixed-rate debt, varying the
maturity and currency structure of future debt issues,
designing different dividend and stock repurchase
policies, and changing the level and composition of
explicit liquidity reserves (as opposed to reserve
debt capacity)—all within the same integrated simulation framework. The standard model can also be
customized as needed to address special topics such
as acquisition funding strategies or the impact of
employee stock option plans. The model has been
applied to dozens of companies in a variety of
nonfinancial industries around the world.
How does the model work? It begins by developing a set of simulation paths with both operating
cash flow and market rate components. Specifically,
based on an industry and company-specific statistical analysis, DBLSM simulates thousands of alternative forecasts of monthly operating cash flows (as
approximated by EBITDA, or earnings before interest, taxes, depreciation and amortization), typically
going out 20 years into the future. Then, using Monte
Carlo simulation methodologies,3 DBLSM projects
monthly interest rates across the yield curve as well
as FX rates for all major currencies over the same 20year time horizon. The EBITDA, interest rate, and FX
projections together define our final simulation
paths, where each path has a unique set of values for
these variables at each monthly time point. Once the
set of paths is established, it becomes the background environment against which a variety of
alternative capital structure assumptions are applied
and evaluated to determine which structure maximizes shareholder value.
The shareholder value calculation reflects both
expected cost and risk components, with risk measured in a variety of ways. We frequently find that debt
structure decisions, such as the fixed vs. floating mix,
end up affecting shareholder value as much as the
overall level of debt, at least over a broad range of
investment-grade credit ratings. We also find that,
especially for companies operating in volatile business
segments, significant value may be added by building
in the financing flexibility afforded by a lower fallback
rating in bad times. In this sense, a company’s key target
credit ratios like leverage and interest coverage are
“dynamic”; that is, they are expected to vary over the
firm’s cash flow cycle as its rating fluctuates between
the permanent and fallback levels.4
In addition to this dynamic aspect provided by
the fallback rating concept, the DBLSM framework
3. More specifically, non-arbitrage constrained, stochastic methods. The
techniques used to generate these simulation paths are similar to methodologies
commonly employed to value options, including the estimation of lognormal
volatilites, cross correlations, and mean reversion. However, the models we
employ are not forced to converge to arbitrage-free implied forward levels but can
instead reflect both near-term forecasts and long-term means based upon statistical
observations and judgment. As discussed later in the context of the fixed versus
floating rate debt analysis, this allows us to build a risk premium into the rate
structure.
4. While credit ratios will correspond with the modeled ratings, we do not
claim that the company’s actual rating moves in lock-step with the modeled rating.
To better reflect the stickiness of actual credit ratings, however, our rating submodel incorporates a two-year look-ahead feature: even if credit ratios at a point
in time in DBLSM would indicate a higher rating, the rating will not be upgraded
unless, based on the average EBITDA trend line, the credit profile two years ahead
is also improved; similarly, a downgrade will not occur unless the profile is also
worse two years ahead.
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We generally find that the additional cost of such [liquidity] insurance is fairly
modest in relation to “normal” capital costs, and quite small compared to the total
market capitalization of the firm.
MEASUREMENT OF SHAREHOLDER VALUE
UNDER “NORMAL” VOLATILITY
also has a “liquidity insurance” component that
distinguishes it from classic capital structure models.
In most approaches, optimal capital structure is
based on the assumption of “normal” operating cash
flows and business conditions that reflect the known
historical ranges of interest rate and foreign exchange rate volatility. But particularly since 1998,
companies have increasingly encountered sudden
and severe operating problems that have been
compounded by a loss of financial flexibility and
liquidity. Unable to raise unsecured debt in the
capital markets at any reasonable cost, companies
have watched as the related loss of equity investor
confidence has led to the evaporation of billions of
dollars of shareholder value (over and above the
losses stemming from the operating problems themselves). A key question, therefore, is how much backup liquidity must be in place to avoid a funding
shortfall under these circumstances. While we typically run DBLSM first under normal volatility assumptions, a major benefit of DBLSM is its ability to estimate
the expected cost of alternative liability structures that
can provide the liquidity insurance necessary to
sustain the firm through periods of stress.
In short, DBLSM designs a company’s capital
structure to maximize shareholder value under
conditions of normal, ongoing volatility, but also
models the cost of a liquidity insurance policy
against the possibility of highly improbable events
capable of shaking creditors’ confidence in the firm.
We generally find that the additional cost of such
insurance is fairly modest in relation to “normal”
capital costs, and quite small compared to the total
market capitalization of the firm.
In the pages that follow, we start by reviewing the
benefits and costs of debt as modeled in DBLSM. Most
of the costs derive from market imperfections, such as
the prohibitive costs of issuing equity in a downturn,
or bond credit spreads in excess of expected default
losses. Following this discussion of the model’s
inputs, we then turn to the output of the model—that
is, the primary “decision” variables, first under “normal” volatility conditions and then when taking
account of the additional liquidity requirements just
discussed. The Appendix furnishes additional detail
about the workings of the DBLSM model.
Tax shields. Finance theorists have long recognized that the reduction in the corporation’s tax
liability due to the deductibility of interest expense
is the most important financial benefit of debt in the
capital structure decision process.5 To model the tax
shield of debt, we compare the tax liability incurred
with debt to the liability incurred if the company had
no debt. Of course, interest expense can shield
income only to the extent that the company has
income to be sheltered. Loss carryforwards, the
Alternative Minimum Tax, and accelerated tax depreciation all can reduce the value of the interest tax
shield. In some cases it is also necessary to factor in
5. See Franco Modigliani and Merton Miller, “Corporate Income Taxes and the
Cost of Capital: A Correction,” American Economic Review, Vol. 53, pp. 433-443
(1963); Merton Miller, “Debt and Taxes,” Journal of Finance, Vol. 32, pp. 261-276
(1977); Harry DeAngelo and Ronald Masulis, “Optimal Capital Structure under
Corporate Taxation,” Journal of Financial Economics, Vol. 8, pp. 5-29 (March
1980); and Michael Bradley, Gregg Jarrell, and Han Kim, “On the Existence of an
Optimal Capital Structure,” Journal of Finance (Vol. 39 No. 3), pp. 857-878 (July
1984). See John Graham, “Estimating the Tax Benefits of Debt,” Journal of Applied
Corporate Finance Vol. 14 No. 1 (Spring 2001) pp. 42-54, for a detailed discussion
on the ways in which real world constraints impact the value of the tax shield on debt.
The value of a levered firm is equal to the sum
of the value of an unlevered firm plus the net benefit
of debt. In the DBLSM framework, the focus is on
the valuation impact of the incremental cash flows
deriving from debt and its structure, and thus we do
not need to know the value of either the levered
firm or the unlevered firm to value the impact of the
level and the structure of any debt financing. In fact,
we can avoid the estimation challenges that would
otherwise need to be addressed (including determination of the appropriate market risk premium and
company beta, if a CAPM framework is used) to
derive the correct discount rate for valuing the
company’s operating or equity cash flows. And
although the right discount rate to apply to the debtrelated incremental flows is not precisely certain,
the range of potential error is much smaller than any
estimate of the equity discount rate. In DBLSM, we
discount the cash flows related to debt and its
structure at LIBOR plus the company’s five-year
credit spread as they evolve in our simulations.
While the use of the five-year credit spread versus
other maturity credit spreads is a matter for debate,
it has no material impact on the relative capital
structure valuations that emerge from our model.
What is important is the incremental present value
of cash flows as we change the capital structure.
Benefits of Debt
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SPRING 2002
the tax loss generated by the exercise of employee
stock options, even though this loss is not recognized for financial accounting purposes. Prior to
2001, there were a number of high-tech companies
whose entire taxable income was offset with such tax
losses despite having no net debt.
While debt is tax advantaged at the corporate
level, the relative advantage of debt over equity is
typically reduced once both corporate and investor
taxes are considered. The differential tax rates on
interest income, dividend income, and capital gains
that are specified in each country’s tax code are key
drivers of the net tax benefit of debt. For example,
with the capital gains rate typically lower than the
rate on dividend or interest income, the higher the
proportion of earnings retained rather than paid out
as dividends, the lower is the net benefit of debt. This
is true for classic tax systems where interest expense
is tax-deductible but dividends are not.6 However,
many countries (including the United Kingdom,
France, Germany, Australia, Singapore, and New
Zealand) have imputation systems that effectively
eliminate some or all of the double taxation of
dividends, further reducing or even completing negating the tax advantage of debt financing. In addition
to the tax system’s structure, the other main factor
driving the effectiveness of the tax shield is the tax
profile of the investor base, including the percentage
of nontaxable equityholders and bondholders.
As an example, consider the Dutch tax system.
Until 2001, the generally zero capital gains rate
resulted in little or no advantage to debt versus
equity for typical dividend payout ratios. But new tax
laws that took effect in 2001 provide that investors
are now taxed on the value of their investments
rather than on their investment income—essentially,
a wealth tax. This makes the form of distribution
(whether interest, dividends, or capital gains) irrelevant to investors, and the interest deduction at the
corporate level once again advantageous, increasing
the attractiveness of debt to Dutch companies.
Temporary use of debt to finance capital expenditures or dividends. Debt cuts both ways with
respect to funding capital expenditures (“Capex”)
and dividends: too much debt on a permanent basis
is dangerous, but the flexibility to fund expenditures
temporarily using more debt can be beneficial. That
is, when companies cannot fully fund value-adding
capital projects and (in some cases) maintain the
common stock dividend, shareholder value can be
lost. If we assume that the cost of issuing new equity
is high, it may be advantageous for the company to
increase debt temporarily to fund the shortfall and
avoid the opportunity cost of not making the investment (or maintaining the dividend).
To illustrate this point, let’s consider a company
for which a mid-BBB rating7 represents the optimal
balance between the present value of any tax shields
and the expected distress costs of debt. If there is some
possibility that Capex cannot be fully funded out of
volatile operating cash flow, DBLSM may indicate an
optimal target rating of BBB+ with a fallback of BBB-.
This means that the extra debt capacity (more than
what would otherwise be considered optimal) that is
built up in good years (consistent with a BBB+ rating)
is expected to be drawn upon in bad years (to the
point where the rating is allowed to fall to BBB-). The
willingness to tolerate this fallback level is based in
large part on the probability that the firm will generate
sufficient cash flow to repay the temporary debt
quickly enough to avoid the higher costs of servicing
debt with lower ratings. In general, the more volatile
are the company’s operating cash flows, the higher
the target rating must be to preserve the debt capacity
necessary to finance Capex. At the same time, though,
the higher is the rate of mean reversion in operating
cash flows, the lower is the fallback rating that can be
tolerated because of the higher probability that the
temporary debt will be rapidly repaid.
In our analysis of shortfalls of Capex or dividends that cannot be covered out of operating cash
flow, we assume that the company will always
choose to issue incremental debt rather than new
equity. Of course, companies can issue equity when
their operating cash flows are down, but typically
only at a price that represents a sharp discount to a
likely already depressed stock. According to efficient
markets theory, companies should generally be able
to issue equity at the current fair value without
affecting the traded value of the company. In reality,
6. In his classic 1977 paper (cited earlier), Merton Miller shows
that the value of the tax shield per dollar of debt can be calculated as:
G =1 - [(1 - t c )(1 - t e )/(1 - t d )], where G is the relative gain on debt
vs. equity, t c is the effective corporate tax rate, and t e and t d are the
effective tax rates on equity distributions and interest, respectively.
Practitioners commonly assume that the effective tax rate faced by both
equity- and debtholders is equal, in which case the value of the tax shield
per dollar of debt reduces to t c.
7. While our rating notation uses S&P designations, our discussion is
understood to represent the Moody’s-equivalent rating as well.
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Too much debt on a permanent basis will cause heavy debt service obligations that
raise the probability of missing Capex and dividends.
Similarly, we assign a cost to the first time that
a company must cut its dividend. Academic research
has clearly shown the negative impact of dividend
cuts on share prices, with typical findings ranging
from a 1% price decline for dividend reductions to a
7% decline for complete omissions.11 For companies
with a long track record of stable or increasing
dividends, we typically assume a penalty towards the
upper end of this range and sometimes even higher
(what would happen, for example, if GE cut its
dividend?). But for companies with a limited dividend
track record or volatile dividend payments, we typically assume a penalty close to or equal to zero.
however, information is limited and investors are
suspicious about both managers’ view of the
company’s prospects and the intended use of the
proceeds from an equity offering.8 Thus, a secondary
issuance of equity to cover shortfalls generally meets
with an adverse market reaction for several reasons:
If the company is short of operating cash to fund
normal Capex or to maintain the dividend, it is likely
that the stock price is already depressed and the
company’s debt spreads have widened. Some portion
of the equity issued in this situation will go to shore
up the creditors’ position, transferring value from the
shareholders to the creditors.9 More importantly,
while the market is likely to accept the story that highflying growth companies need extra equity to expand,
it tends to be more skeptical of claims by managers of
depressed companies that they will prudently apply
the new money to rebuild the business. In other
words, agency and information costs are at a peak
when the company’s financials are weak.
Except for companies with prospects of rapid
growth, issuance of equity may imply that management feels the stock is overvalued, or that the
company’s relationship with potential lenders has
deteriorated.10 In either case, an equity issue will not
be warmly received by the market.
How does our model quantify the expected cost
of missed investments or dividends? When cash flow
is inadequate to fund Capex requirements—even
after using the incremental debt capacity provided
by the fallback rating—we assume a shareholder
value loss equal to a percentage penalty factor times
the unfunded Capex. For example, a typical penalty
factor for companies trading at P/E multiples in the
upper teens might be 25%, meaning that for every
$100 of unfunded Capex, shareholders incur a $25
cost at the time of the Capex shortfall. For growth
companies trading at much higher P/E ratios, the
penalty would typically be higher. For example, a
pharmaceutical company that has finally won FDA
approval on a blockbuster drug faces enormous
opportunity costs if it cannot fund the Capex necessary to produce and distribute the drug.
Costs of Debt
Crowding out of Capex and dividends. We
have already discussed the dual role of debt with
respect to Capex and dividend funding. Too much
debt on a permanent basis will cause heavy debt
service obligations that raise the probability of
missing Capex and dividends. These in turn lead to
the shareholder value penalties just described.
Interest costs in excess of the floating borrowing rate of an AAA-rated company.We treat interest
costs in excess of the floating borrowing rate of an
AAA-rated company as a cost to shareholders. AAA
floating borrowing rates are used as our base, or
“riskless,” rate because U.S. Treasury or other direct
government borrowing rates, which are generally
lower than AAA corporate rates, have special liquidity
and regulatory benefits that go beyond credit risk. The
shareholder cost derives both from the credit spread
incurred on debt and from fixing interest rates when
subsequent floating rates turn out to be lower.
The argument that the credit spread is a cost is
somewhat controversial.12 While corporate finance
managers instinctively treat the credit spread on debt
as a cost, some academics argue that the spread fairly
compensates investors for their risk of loss from
bankruptcy net of expected recoveries, and thus does
not represent a true cost to shareholders. However,
we believe that for investment-grade companies, the
8. See Michael Jensen, “Agency Costs of Free Cash Flow, Corporate Finance, and
Takeovers,” American Economic Review, Vol. 76 No. 2, pp. 323-329 (May 1986).
9. See Stewart Myers, “Determinants of Corporate Borrowing,” Journal of
Financial Economics, Vol. 5 No. 2, pp. 147-175 (Nov. 1977).
10. See Stewart Myers and Nicholas Majluf, “Corporate Financing and
Investment Decisions When Firms Have Information that Investors Do Not Have,”
Journal of Financial Economics, Vol. 13 No. 2, pp. 187-221 (June 1984).
11. For a review of dividend policy signaling literature, see Chapter 7 of
Dividend Policy—Its Impact on Firm Value, by Ronald Lease, Kose John, Avner
Kalay, Uri Loewenstein, and Oded Sarig (Harvard Business School Press, 2000).
12. Surprisingly, there seems to be little academic research directly on the
subject of the credit spread cost to shareholders.
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VOLUME 15 NUMBER 1
SPRING 2002
credit spread has generally been much greater than
the level implied by actual bankruptcy losses net of
recoveries.13 This result14 could have much to do with
the fact that, in recent years, there have been several
notable cases in which a major company has experienced rapid and dramatic credit deterioration when it
came to light that the company was taking on much
more risk or incurring more extensive losses than
had previously been publicized or disclosed in its
financial statements. Having been blindsided in the
past by such cases, investors have little way of knowing
which apparently strong companies are misleading
them. Hence, investors must charge all companies a
risk premium to cover the expected cost of these losses.
This credit premium “surcharge” should be
considered a cost to the shareholders of those
companies that are not misleading their creditors—
a category of costs that economists call “adverse
selection.” Auto insurance provides a good example
of such costs. Insurance companies have limited
ability to identify bad drivers prior to the occurrence
of an accident, and many jurisdictions prohibit insurance companies from charging differential premiums
based upon certain types of statistical evidence.
Therefore, the extra insurance premium that good
drivers pay to cover the losses incurred by bad drivers
should be considered a cost to the good drivers.
Another source of the excess credit spread is a
limit on the supply of institutional credit. As a
company’s credit standing deteriorates, fewer institutions are ready or even permitted to invest in
weaker credits. In an efficient market, all investors
would be able to invest in companies of any credit
quality but would adjust their required return to
reflect the risk of the individual company. While we
agree that this is largely true of major equity markets,
the supply of fixed-income funding is vastly greater
for strong companies than for weak companies. A
well-known example is the commercial paper market, where the supply of credit to A-2/P-2 issuers is
only about 5%-10% of the supply to A-1/P-1 issuers,
largely because money market funds must, by regulation, restrict most of their investments to A-1/P-1 or
better. When an A-1/P-1 issuer is downgraded, it
must typically pay a very high premium to crowd out
other A-2/P-2 issuers so as to attract a sufficiently
large portion of the limited A-2/P-2 market. Similarly,
other major fixed-income investors such as insurance companies, pensions, and bond funds face
restrictions on the quantity of lower-rated term debt
they can hold. As the issuance of lower-rated paper
increases due to downgrades, the credit spreads on
all debt at the lower end of the market are bid up.
Based on these considerations of adverse selection and institutional supply constraints, we model
the entire credit spread above the AAA borrowing
rate as a cost to shareholders (while conceding that
at least some portion of the spread is there to cover
net default risk). We justify using the entire spread
with the argument that most investment-grade firms
are evaluated as ongoing concerns by their shareholders. In other words, shareholders generally want
management to maximize returns contingent upon
the firm surviving catastrophic events, and the cost
of protecting against such an improbable risk is
simply a cost of business. Viewed from another
perspective, few analysts are likely to add back any
of the credit spread incurred on debt to arrive at a
“truer” economic earnings profile for a company.
The Business Effects of Credit Downgrades.
When a company’s credit deteriorates, particularly
below investment grade, the company finds it increasingly difficult to negotiate favorable payment terms
with its suppliers. As payments are accelerated, the
payable account declines and must be replaced by
interest-bearing debt. Interest costs on incremental
working capital are the indirect result of lower credit
ratings, and DBLSM explicitly models the cost of this
additional interest, net of any tax shield, by increasing
working capital requirements as ratings are lowered.
Besides affecting supplier credit availability,
low ratings also clearly affect relationships with
customers and employees. For example, manufacturers of cars or airplanes may lose business to more
creditworthy competitors if customers feel the company will not be around to service its product. Natural
13. Using Moody’s data for annual and two-year default probabilities
for cohorts from 1997 through 2000 and simplified modeling assumptions,
we estimated what credit spread would be required to cover the risk of
default (net of recoveries) as a function of credit rating. This hypothetical
spread was then compared to the observed spread. We found that, down
to mid-BBB ratings, the actual spread is significantly greater than the
“default only-required” spread, with the default component accounting for
somewhere between only 0-20% of the total observed spread. For a
comprehensive analysis of this question using a calibration approach on a
variety of structural models for credit risk, see Jing-zhi Huang (Pennsylvania State University) and Ming Huang (Stanford University), “How Much of
the Corporate-Treasury Yield Spread is Due to Credit Risk?: A New
Calibration Approach,” working paper (April 2002).
14. One could argue that the excess credit spread may be at least partly
attributable to systematic risk, which could imply that portion of the excess spread
so attributed is not a cost to shareholders.
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JOURNAL OF APPLIED CORPORATE FINANCE
bankruptcy event. The Enron case provides a good
illustration. As counterparties and employees defected, immense intangible value, particularly related to the energy trading business, was lost. This
is the present value of the expected future cash flows
that would have materialized absent the bankruptcy.
resource exploration and production companies,
despite producing a commodity product, may lose
access to reserves if a low credit rating prevents
them from entering into long-term contracts. Companies whose principal asset is human capital may
lose valued employees who depart for more secure
firms.
To model this loss of business as a function of
credit rating, DBLSM assumes that an increasing
percent of EBITDA is lost as ratings decline, particularly if they drop below investment grade. The loss
factors are estimated based on industry analysis and
discussions with the company. DBLSM then charges
the present value of lost EBITDA in each simulation
month to shareholder value.
Bankruptcy Costs. The increased working capital requirements and lost EBITDA are financial
distress costs that grow as a firm’s credit quality
deteriorates. Actual bankruptcy costs (which include
the costs of reorganizing a company whether inside
or outside Chapter 11) are generally negligible in our
modeling unless the descent to bankruptcy from
investment grade is very rapid.
DBLSM incorporates a relatively simplistic lagged
model of the company’s share price15 and assumes
that all of the equity value is wiped out upon
bankruptcy. If the company has already slid to deep
non-investment-grade ratings prior to bankruptcy,
the share price model would typically indicate little
remaining shareholder value and thus minimal
bankruptcy costs. Material bankruptcy costs arise
only when the company has a “brittle” credit
standing that is based largely on cash flows and not
on tangible assets that other creditors would lend
against. In the event that cash flows are suddenly
inadequate to service debt and the quantity of debt
already exceeds the limited secured borrowing
power of the assets, the company could experience
a rapid meltdown, resulting in a dramatic loss in
shareholder value.
This is a separate effect from the loss of business
discussed above. Whereas the latter captures losses
in each simulated period due to lower ratings, the
bankruptcy cost captures (by assuming the stock
price falls to zero) the present value of all lost cash
flows that would have occurred subsequent to the
PRIMARY DECISION VARIABLES AND
TYPICAL FINDINGS
Now that we have summarized the key input
components of DBSLM, let’s turn to the output
recommendations for capital structure that the model
is likely to generate. The decision variables that can
be changed by management to maximize shareholder value include not only the leverage ratio but
both the target and fallback credit ratings, the
optimal level of cash reserves, dividend and share
repurchase policies, as well as several more detailed
aspects of debt structure such as maturity, currency,
and the mix of fixed vs. floating.
We start our discussion with the optimal target
and fallback ratings that determine the level of debt,
and then consider the three aspects of debt structure
just cited. The questions of optimal dividend policy
and cash reserve targets are discussed last.
Rating Targets
In applying our model to non-financial companies across many industries, we have found optimal
target ratings that run the gamut from mid-BBB to
AAA levels. While specific conclusions depend on
many individual factors, including the firm’s tax
position, the principal determinants in a broad
sense are the size of Capex and dividends relative
to EBITDA, the volatility of EBITDA, and the
expected costs associated with falling to lower and
especially non-investment-grade ratings. All other
factors equal, higher Capex and dividends and
higher EBITDA volatility dictate higher target ratings, and thus lower leverage ratios, while companies with lower Capex and dividends and lower
EBITDA volatility can support more debt (lower
target ratings).16 But there are many intermediate
cases with high Capex and dividends but low
15. The stock valuation model is Pt = aPt-1 + b (P/E) EPSt-1 where Pt is the
price in month t, EPSt-1 is the EPS in month t-1, (P/E) is an assumed long term
P/E ratio (with volatility applied around an expected value), and a and b are
coefficients. We adjust a and b to produce results reasonably similar to historical
patterns of annual stock price volatility.
16. Leverage ratios span a range for a given credit rating, and this is reflected
in our ratings sub-model as described in Step 7 of the Appendix.
37
VOLUME 15 NUMBER 1
SPRING 2002
FIGURE 1
EVOLUTION OF
ACTUAL LIBOR VS. LIBOR
ORIGINALLY PREDICTED
BY FORWARD CURVES1
12%
Actual LIBOR
Forward LIBOR
Forward Curve at April 1993
10%
LIBOR
8%
6%
4%
Jan/12
Jan/11
Jan/09
Jan/10
Jan/08
Jan/07
Jan/06
Jan/05
Jan/04
Jan/03
Jan/01
Jan/02
Jan/00
Jan/99
Jan/98
Jan/96
Jan/97
Jan/95
Jan/93
Jan/94
Jan/92
Jan/91
0%
Example: In April 1993, the forward curve “predicted”
that LIBOR in January 1997 would be 6.68%, but the
actual LIBOR in January 1997 was only 5.69%
Jan/89
Jan/90
2%
Source: Deutsche Bank Debt Capital Markets and Bloomberg historical data.
1. As can be seen in the figure, during the periods in the last 13 years (for which data were readily available) when LIBOR
has significantly declined, the decrease has been far sharper than the forward curves would have predicted. But in the periods
when LIBOR increased, although forward rates also “underpredicted” the increase, the underprediction in this case was smaller
and more short-lived than the overprediction in the other direction, making forward LIBOR rates too high on average.
Debt Characteristics
EBITDA volatility, or low Capex and dividends but
high EBITDA volatility.
In practice, DBLSM derives a majority of optimal target ratings to be centered in the high-BBB to
high-A range. Based on client feedback, we believe
these findings represent stronger rating and hence
lower leverage recommendations than results generally produced by other, frequently weighted average
cost of capital-based, analyses.
For the fallback rating, we find that a gap of at
least one rating notch between the target and
fallback rating generally adds material value, as
compared to an inflexible capital structure that
allows no deviation from the target ratio. For example, if the target rating is A, a “two-notch” fallback
to BBB+ may be optimal. Generally, the greater the
volatility of EBITDA, the lower is the fallback rating.
Nevertheless, the model typically tries to leave
breathing room between the fallback rating and noninvestment-grade territory to avoid the costs associated with higher credit spreads, lost business, and
higher working capital needs that occur at the lower,
particularly non-investment-grade, ratings.
Fixed versus Floating Mix. The optimal mix of
fixed- and floating-rate debt is frequently of great
interest to CFOs and corporate treasurers. Our
interest rate simulations are constructed so that, on
average, the future evolution of LIBOR is lower than
that implied by forward LIBOR rates.17 (For historical
evidence in support of this approach, see Figure 1.)
We argue that borrowing at floating rates is
value-neutral, while borrowing at fixed rates exposes
the company to potential economic losses or gains (if
subsequent floating rates go below or above the fixed
rate).18 One way to see this is that floating debt, prior
to credit spread considerations, maintains par value
while fixed rate debt does not. When a company
borrows fixed and rates decline, there is an unquestionable shift in value from shareholders to creditors.
Our basic philosophy is that companies should
not incur the risk premium associated with fixed-rate
financing unless such financing is the most costeffective means of reducing other substantial risks
facing the firm. One such possible risk is a spike in
18. Once again, the focus of our model is non-financial companies. Other
companies with significant financial assets would incur risks of rating downgrades
and financial distress should the gap between asset and liability durations become
excessive.
17. Our approach of assuming that the yield curve embeds a risk premium is
consistent with the liquidity-preference theory of the term structure of rates.
38
JOURNAL OF APPLIED CORPORATE FINANCE
For the fallback rating, we find that a gap of at least one rating notch between the
target and fallback rating generally adds material value, as compared to an inflexible
capital structure that allows no deviation from the target ratio.
2.0
Year-over-year change in EPS
FIGURE 2
CHEMICAL COMPANY:
ANNUAL CHANGE IN
DILUTED EPS (IN $)
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
Actual Change
Change with 100% Instead of 30% Assumed Floating
-2.5
-3.0
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
Source: Company data and Deutsche Bank analysis.
in EPS would have been with 100% floating debt
compared to the actual level, which often tends to be
in the 20% to 30% range. Figure 2 outlines such an
analysis for a large chemical company for EPS changes
over the 1983-2001 period. As can be seen in the figure,
going from an assumed 30% floating to a hypothetical
100% floating would have slightly reduced the annual
change in EPS in most years. This reflects the positive
correlation between earnings and LIBOR, such that
when earnings rise, the increase is slightly offset by
higher interest costs, and when earnings fall, the
decrease is slightly muted by lower interest costs. The
standard deviation of the actual annual EPS changes
over the period is $1.055, but this would have dropped
to $1.019 had debt been 100% floating.
We have found in the fixed versus floating
analysis that a floating percent at or near 100% is often
optimal for many investment-grade industrial firms.
The fact that many investment-grade industrials
target only 20-30% floating, when they would have
greater shareholder value at higher percentages,
may perhaps be symptomatic of a mistaken focus on
managing interest rate volatility in isolation rather
than on the expected cost of debt and overall cash
flow volatility.
On the other hand, we also see situations where
very low levels of floating-rate debt (high levels of
fixed-rate debt) is optimal. This tends to occur when
interest coverage is already quite weak and escalating rates can put the company at significant risk of
a further downgrade. Also, high levels of floatingrate debt can materially increase cash flow and EPS
volatility when a company’s EBITDA is very stable
or, worse, negatively correlated with interest rates.
interest rates that hurts coverage ratios enough to
jeopardize the firm’s credit rating. Lower ratings could
in turn cause a real loss in shareholder value due to
the higher credit spreads, working capital requirements, and loss-of-business effects already discussed.
A second risk that can be managed with fixedrate debt is more accounting-oriented—namely, the
possibility that greater use of floating-rate debt may
increase the volatility of reported earnings and EPS.
While many analysts believe that companies with
higher EPS volatility trade at lower multiples, we do
not attempt to assign a price tag to such volatility. In
theory, shareholders should not care about interest
expense or even EPS volatility so long as the actual
risks of rating downgrades or financial distress do
not increase. In fact, we find that for most moderate
to strong investment-grade borrowers, high levels of
floating debt do not materially increase either the
probability of rating downgrades or EPS volatility. The
typical volatility in interest rates, when applied to the
relatively modest quantity of debt in an investmentgrade company, tends to be “washed out” by the basic
operating cash flow volatility of the company. Also
important in mitigating volatility is the fact that in
many industries, including natural resource exploration and production, paper, chemicals, and other
industrial product companies, there is a positive
correlation between the change in cash flow and
changes in LIBOR. And to the extent that such
companies’ operating cash flows move up and down
with changes in interest rates, the use of floating-rate
debt actually reduces earnings volatility.
To illustrate this point, we sometimes “re-run”
the history of a company to estimate what the change
39
VOLUME 15 NUMBER 1
SPRING 2002
An analogy with personal finance may be
helpful in showing why the optimal levels of floating
rate debt is frequently at one or the other extreme.
Many oil and gas companies send a contract to their
customers once a year allowing them to lock in the
cost of fuel for the coming year. The offered contract
prices often seem high compared to the expected spot
price of the fuel. But customers who live from
paycheck to paycheck cannot afford to take the risk
of a large potential increase in their winter heating bill,
and often sign the contract to lock in this price. More
affluent customers, however, have a greater buffer in
their finances and are not very likely to sign the
contract. But it would be unusual for any customer to
conclude that hedging only, say, half of the future
purchases is best.
Maturity Considerations. DBLSM analyzes the
trade-off between the higher credit spreads but
lower rollover risk associated with issuing longerterm debt and the lower average cost but higher
rollover risk of shorter-term debt. A few years ago,
we would typically have observed a more or less
break-even situation in which the higher credit
spread on longer-term debt was largely offset by the
expected cost of rolling over short-term debt at
potentially less favorable rates. That is, shareholder
value differences were minor across the new-issue
maturity spectrum. More recently, though, with a
general increase in corporate debt spreads, we find
on average a net cost to longer-term maturities.
Hence, under conditions of “normal” volatility, the
company would be better off on average with
shorter-term debt, even after considering the various
costs of financial distress captured by our model.
Nevertheless, an unusual event that is not
captured under normal volatility (for example, a
sudden legal liability, natural disaster, or unexpected
reporting problem) can result in an abrupt withdrawal
of unsecured credit support from potential lenders and
a sharp increase in outstanding debt trading spreads.
We address shortly how to adjust capital structure to
protect against such “event risk” contingencies.
Currency Mix of Debt. Multinational corporations commonly ask about the optimal currency mix
of their liabilities. In practice, companies rarely borrow in foreign currencies when they cannot make use
of hedge accounting, mainly because it is difficult to
explain the earnings volatility attributable to naked
foreign currency borrowings. Interestingly, government or government-controlled entities seem more
willing to take on foreign currency exposure because
they are not subject to the same scrutiny.
DBLSM captures several effects of foreign currency borrowings:
The lower or higher average cost of financing
compared to the company’s home currency borrowings, depending on the specification of the FX and
interest rate models;
The lower volatility of shareholder value and EPS
to the extent that the interest expense on foreign
currency debt offsets the foreign currency earnings
of foreign subsidiaries;
The greater diversification of funding costs. For
example, it may be less risky to borrow in multiple,
not strongly correlated, currencies than in just one
currency; and
The impact on ratings and hence borrowing costs
of both local and foreign currency debt. For example, if a company has significant foreign currency
debt employed to hedge net investments and the
foreign currency appreciates, the higher book value
of the debt, though offset by translation of the net
investment, will still cause important credit ratios
such as debt/total capital or funds flow from operations/debt to deteriorate.
19. In addition to dividend policy, DBLSM is able to address various shareholder
value aspects of share repurchases. For example, assumptions can be incorporated
regarding positive stock price effects of modest amounts of repurchases, as well as
negative effects for repurchases beyond certain levels where the company would
have to pay a significant premium to buy in the shares. In the interest of brevity, we
have not focused on our repurchase modeling capabilities in the present paper.
Dividend Policy
Although DBLSM is able to incorporate various
types of dividend policies, most take the form of a
minimum payout ratio and a target growth rate in
dividends per share subject to a maximum payout
ratio. DBLSM assumes that a company will not cut its
dividend unless paying the dividend would require
so much debt financing that ratings would fall below
even the fallback credit rating. As discussed earlier,
a shareholder penalty is imposed the first time a
dividend cut is necessary.
The model reflects several implications of dividend policy:
The higher the dividend, the lower are stock
repurchases, since share repurchases are funded out
of any residual cash flow left after all Capex and
dividends are funded.19
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Although liquidity management is often thought of as separate from capital
structure, we believe that it is a mistake to try to separate the two topics.
bered assets. High-tech companies with little in the
way of tangible assets, or airlines that rely heavily on
secured financing, would fit this category.
In these circumstances, the benefit provided by
cash reserves to help avoid the penalties associated
with dividend or Capex shortfalls—or, in the extreme, to help cover interest and tax obligations—
can outweigh the cost.
The higher the dividend, the greater is the risk of
a dividend cut in the future, triggering the dividend
cut penalty.
The higher the dividend, the greater the chance for
crowding out Capex in a given period and incurring
the associated penalty. As a secondary effect, future
Capex can also be squeezed out if the firm has
already reached its fallback rating level of debt to
meet current dividend requirements.
To the extent that higher dividend payouts have
the effect of increasing debt outstanding, credit
ratings will be pushed down, with implications for
higher costs of debt, working capital needs, and lost
business.
OPTIMAL CAPITAL STRUCTURE ADJUSTED
FOR LIQUIDITY REQUIREMENTS
Up to this point, we have discussed optimal
capital structure assuming normal, ongoing behavior
of the simulated variables. We now consider how to
adjust capital structure to provide sufficient contingent liquidity in light of event risk. Although liquidity
management is often thought of as separate from
capital structure, we believe that it is a mistake to try
to separate the two topics. Providing for liquidity
insurance increases the cost of capital and affects the
structure of liabilities. In formulating their capital and
liability strategies, financial managers should attempt
to weigh the costs of alternative approaches of
liquidity insurance with the level of protection they
provide, much as a driver might compare auto
insurance policies. DBLSM can quantify the costs of
these different solutions—for example, the relative
costs of various debt maturity profiles, or of different
levels of cash (and near-cash) liquidity reserves.
Under normal volatility, DBLSM shows that
longer-term debt, even after taking account of its
lower rollover risk, is more costly than short-term
debt. Why should companies, particularly highrated companies, not then finance themselves entirely with commercial paper? The answer is that
virtually any company is exposed to event risk and
must construct an alternative liquidity plan that
contemplates a complete withdrawal of unsecured,
uncommitted credit for a sustained period of time.
Such a plan should not include the sale of core assets
because significant shareholder value would likely be
sacrificed in a sale under distressed conditions. We
use a time frame of two years to give the company
enough time to organize its recovery. Our approach
identifies likely cash inflows and outflows and then
finds the liability structure that provides the needed
“breathing room” at the lowest expected cost.
The cost of providing adequate back-up liquidity can be viewed by the company as a kind of
insurance policy. The event risk contingency has a
Cash Reserves
Some industries such as autos, airlines, and
technology maintain sizeable cash liquidity reserves
which can be drawn upon in situations when
operating cash flows are inadequate. In particular,
DBLSM defines the “free” cash reserve as a pool
available to pay interest expense and taxes if necessary, or to fund dividends and Capex in the event
operating cash flows fall short and the firm is already
at its fallback rating debt level. Free cash reserves do
not include any cash that may be “trapped” within
low-tax foreign subsidiaries as a result of the tax
penalty that the company would incur to repatriate
earnings back to its home country.
DBLSM measures the cost of maintaining a cash
reserve as the negative “carry” due to the shortfall
between the short-term interest rate earned and the
cost of the implicit term debt financing necessary to
maintain the reserve, plus the reduction in the
interest expense tax shield resulting from the interest
earned. Managers sometimes overlook the fact that
cash reserves produce a negative tax shield interest,
that is, income is subject to a corporate layer of
taxation that would be avoided if the shareholders
held the cash directly.
Notwithstanding these negatives, DBLSM shows
that the cost of a cash liquidity reserve can be justified
in the following situations:
The company’s operating cash flows are highly
volatile and debt credit spreads escalate rapidly at
lower ratings;
Working capital requirements increase dramatically when business conditions deteriorate;
Unsecured financing capacity is constrained, particularly in hard times, by a lack of hard, unencum41
VOLUME 15 NUMBER 1
SPRING 2002
low probability of occurring but a very high cost if
uninsured. The cost, in fact, could be the complete
collapse of the company. If, however, back-up liquidity is strong enough when a crisis hits, lenders see that
the company has the resources to weather the crisis.
When back-up liquidity is not adequate, potential
lenders lose confidence and withdraw their support
because they cannot see how the company will
survive.
Like many other aspects of capital structure, the
need for back-up liquidity is magnified by market
imperfections such as asymmetric information, which
is a major factor when an event risk situation develops.
Potential lenders may not know all the relevant factors
and are suspicious that management is hiding the real
story in order to secure cheap financing. Audited
financial statements are generally not available until
well after the event, and are now viewed with
particular suspicion in light of recent SEC investigations of financial reporting irregularities. Because
potential lenders do not have full information, they
will withhold additional support unless there is
tangible back-up liquidity in place that would allow
the company to survive the situation.
To bolster back-up liquidity, a company can:
Extend debt maturities so that debt does not come
due within the target recovery period;
Establish asset-backed securities (ABS) programs,
test them, and then earmark assets that could be
utilized in these programs in a liquidity crunch. This
is the mainstay of the auto companies’ back-up
liquidity. Both GMAC and FMCC made heavy use of
ABS markets in the recent downturn to pay down
commercial paper when they lost their A-1/P-1 commercial paper ratings. Using these programs does not
seem to sound any alarm bells in the market;
Create a liquidity reserve composed of liquid cash
or near-cash investments. However, in industries that
customarily maintain cash reserves, the act of drawing
them down when times are clearly troubled sends a
signal that the company is encountering difficulties; or
Establish committed bank facilities and then draw
upon them when required. But drawing on bank lines
as an investment-grade credit sends very negative
signals to both the fixed-income and equity markets.
Given the negative signal of actually drawing
upon committed bank lines, why might it still be
desirable to use these lines as back-up instead of the
other alternatives? The cost of issuing commercial
paper backstopped with bank facilities can still be
significantly lower—particularly for companies that
bear an A-1/P-1 commercial paper rating or higher.
Moreover, if the company is downgraded to noninvestment grade, drawing upon the bank lines
sends only a modestly negative signal, since the lines
are designed to replace commercial paper when the
company can no longer issue it in the market. Finally,
even if the company remains investment grade, the
lines give it significant negotiating power with its
bank group.
But, having said this, it is becoming increasingly
clear that 364-day bank lines are not providing
adequate backstop liquidity.20 The shorter-term lines
have been popular in the past because banks do not
have to allocate capital to them and charge only
minimal commitment fees. However, these shorter
lines do not provide enough time for a company to
fix a liquidity problem and are perceived by credit
analysts to be inadequate. Shorter lines can be
justified only to support truly short-dated funding
needs (such as a retail inventory build-up in the fall
season) or to backstop commercial paper that could
be replaced with ABS.21
Just as important as securing sources of liquidity is the need to accurately identify the possible uses
of cash in a crunch, such as debt repayments and
operating cash. Additional flows would include
likely cash restructuring costs, product discounting
to liquidate inventory, and adverse shifts in working
capital as production is scaled back.
In the liquidity planning process, it is also
important to avoid “liquidity traps” that have gotten
companies in trouble before. For example, it is
tempting to believe that meeting rating agency
requirements for issuance of commercial paper is
sufficient for liquidity purposes and that if the
agencies can be talked into requiring less back-up,
the company is better off. This may be shortsighted.
Similarly, in an event-risk situation, it is also important to keep in mind that serial put bonds and
20. See Pamela Stumpp and Daniel Gates, “Moody’s Approach to Assessing
the Adequacy of ‘Liquidity Risk Insurance,’” Moody’s Investors Service —Rating
Methodology (January 2000), for a discussion of Moody’s growing concern over the
availability of traditional bank commercial paper back-up facilities. Possible
solutions to this problem are the new “contingent capital” financing products—in
effect, sub debt and equity lines of credit—discussed by Chris Culp in this issue.
21. Note that 364-day lines with term loan options can provide true term
liquidity.
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CASE STUDY: OUTPUT RECOMMENDATIONS FOR COMPANY X
factors that argued strongly for having a significant portion
of the acquisition debt at ten-year or longer maturities.
Target Rating: DBLSM indicated that Company X
should manage toward a permanent target rating of A-.
With the fallback rating also set at A-, this rating
combination added about $600 million of shareholder
value versus keeping the target (and fallback) rating at
the initial BBB level, where there is a substantially
higher net interest cost (that is, the present value of the
spread over AAA rates less the tax shield benefit). It was
projected to take about five years on average before X
substantially attained the A- level through debt paydown
out of operating cash flows.
Fallback Rating: With the target rating set at A-,
allowing the fallback rating to drop to BBB- (three
rating notches below the target) added roughly $200
million of additional value, due primarily to avoiding
the penalties for missed Capex or dividend cuts that
would otherwise arise due to the highly volatile nature
of the modeled EBITDA. The additional debt capacity
at BBB- allowed debt to expand temporarily to cover
funding needs in periods of cash flow shortfall.
Fixed versus Floating Mix: The model indicated
that Company X should aim for 100% floating rate debt
in the long term, but should move toward this target
gradually over the next several years while the rating
profile strengthened to A- from its current BBB range.
When compared to the initial case of 10% floating, we
estimated that the ultimate 100% floating would add
about $750 million of shareholder value. This was
primarily due to reduced expected net interest costs,
which in turn improved expected EPS and credit ratios,
and actually reduced risk measures such as the probability of Capex shortfalls or dividend cut. The reduced
risk was the result not only of the reduced debt service
burden with more floating, but also the observed 30%
correlation between changes in LIBOR and changes in
EBITDA/operating assets.
Maturity Structure of New Issue Term Debt: For
new term debt issues in the future, alternative maturity
configurations produced only minor shareholder value
differences. Therefore we recommended that Company
X should target its new issues across a spectrum of
maturities to meet investor demand, strengthen liquidity,
and avoid unnecessary refunding concentrations.
Though the unique characteristics of each company make it inappropriate to apply the results of one
study to other firms, a sample of the main recommendations resulting from a recent DBLSM client study for
Company “X” may be helpful in illustrating the kind of
output DBLSM produces. Key inputs for the analysis
were as follows. X is a large U.S. industrial (with a
market cap of roughly $15 billion at the time of this
study) that is a leader in its highly cyclical, commoditytype industry.* It was modeled with a long-term mean
EBITDA/operating assets of about 16%, and an annual
standard deviation for EBITDA/operating assets equal
to about 1/3 of the long-term mean. (A ratio of 1/3
represents a high EBITDA volatility compared to that of
many other industries we have analyzed, which are
most often in the 1/5 to 1/4 range.) This high EBITDA
volatility risk was only somewhat offset by an annual
rate of mean reversion of about 35%, which is midrange for mean reversion rates. The correlation between EBITDA and LIBOR was estimated at positive
30%, indicating a moderate tendency for operating cash
flows to keep pace with interest rates.
The analysis was performed to include the debt
associated with a then-impending acquisition that
more than doubled previously outstanding debt, and
which put the initial credit rating in the mid-BBB range.
Initial floating rate debt was only about 10% of the total.
Future credit ratings were projected by a model driven
mainly by two ratios: the EBIT/interest coverage and
the funds flow from operations/debt ratios. The projected corporate tax rate was close to 40%, but the debt
was estimated at only about 70% effective in shielding
income after flowing taxation through both the corporate and personal levels. The dividend payout was fixed
at 40%. Among other questions, we explored how to
optimize the acquisition funding, target and fallback
ratings, fixed versus floating mix, and maturity structure
of the debt portfolio.
Principal recommendations:
Acquisition Funding: Though short-maturity funding had a lower expected cost than longer-term strategies
by about $40 million, this difference represented only
about 0.25% of the firm’s total market cap. The modest cost
of term debt was outweighed by a combination of rating
agency, term liquidity insurance, and market receptivity
* Numbers have been broadly rounded where appropriate to disguise the
identity of the firm.
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VOLUME 15 NUMBER 1
SPRING 2002
CONCLUSION
puttable convertible bonds—securities that are not
classified as “short term” on the balance sheet—will
almost certainly be put back to the issuer for cash if
the issuer’s condition markedly deteriorates. If these
securities are not adequately considered in the
design of the firm’s alternative liquidity plans, the
future uncovered puts will add to investor concerns
and magnify the company’s difficulties in obtaining
new loans in an event risk situation.
Another common temptation is to view historically maintained back-up liquidity as no longer
necessary if the company has never had to use them.
The pressure to scale back costly back-up liquidity
is greatest when management is having a hard time
meeting promised earnings targets. Finally, writing
puts on the company’s own stock can create significant short-term cash liabilities at precisely the worst
time—namely, when the stock is sinking. While
writing puts can have significant benefits, their
potential exercise must be considered in liquidity
planning.
We have presented some of the underpinnings
of our approach to capital structure as captured in the
Deutsche Bank Liability Structure Model. We do not
claim that our model can predict the actual capital
structures of companies already in place. Rather, our
basic philosophy is that the process of determining
an optimal capital structure should involve an attempt to identify and quantify all of the important
shareholder value costs and benefits of the capital
structure decision variables associated with the level
and structure of the company’s debt. From the
multiplicity of variables and inputs discussed above,
it is clear that the capital structure optimization
exercise is complex and goes well beyond a simple
target for the ratio of debt to total capital. Finally, it
is critical to adjust capital structure around the
requirement to provide liquidity insurance to ensure
that the company can weather a loss of investor
confidence when it hits difficult times.
ROGER HEINE AND FRED HARBUS
are Managing Director and Director, respectively, of the Liability
Strategies Group of Deutsche Bank Securities Inc.
APPENDIX: MODEL FLOW
The main steps involved in running DBLSM are as
follows:
1. Develop projections for the ratio of EBITDA to
the operating asset base. Specifically, fit a meanreversion time-series model to the ratio of EBITDA to
operating assets, where operating assets equals total
assets less free cash and goodwill, plus capitalized
operating leases. Estimate the ratio’s long-term mean,
rate of mean reversion, and annual volatility of the ratio
using a combination of industry historical data and
company-specific financials. The resulting model is the
basis for the baseline EBITDA projections within DBLSM.
Overlay any special cash flow projections (such as
anticipated acquisitions or divestitures) not captured
by the EBITDA trend line. Identify starting values for
EBITDA and operating assets.
2. Develop assumptions about the “financeability”
of hard assets, targeted cash reserves, and strategic
investments that could provide sources of liquidity in
the event of a debt service shortfall.
3. Based on both company historical data and
available projections, develop assumptions for forward-looking Capex, dividend payout policy, book
and tax depreciation (as well as true economic depreciation), tax rates, tax credits and loss carryforwards,
working capital requirements, share count, and other
key parameters necessary to project net cash flows and
key accounting items, including EPS. Importantly, the
excess of estimated Capex over economic depreciation
drives asset growth in the model, which in turn drives
EBITDA growth after application of the EBITDA/
operating assets ratio.
4. Estimate how EBITDA and working capital
requirements vary as a function of credit rating.
5. Identify and load into DBLSM the company’s
current debt portfolio and affiliated swaps.
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JOURNAL OF APPLIED CORPORATE FINANCE
APPENDIX (continued)
6. At the firm’s actual current rating, estimate
the cost of term debt as a function of maturity from
one to 30 years, expressed as a spread to the corresponding LIBOR swap rate. Then, for both ten-year
debt and one-month debt, estimate the hypothetical
spread that would be expected if ratings varied
across the spectrum from AAA to the B range. Input
the current levels of absolute short-term and longterm swap rates, by currency. Update both yield
curve and FX simulation parameters including rates
of mean reversion, volatilities, and correlations
between different points on the respective yield
curves and between different currencies.
b. Set the base case levels of percent of floating rate
debt and percent of debt that is short-term (one-month)
vs. longer term; set the maturity of new term debt for
any long-term debt issued in future years.
c. With these base parameters held fixed, vary
the target credit rating over the range from AAA to BB,
and for each target rating, set the fallback rating to a
level ranging from the target rating itself to the three
or four rating notches immediately below the target
rating. Identify the combination of target and fallback
ratings which together maximize shareholder value
(the “optimal rating” combination).
d. At the optimal rating, vary the percent of
floating rate debt from 0-100% in regular increments
(typically 10%) to identify the optimal floating percent.
Then run this optimal percent against alternative rating
combinations in the neighborhood of the previously
identified optimal rating to test whether the optimal
rating has shifted. If so, re-do the floating rate sensitivity
at this “new” optimal rating. This in turn may give rise
to a different floating rate optimum. Iterate this procedure until the shareholder value-maximizing configuration of both ratings and floating rate percent is found.
e. Given the optimal rating and floating rate
configuration, proceed to optimize other variables.
Like the rating and floating percent, dividend policy
decisions can also have a significant impact, as an
increase in dividend requirements will not support as
much debt. On the other hand, the maturity of new term
debt issues typically has a relatively weak impact. Also
to be varied are the targeted liquidity reserve assumptions, and, most importantly, for multi-currency analyses, the currency mix of the debt portfolio. Again, we
would test the robustness of previously determined
optimal parameters, and iterate if necessary.
Many variations on this sequence are possible. For
example, if the client wishes to focus purely on the
floating/fixed question assuming the current rating is
“locked in,” we would skip over step 9c. Additionally,
if desired, basic assumptions for the underlying paths
for EBITDA and/or interest rates can be changed, and
new optima solved for. For example, high growth vs.
low growth scenarios for EBITDA, or changes in
EBITDA volatility for the same growth rate, could well
lead to different conclusions regarding the optimal
rating and floating percent.
7. Based on industry credit analysis, build a
ratings model that estimates the firm’s projected credit
rating as a function of key credit ratios. Generally two
ratios are used, one involving the level of debt such as
debt/total capital and one involving interest expense
such as EBITDA/interest, though the specific choice
will vary by industry. The ratings model may take the
form of either a statistical regression or a look-up table
of ratio thresholds at different rating levels. A particular
rating then corresponds to a range of credit ratios
between one threshold level and the next.
8. Using the EBITDA, interest rate, and FX
simulation models, generate a multitude of simulation
paths (typically on the order of 1,000), where each
path represents a particular trajectory of monthly
EBITDA, yield curves, and FX rates, usually extending
out 20 years. The paths reflect estimated correlations
between EBITDA and LIBOR, across interest rates at
different points on the yield curve, and across different FX rates.
9. Once the underlying set of paths is developed,
this same set is used repeatedly against alternative
capital structure assumptions within DBLSM. By varying each key assumption over a range, we are able to
identify the combination of parameters that optimizes
shareholder value as well as accounting results. The
following is a typical sequence of analysis:
a. Input the company’s dividend policy, which
includes targeting both a payout ratio range and a
targeted annual dividend growth rate subject to a
maximum payout; further, specify any limits on the
maximum percent of outstanding shares that may be
repurchased annually.
45
VOLUME 15 NUMBER 1
SPRING 2002
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