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79-3
LARGE BANK FAILURES AND INVESTOR
PERCEPTIONS OF THE RISKINESS OF BANKING
Chayim Herzig-Marx
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L a r g e Ban k Failu r e s and Inves t o r P e r c e p t i o n s
of the R i s k i n e s s of Bank i n g
by
Chayim Herzig-Marx
Department of Research
Federal Reserve Bank of Chicago
The views expressed herein are solely those of the author and
do not necessarily represent the views of the Federal Reserve
Bank of Chicago or the Federal Reserve System. The material
contained is of a preliminary nature, is circulated to stimulate
discussion, and is not to be quoted without permission.
L a r g e B a n k Failu r e s and Investor P e r c e p t i o n s of the
R i s k i n e s s of Banking
Considerable research time and effort have been devoted lately to
examining the question whether financial markets can exert significant
control over risk-taking by commercial banks and whether market-based
information might prove a useful adjunct to the present regulatory ap
paratus.
On the whole, available evidence indicates that financial
markets are sensitive to the degree of leverage banks employ and levy
higher costs of funds against more leveraged banks.
In addition, there
is a growing volume of evidence that markets anticipate deterioration
in bank soundness before regulators do, often long before.
What
evidence there is, however, falls far short of incontrovertible proof
that the bank examination process can safely be left to the workings
of financial markets.
Because banking presently is highly regulated,
considerable sentiment remains that investor senses are dulled from
relying on regulators to monitor bank soundness.
An interesting line of research that has been pursued in two
recent studies is to examine investor behavior before and after the
failures of large commercial banks.
United States National Bank of
San Diego and the Franklin National Bank of New York were both far
larger than any other bank to fail in U.S. history.
Indeed, these
failures launched Congressional hearings into the adequacy of federal
bank regulation (federal bank •protection?).
Surely, had investors
previously assumed bank securities to be safe investments, after these
cataclysmic events they no longer would.
-2-
A model by Richard H. Pettway [6] looked at the rate of return
required by investors in bank common stocks.
Donald R. Fraser and
J. Patrick McCormack [2] modeled rates of return required by investors
in long-term bank debt.
If large bank failures really did alter in
vestor risk perceptions, one should detect a structural change in such
valuation models, higher rates of return now required as compensation
for the higher perceived level of risk.
The results of Pettway’s study
were that perceived risk to investors did not change as a result of
either large bank failure and no permanent structural change in the
equity model could be detected.
Fraser and McCormack, on the other hand,
found that required rates of return increased sharply and substantially
(about 66 basis points) after Franklin failed.
Pettway’s study used best methodology to test his hypothesis, thus
this paper will not have any direct comment to make on his work.
This
paper will argue that Fraser and. McCormack arrived at a correct con
clusion but their model was inadequate to discern the true nature of
the change that occurred.
Their dummy variable approach was unable to
separate changed investor perceptions concerning individual banks from
changed investor perceptions of the banking sector.
Qualitative results
of the more refined analysis in this paper will support Fraser and
McCormack’s conclusion, while quantitative estimates of the magnitude
of the change will indicate that the result is not much different from
Pettway’s.
however.
The policy implication of the present findings is important,
After Franklin failed, investors perceived risk in the banking
industry to be procyclical rather than insensitive to the business cycle
as before.
This means that financial markets will exert more restraint
over banks during periods of deteriorating bank soundness, which makes
market regulation of bank risk-taking more feasible.
-3-
I. Model, Sample, and Data
Following most previous empirical work on the valuation of risky
debt securities, this paper posits a risk premium model.
It is
illustrative, however, to write out the model in promised yield form:
(1)
RR = RF + M C (*) + IC(-),
where RR is the promised yield to maturity on risky debt, RF is the
yield to maturity on risk-free debt of the same maturity, MC is a
function representing conditions in money and capital markets, and IC
is a function of risk characteristics of specific issuers.
When
estimated for a purely contemporaneous cross section, variables in MC
are suppressed since market conditions are constant over the entire
sample.
When observations are drawn from differing time periods,
however, MC must be specified, which Fraser and McCormack fail to do.
Equation (1) is a microeconomic relationship, and such a model
could be applied to any class of financial or non-financial firms.
The methodological difference between the present paper and that of
Fraser and McCormack can best be understood by imagining that (1) is to
be aggregated over all commercial banks and then incorporated into a
general equilibrium model of the financial sector.
The IC function
can then be seen to denote individual bank deviations from the norm for
all commercial banks.
Hence in the aggregation process the IC
function will drop out (except possibly for certain institutional
features that might appear in the general structural model).
The
perceived riskiness of the commercial banking sector is captured by
the MC function, which relates the banking industry to events in the
economy as a whole.
Thus, when asking questions about investor perceptions
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of the banking industry, one is actually testing hypotheses about the
parameters of the MC function, not the IC function.
Since Fraser and
McCormack do not specify MC completely, their model is insuffxcxent to
answer the question they raise.
Changes over time in parameters from
the IC function, on the other hand, indicate whether relative riskiness
of banks within the sector has altered.
In specifying the MC function, two types of variables are included.
The first type measures general conditions in financial markets, and for
this purpose the present paper uses the overall level of xnterest rates
as measured by Treasury yields and the yield spread between medium grade
and high grade bonds as reported by Dow Jones and Company (Barron _s
National Business and Financial Weekly).
The yield on Treasury secur
ities anchors one end of the risk structure of interest rates and,
because it is the most efficient of the debt markets, Treasury yields
are probably observed with the least error.
Justificatxon for the
spread between medium and high grade bond yields as an xndxcator of
general economic conditions can be found in the work of Jaffee [4].
He found that the Baa-Aaa rate spread (Moody's ratings) was satxsfactorily explained by six variables denoting economic conditions:
consumer sentiment, growth rate of corporate retained earnings, growth
rate of fixed capital investment, the unemployment rate, growth rate
of the output price index, and the level of interest rates.
paper, Jaffee's results are inverted.
In this
The yield spread, denoted SPREAD
increases when economic conditions deteriorate and decreases during
expansions.
Hence its sign is expected to be positive.
Following
recent theoretical work of Merton [5], the expected sign of MKT RATE,
the Treasury yield, is negative.
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The second set of variables included in MC are aspects of in
vestor preferences unrelated to specific issuing firms, namely, market^ i l ^ ^ y , term to maturity, and private vs* public placements*
Market—
ability of an issue is measured by its total size (ISSUE) and term
to maturity (TERM) is in years and decimals from the date of issue.
The sample for the present study differs from that of Fraser and
McCormack by including issues placed privately as well as publicly
marketed bonds.
The variable PRIVATE takes the value unity if the
bond is privately placed, zero otherwise.
Although marketability
is not of concern for private issuances, the size of the bond issue
can be taken to measure per unit transactions costs, mostly negotiation
costs.
Thus, the expected sign of ISSUE is negative for private as well
as public issues.
The expected sign of TERM is positive, since the
probability of default is usually taken to be an increasing function
time.
The expected sign of PRIVATE is positive, since one expects
smaller firms and also those with weaker financial conditions to prefer
private placements.
The IC function is specified to contain two variables.
The
capitalization variable, LEVERAGE, is the ratio of all interest-bearing
liabilities to total assets.
Non-interest bearing liabilities are
dominated by demand deposits, which for most banks are held primarily
as part of the customer relationship and thus assure a line of credit.
As compensating balances, they tend to be a stable source of funds to
the bank.
Interest-bearing liabilities, on the other hand, are
dominated by federal funds, certificates of deposit, and other borrowings,
which are highly interest—sensitive and thus are the most important
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source of balance sheet leveraging.
The other IC variable is the
gross rate of return on income-producing assets, RGROSS, which is
included as a measure of the riskiness of the total bank portfolio.
The expected signs of both LEVERAGE and RGROSS are consequently
positive.
Before estimation, the coefficient of RF in equation (1) is
constrained to be unity by subtracting that variable from both sides
of the relationship.
The dependent variable is thus risk premium.
The sample consists of 230 observations drawn mainly from the
Trying Trust Company bimonthly listings of securities issued by banks
and bank holding companies [3].
As with most previous research, this
sample includes debt issued by both banks and bank holding companies.
Detailed analyses conducted elsewhere [7] have indicated that, for this
exact sample, the regression model used in this paper is not sensitive
to the distinction between banks and bank holding companies.
Observa
tions are taken from years 1971 through 1977 inclusive, and thus en
compass a considerably longer period than any other published study of
bank risk premiums.
In particular, a full year and a half's additional
observations after the failure of Franklin National are included in the
present sample than were included in Fraser and McCormack's (in total,
129 observations after Franklin failed).
Balance sheet and income data come from Reports of Condition and
Income filed with federal bank regulators.
are used for RF, the risk-free rate.
Yields on Treasury securities
Fraser and McCormack use Aaa bond
rates instead, mostly because such bonds are issued more frequently,
hence tax considerations related to widely differing coupons are minimal.
The present study excludes deep discount bonds ("flower bonds").
The
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gain in degrees of freedom is consequently judged to outweigh any minor
difference due to tax.
II.
Results
Table 1 presents basic regression results for the risk premium
model described in section I.
The column labeled "whole sample" under
Model 1 gives parameter estimates for the empirical counterpart of
equation (1) of the text.
Each of the five variables comprising the
MC function bears the expected sign and is significantly different from
zero at the 1% level of Type I error.
MKT RATE, SPREAD, and PRIVATE
have coefficients that are quantitatively important, while the coeffi
cients of ISSUE and TERM imply that investors are not especially sensi
tive to changes in the underlying variables.
A $10 million increase in
the size of the issue results in only a 4 basis point decrease in
risk premium, while each additional year in term to maturity requires
only 2 basis points in yield.
Of the two variables in the IC function,
only the gross rate of return on assets is different from zero at the
5% level.
To this extent, the findings of the present paper agree with
those of Fraser and McCormack, who also found leverage to be unimportant
as a determinant of risk premium and issue size to be moderately
important.
The explanatory power of the present model, judged by
adjusted R-squared, is a good deal lower than Fraser and McCormack's
model, but the value of the overall F statistic is much higher.
Although in Model 1 the distinction between issues sold publicly
and those placed privately is denoted by a simple intercept dummy
variable, an analysis of covariance was conducted to determine if
slope coefficients are the same across both types of issues.
The
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value of the F statistic for this test is 0.856 for Model 1 and 1.486
for Model 2.
Thus, any difference between private and public evalua
tions of bank debt securities is satisfactorily captured by the in
tercept term.
Adding a dummy variable (FRANKLIN) for issues sold after the
failure of Franklin National Bank (Model 2) shows the results of
adopting Fraser and McCormack's methodology.
two striking effects on the regression model.
This addition produces
The coefficient of
RGROSS falls by half and becomes insignificantly different from zero.
Through the remainder of the empirical tests to be reported, the
coefficient of RGROSS remains insignificant.
To some extent, this
change is due to multicollinearity among RGROSS, MKT RATE, and
FRANKLIN.
Since RGROSS is a bank—specific variable, and hence does not
convey information on investor perceptions of commercial banking as
a financial sector, we are content simply to note the decline in its
significance without attempting to discover the precise cause.
The more interesting change occurring between Models 1 and 2 is
that the coefficient of SPREAD falls by more than half while still
retaining statistical significance.
This variable is extremely im
portant since it denotes the economy's position in the business cycle
and thus its coefficient directly relates investor perceptions con
cerning bank risk to macroeconomic conditions.
The fact that SPREAD'S
coefficient is strongly altered by the inclusion of FRANKLIN suggests
the possibility of structural change in the regression model due to
the failure of Franklin National Bank.
labeled
before
The two columns under Model 1
and "after" estimate the regression model on the two
-9-
subperiods separately.
The F statistic from the test of the homogeneity
of slopes before and after Franklin, allowing different intercepts, is
3.319 with 7 and 214 degrees of freedom, significant at the 1% level.
One must thus conclude, as Fraser and McCormack stated, that a struc
tural change did occur after the failure of Franklin National Bank.
Comparing the "before" and "after" columns shows that only variable
whose coefficient changes dramatically is SPREAD, which changes from
significantly negative to significantly positive.
One might also note
that the explanatory power of the model falls sharply in the "after"
period, although one can easily reject the null hypothesis that all
slope coefficients are zero.
Because an F test for homogeneity of slopes is not particularly
sensitive to changes in individual coefficients, separate slope dummy
variables for the period after Franklin failed were entered into a
single regression equation, one slope dummy variable for each of the
seven independent variables other than FRANKLIN.
Only one slope dummy
proved statistically significant (two-tailed tests), that for SPREAD.
Regression results for Model 2 of Table 1 augmented by this inter
active term are shown in the middle column of Table 2.
Figure 1
graphs the relationship between risk premium and SPREAD before and
after Franklin failed.
SPREAD is interpreted as a measure of macro-
economic risk, larger values as stated before representing deteriorating
economic conditions.
The relationship between macro risk and return,
assumed linear, is drawn as a solid line for the period before
Franklin failed.
The intercept and slope for this line are the
coefficients of "intercept" and SPREAD in Table 2, and the slope is
-10-
Risk
Premium
Figure 1
-11-
drawn taking the coefficient of SPREAD to be significantly different
from zero.
This relationship shows that before Franklin failed investors
believed bank debt securities became more safe as economic conditions
worsened.
The intercept and slope for the macro risk relationship
after Franklin failed are calculated by summing, respectively,
"intercept" with FRANKLIN and SPREAD with FRANKLIN*SPREAD and are shown
as the dotted line.
Thus, after Franklin failed, worsening economic
conditions were generally associated with a significantly greater
degree of risk to holders of bank securities.
An alternative means of presenting these results follows from the
work of Cohan [1],
Although economic and finance theory indicate that
investors require higher expected rates of return as compensation for
bearing greater risk, risk premium is itself a not very enlightening
index of risk.
Risk is usually taken to mean the probability that an
investment will default in whole or in part.
Noting that in perfect
capital markets investors will not expect to earn, in the long run, in
excess of the risk-free rate of return, Cohan is able to derive an
expression for the probability of payment in whole over the life of a
bond, which probability is a simple function of the promised yield on
the bond and the promised yield on a risk-free bond of identical
maturity.
The relationship is
where RF and RR have already been defined as risk-free and risky rates
of return and T is term to maturity (number of periods).
Since P is
the periodic probability of payment in whole, 1-P is the periodic pro-
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bability of default in whole or in part.
The quantity 1-P, denoted
DEFAULT, is used as the dependent variable of the risk premium model
in the right-hand column of Table 2.
Coefficients indicate the
effects of one unit increases in the independent variables on the
probability of default per year.
The units of the dependent variable
are percentage points of probability; i.e., a one-half chance of
default would be 50.0.
Signs of all coefficients are the same with DEFAULT as the de
pendent variable with the exception of TERM, which is an arithmetic
quirk.
Given a promised yield on a risky bond, larger values of TERM
imply smaller periodic probabilities of default.
Apart from the in
tercept, the only variables whose coefficients are quantitatively
important are FRANKLIN and FRANKLIN*SPREAD.
Note also that the
coefficient of SPREAD itself in this formulation is not significantly
different from zero.
Thus, drawing Figure 1 with probability of
default on the vertical axis instead of risk premium would depict
the pre-Franklin relation as essentially horizontal.
After Franklin
failed, however, probabilities of default became viewed as increasing
as the economy moved into a cyclical trough and decreasing as the
economy moved into an expansionary phase.
The quantitative importance of these results can best be made
clear from calculations based upon the sample at hand.
At mean values
for all issues before Franklin failed, the probability of repayment
in full over the entire life of the average bond in the sample was
98.6% (average term to maturity is 16.6 years).
A one standard
deviation increase in the medium grade-high grade yield spread,
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equivalent to 10.7 basis points, would hav^. raised that probability in
investors' eyes to at most 98.7%.
At mean values for all issues after
Franklin failed, the probability of payment in full over the entire
life of the average bond in the sample was 98.2%, or about four—tenths
of one percent lower than bonds issued in the pre-failure period.
A one standard deviation increase in SPREAD, equivalent to 9.9
basis points, would now reduce the probability of repayment in
full to 97.8% (average term to maturity is 15.3 years).
Thus, while
it is reasonably clear that a structural change in the way market
investors view the riskiness of long-term bank debt did occur after
the failure of Franklin National Bank, the size of the change was
certainly not great when gauged by the effect of worsening economic
conditions on the probability of repayment in full.
The banking sector
was not suddenly seen to be enormously more risky than it had been.
Furthermore, investors did not alter the way they judged relative
riskiness of firms within the banking sector.
III.
Summary and Conclusions
Fraser and McCormack report that after the failure of Franklin
National Bank spreads between yields on Aaa rated bonds and bank debt
increased some 66 basis points.
This increase they attributed to an
alteration in the risk structure of interest rates that banks face in
debt markets.
Since their risk variables were not significant in ex
plaining risk premium, it is not entirely clear just what their use of
the term "risk structure of interest rates" is intended to convey.
Results of this paper, using a more completely specified model of risk
premium, show that the structural change occurring after Franklin's
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demise concerned investor perception of bank riskiness over the
business cycle.
Before Franklin, the riskiness of investment in long
term bank debt securities was viewed as more or less insensitive to
the economy’s position in the business cycle, while after Franklin1s
failure bank risk was viewed as being pro-cyclical.
Interestingly,
4
the intercept term on the risk-return tradeoff is smaller after Franklin
than before, which is contrary to the result that Fraser and McCormack
present.
The explanation for this is simple, however:
banks are
now viewed as being significantly less risky during expansionary periods
as well as more risky during troughs.
The "risk structure of interest
rates" facing banks can thus be viewed on a macro as well as on the
more customary micro level.
On the micro level, results in this paper
are similar to Fraser and McCormack’s in that traditional micro
measures of risk, such as leverage and gross rate of return on assets,
are not significant in explaining risk premium.
It is on the macro
level where the significant structural shift of investor risk per
ceptions occurred.
Finally, one can compare the results of these two debt market papers
with the findings of Pettway based on equity markets.
Because method
ologies are so different, a definitive reconciliation of the divergent
results is probably impossible.
One should note, however, that results
in the present paper can be compared with Pettway’s more appropriately
than can results given by Fraser and McCormack because both Pettway and
the present paper compare measures of investor risk with events in the
general economy.
While this paper finds investor perceptions of the
riskiness of the banking sector to have become more procyclical after
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the failure of Franklin, Pettway finds nc such significant shift.
A
conflict of results thus remains to be reconciled; but evidence presented
here, that implied probabilities of failure increased only slightly
after Franklin's failure, suggests that quantitatively there is not
much of a conflict to resolve.
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REFERENCES
[1]
Cohan, Avery B. nThe Ex Ante Quality of Direct Placements, 195161,n in Jack M. Guttentag, editor, Essays on Interest Rates,
Volume II. National Bureau of Economic Research (1971),
pp. 281-336.
[2]
Fraser, Donald R. and McCormack, J. Patrick.
"Large Bank Failures
and Investor Risk Perceptions: Evidence from the Debt Market,"
Journal of Financial and Quantitative Analysis (September
1978), pp. 527-32.
[3]
Irving Trust Company. Report of Debt Securities Issued by Commer
cial Banks and Holding Companies. Corporate Financial
Counseling Department, bimonthly with annual summary.
[4]
Jaffee, Dwight M. "Cyclical Variations in the Risk Structure of
Interest Rates," Journal of Monetary Economics (July 1975),
pp. 309-25.
[5]
Merton, Robert C. "On the Pricing of Corporate Debt: The Risk
Structure of Interest Rates," Journal of Finance (May 1974),
pp. 449-70.
[6]
Pettway, Richard H. "The Effects of Large Bank Failures upon
Investors' Risk Cognizance in the Commercial Banking Industry,"
Journal of Financial and Quantitative Analysis (September
1976), pp. 465-77.
[7]
Weaver, Anne S. and Herzig-Marx, Chayim. "A Comparative Study of
the Effect of Leverage on Risk Premiums for Debt Issues of
Banks and Bank Holding Companies," Staff Memoranda 78-1,
Federal Reserve Bank of Chicago.
-
17-
Table 1
Regression Results for Risk Premium Model
Independent
Variable
whole sample
Model 1
before
after
Model 2
whole sample
Intercept
2.242***
(0.344)
4.092***
(0.365)
2.618*
*
(1.511)
3.557***
(0.491)
MKT RATE
-0.352***
(0.066)
-0.514***
(0.057)
-0.388***
(0.196)
-0.494***
(0.075)
SPREAD
1.191***
(0.243)
-0.639a
(0.262)
1.722***
(0.516)
0.553***
(0.294)
ISSUE
-0.004***
(0.001)
-0.004***
(0.001)
-0.003***
(0.001)
-0.004***
(0.001)
TERM
0.020***
(0.004)
0.030***
(0.004)
0.014*
(0.011)
0.024***
(0.004)
PRIVATE
0.341***
(0.073)
0.244***
(0.074)
0.355***
(0.115)
0.280***
(0.073)
RGROSS
0.042**
(0.020)
0.017
(0.019)
0.006
(0.035)
0.021
(0.020)
LEVERAGE
0.003
(0.003)
0.005**
(0.003)
-0.0013
(0.005)
0.002
(O.O03)
FRANKLIN
R2
F
RSS
0.521***
(0.142)
.334
17.380***
47.161
.654
30.171***
8.345
.233
6.207***
31.766
.369
17.730***
44.466
Notes: Standard errors are in parentheses. RSS is residual sum
of squares.
Significance of coefficients is judged by one-tailed tests (twotailed for intercepts) and denoted as follows:
*significant at 10% level of Type I error.
**significant at 5% level of Type I error.
***significant at 1% level of Type I error.
Sign counter to expectation, significance not indicated.
-18-
Table 2
Regression Results with Interactive Variable
Dependent Variable
PREMIUM
DEFAULT
Intercept
4.164***
(0.492)
0.402***
(0.072)
MKT RATE
-0.493***
(0.072)
-0.040***
(0.011)
SPREAD
-0.633a
(0.391)
-0.054
(0.057)
ISSUE
-0.004***
(0.001)
-0.000**
(0.000)
TERM
0.026***
(0.004)
-0.005***
(0.001)
PRIVATE
0.291***
(0.070)
0.022**
(0.010)
RGROSS
0.016
(0.019)
0.005**
(0.003)
LEVERAGE
0.002
(0.003)
0.000
(0.000)
FRANKLIN
-1.141***
(0.402)
-0.179***
(0.059)
FRANKLIN*SPREAD
2.469***
(0.562)
0.299***
(0.082)
0.417
19.212***
40.877
0.402
18.115***
S*» I.
Independent
Variable
Notes:
See Table 1
@FedFRASER