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Federal Reserve Bank San Francisco | Monitoring Debt Market Information for Bank Supervisory Purposes |

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FRBSF ECONOMIC LeTTer
2003-35

November 28, 2003

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Monitoring Debt Market Information for Bank Supervisory Purposes
John Krainer and Jose A. Lopez
Debt market information and supervisory monitoring
Can BHC debt spreads anticipate BOPEC changes?
Debt market information in an off-site monitoring model
References
Bank supervisors monitor bank holding companies (BHCs) in order to enforce regulations and gauge their
soundness so as to guard against systemic risk in the financial system. This monitoring is chiefly
conducted using supervisory resources, such as bank examinations and quarterly filings of balance sheet
information. BHCs are also monitored by other parties, in particular investors in their public securities;
this type of monitoring is commonly referred to as market discipline, and the market assessments from
it are reflected in the prices of BHC public securities.
In the past few years, supervisors have expressed an intent to incorporate more market information into
their monitoring efforts. Researchers and policymakers have advocated using BHC subordinated debt as
a tool for increasing the degree of market discipline applied to BHCs. A recent study by the Board of
Governors of the Federal Reserve System and the Secretary of the Treasury (2000) found evidence
supporting this assertion and concluded that subordinated debt issuance might enhance both direct and
indirect market discipline.
In this Economic Letter, we present empirical evidence on the potential usefulness of BHC debt market
information, and securities market information more broadly, for supervisory monitoring. We find that
changes in BHC bond yields precede corresponding changes in supervisory BHC ratings by a year. We
also assess the contribution of BHC debt yields in the context of an off-site monitoring model that
includes both supervisory and equity market variables. Our results indicate that debt market information
is useful for supervisory monitoring, even in the presence of equity market data. In fact, debt yields
contributed more explanatory power for BHCs that are relatively closer to insolvency.
Debt market information and supervisory monitoring

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Federal Reserve Bank San Francisco | Monitoring Debt Market Information for Bank Supervisory Purposes |

Publicly traded BHC debt, and subordinated debt in particular, may be useful for supervisory monitoring
because, in general, BHC debtholders have incentives roughly in line with supervisors. That is, investors
in BHC subordinated debt are among the first to lose their investments, after equity investors, if the
bank defaults, but they do not benefit directly from any gains that accrue beyond the face value of their
holdings. Like supervisors, these investors have an incentive to monitor BHC conditions, and their
assessments could be imputed from changes in public BHC debt prices. However, as a BHC nears
insolvency, the incentives of subordinated debt holders become more like those of equity investors, who
are willing to participate in riskier transactions to “save” the concern. Such transactions would not be
aligned with the concerns of supervisors, who would be most interested in safeguarding the existing
assets. Note, however, that changes in equity prices still should contain information on investor
assessments of BHC performance that could be useful for supervisory monitoring.
We gauged the potential supervisory value of BHC debt market information by incorporating it into
models of BHC supervisory ratings. The Federal Reserve supervises U.S. BHCs, which make up the bulk
of public bond issuance by banking institutions. (The remainder of these bonds are issued by individual
banks within BHCs.) The primary component of BHC supervision is on-site inspections, which generally
are conducted once a year, although the largest and most complex BHCs have a continuous supervisory
presence. At the conclusion of a BHC inspection, the supervisors assign a composite BOPEC rating that
summarizes the five key areas of supervisory concern: the condition of the BHC’s Bank subsidiaries,
Other nonbank subsidiaries, Parent company, Earnings, and Capital adequacy. BOPEC ratings are
assigned according to an absolute scale from the highest rating of one to the lowest rating of five; these
ratings are confidential and are not made public.
Can BHC debt spreads anticipate BOPEC changes?
If BHC debt market information is to be useful to supervisors, it should agree with supervisory
assessments a reasonably large fraction of the time. That is, large changes in BHC debt yields should
give supervisors an early warning of changes in BHC conditions. To examine this possibility, we analyzed
changes in BHC debt yields leading up to BOPEC assignments. The yields were adjusted to account for
multiple bond issues by the same BHC, bond maturities, public credit ratings, and prior BOPEC ratings;
see Krainer and Lopez (2003). One caveat to our analysis is that bonds are largely traded over-thecounter with greatly varying degrees of liquidity, which should have an impact on the quality and
reliability of the observed bond yields.
As shown in Figure 1, changes in adjusted BHC yields moved in
accordance with and up to a year prior to the future BOPEC
assignments. For the BOPEC downgrades in our sample, the
average cumulative increase in yields was statistically
significant at about one percentage point by the time of the
inspection, which is a signal that debt market investors were
demanding an increase in their investment return. For the
sample’s upgrades, adjusted yields dropped by 75 basis points
by the time of the inspection. For the inspections without
BOPEC changes, the yield changes were effectively zero on
average. We thus conclude that changes in adjusted BHC debt
yields are consistent with future supervisory assessments and
could be useful for supervisory monitoring.
Debt market information in an off-site monitoring model
We gauged the potential usefulness of BHC debt market
information for supervisory monitoring by combining it with supervisory variables in an off-site
monitoring model. Securities market data are, in general, available sooner than supervisory data from

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Federal Reserve Bank San Francisco | Monitoring Debt Market Information for Bank Supervisory Purposes |

quarterly financial statements, which could assist an off-site monitoring model in detecting sudden
changes in BHC conditions. Since the cost of incorporating securities market variables into the model is
low, even small net improvements in forecast accuracy could be valuable. We used our proposed BOPEC
off-site monitoring (BOM) model (Krainer and Lopez 2001). The benchmark, or core, BOM model
examines the relationship between BOPEC ratings and selected supervisory variables; this model was
extended to incorporate our adjusted BHC debt yields. When the model was estimated over our full
sample of BOPEC ratings assigned from 1990 to mid-1998, adjusted BHC debt yields were statistically
significant and contributed to the model’s empirical fit of the data.
BHC debt yields, of course, represent only one source of market information. As shown in Krainer and
Lopez (2001), changes in BHC equity prices also contain information useful for supervisory monitoring
within the context of the BOM model. When we extended the core model to include equity market
variables, both sets of securities market variables were statistically significant and improved the model’s
empirical fit of the data more so than models using just one set of market variables. This result suggests
that the BHC assessments expressed by both sets of investors via changes in BHC securities prices could
contribute to supervisory monitoring.
We further examined whether securities market variables might provide different information depending
on how close a BHC is to default, measured as the point at which BHC liabilities exceed assets. Using a
measure of a firm’s default probability, commonly known as the distance-to-default, based on the
market value of BHC assets and outstanding liabilities, we ranked the publicly traded BHCs in our
sample and used those rankings within the BOM model. We found that measures of equity returns had a
greater impact when BHCs were further away from default and that debt yields had more impact when
BHCs were closer to (but not in) default. The asymmetric contributions of debt and equity return
variables are consistent with the theory that debtholders do not benefit directly from gains accruing
beyond the face value of their investment, but are affected by actions that the BHC takes while
relatively closer to default. In contrast, equity holders should be less sensitive to changes in firm value
close to default because their investment might disappear entirely, while further from default, they
would be more sensitive to changes in BHC condition.
To be useful for supervisory monitoring, the extended BOM model with both BHC debt and equity market
variables also must forecast BOPEC ratings accurately. To mimic actual practices, we re-estimated the
BOM model with and without securities market variables every quarter based on a rolling four quarter
sample of data. The estimated models were then used to generate one-quarter-ahead BOPEC forecasts.
They generated a forecasted change in supervisory rating if the forecast was more than three-quarters
of a rating grade different from its corresponding lagged BOPEC rating. When compared to all our
sample’s ratings at four quarters prior to assignment, this extended model correctly signaled 67% of all
the BOPEC assignments and almost 60% of all BOPEC changes. These percentages increase to 70% and
88%, respectively, at one quarter prior to assignment.
Another dimension of accuracy for an off-site monitoring model is the mix of correct and incorrect
forecast signals; for example, if the model signals a downgrade, what is the probability that the signal is
correct? This dimension of accuracy is measured using the ratio of correctly signaled downgrades to the
total number of signaled downgrades. We find “no change” signals were the most common and were
correct 67% of the time. Downgrade signals, which are of more interest to supervisors, were correct
58% of the time at four quarters prior and improved to 86% at one quarter prior. Upgrade signals
occurred with the same frequencies. Our results indicate that forecast signals from the extended BOM
model were accurate a large percentage of the time, even up to a year prior to the BOPEC assignments,
and could thus be useful for off-site BHC monitoring.
A critical question is whether forecasts from the extended model including both sets of securities market
variables provides further information about BOPEC ratings beyond that obtained using forecasts from
the core model using only supervisory variables. To make this assessment, we compared the accuracy

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Federal Reserve Bank San Francisco | Monitoring Debt Market Information for Bank Supervisory Purposes |

of the two sets of forecasts statistically, which in this case is the percentage of BOPEC ratings accurately
forecast. By this measure, we found little difference between the accuracy of these two sets of
competing forecasts.
This result, however, does not mean that the forecasted BOPEC ratings from the two models are
identical. Since the forecasting literature has shown that combining forecasts from different models can
improve forecast accuracy, we decided to gauge the contribution of securities market information by
examining the additional forecast signals for BHCs with public securities generated by the extended
model relative to the core model’s signals. At four quarters prior, the extended model signaled 54
additional BOPEC changes, of which 27 were correct and were almost evenly split between upgrades and
downgrades. For one quarter prior, 65 additional BOPEC changes were signaled, of which 42 (or 65%)
were correct and again almost evenly split between upgrades and downgrades.
Seen in this light, the marginal benefit of incorporating securities market variables into the BOM model is
notable. At four quarters prior, the additional 27 correct signals regarding BOPEC changes increased the
total to 93, a 40% increase. At one quarter prior, the additional 42 correct signals increased the total of
correct BOPEC change forecasts by over 30% to 175. The benefits from having the additional correct
early-warning signals provided by these forecasts could very well be worth the supervisory costs of
dealing with the additional incorrect signals.
John Krainer
Economist
Jose A. Lopez
Senior Economist
References
[URLs accessed November 2003.]
Board of Governors of the Federal Reserve System and the U.S. Department of the Treasury. 2000. “The
Feasibility and Desirability of Mandatory Subordinated Debt.”
Report to Congress pursuant to section
108 of the Gramm-Leach-Bliley Act of 1999.
http://www.federalreserve.gov/boarddocs/rptcongress/debt/subord_debt_2000.pdf
Krainer, J., and J.A. Lopez. 2001. “Incorporating Equity Market Information into Supervisory Monitoring
Models.” FRBSF Working Paper 01-14.
/economic-research/papers/2001/wp01-14bk.pdf
Krainer, J., and J.A. Lopez. 2003. “How Might Financial Market Information Be Used for Supervisory
Purposes?” FRBSF Economic Review, pp. 29-45.
/economic-research/review/2003/article3.pdf
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Opinions expressed in FRBSF Economic Letter
do not necessarily reflect the views of the
management of the Federal Reserve Bank of
San Francisco or of the Board of Governors of
the Federal Reserve System. This publication is
edited by Sam Zuckerman and Anita Todd.
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