FRBSF Economic Letter
2005-14; June 24, 2005
Stress Tests: Useful Complements to Financial Risk
Models
Risk-management practices at financial institutions have
undergone a quantitative revolution over the past decade
or so. Increasingly, financial firms rely on statistical
models to measure and manage financial risks, ranging from
market risks (such as exchange rate fluctuations) to credit
risks (such as borrowers' default probabilities) to operational
risks (such as expected losses due to fraudulent transactions).
Such models have gained credibility because they provide
a coherent framework for identifying, analyzing and communicating
these risks. However, models are only simplifications of
reality and cannot capture every aspect of these risks.
For example, unlikely yet possible events that could cause
significant losses are not captured readily by models constructed
to monitor typical risk outcomes.
To address this shortcoming,
risk managers have developed a practice known as "stress
testing," which also
has become an important element of the supervisory monitoring
of financial firms. Indeed, many supervisory agencies have
begun using stress-testing techniques to assess the capital
adequacy of individual firms and even national financial
systems. In this Economic Letter, I define stress testing,
describe its possible applications, highlight certain techniques
developed to conduct this testing, and survey its recent
use by supervisory agencies.
Definition and applications
An underlying principle of modern financial risk management
is that statistical models can be used to estimate the
distribution of possible future financial outcomes, such
as changes in interest rates or a firm's credit quality.
Academic and practitioner research supports the view
that such models characterize the probabilities of
most future
outcomes reasonably well. For example, as part of managing
the risk of a bond portfolio, a firm could estimate the
distribution of possible outcomes, say, one-day-ahead
by modeling the behavior of a set of risk factors,
such as
changes in interest rates, that affect the portfolio's
value. That estimated distribution indicates the probability
that the portfolio's value will be above (or below) any
given value. With that information in hand, the firm
can manage its portfolio's risk exposure by setting
aside capital
sufficient to cover, say, 95% of possible portfolio losses
arising from adverse outcomes. Such value-at-risk (VaR)
analysis has become a standard risk-management tool.
However, VaR models cannot incorporate all possible
risk outcomes.
Historical experience has shown that they cannot capture
sudden and dramatic changes in market circumstances since
such changes are, by definition, atypical.
To address this
shortcoming, risk managers have developed "stress
testing," which is a risk-management tool used to
evaluate the potential impact on portfolio values of unlikely,
although plausible, events or movements in a set of financial
variables. While such unlikely outcomes do not mesh easily
with VaR analysis, analysis of these outcomes can provide
further information on expected portfolio losses over a
given time horizon. Accordingly, stress testing is used
increasingly as a complement to the more standard statistical
models used for VaR analysis.
Stress testing is mostly used
in managing market risk, which deals primarily with traded
market portfolios. These
portfolios include interest rate, equity, foreign exchange,
and commodity instruments and are amenable to stress
testing because their market prices are updated on a regular
basis.
A survey of financial firms by the Committee on the Global
Financial System (CGFS, 2005) found that more than 80%
of stress tests were applied to traded portfolios and
that interest rate movements are the basis for most of
them;
however, stress-testing applications have expanded to
considering credit risk in loan portfolios as well as the
impact of
sudden interest rate changes on firms' funding sources.
In
addition to providing a "reality check" on
VaR models, stress testing has been found to be an effective
communication tool between a firm's senior management
and its business lines. The communication advantage that
stress
tests have over VaR analysis is their explicit linking
of potential losses to a specific and concrete set of
events. That is, stress tests can be thought of as exercises
based
on a unique set of outcomes for the relevant risk factors—interest
rates change by a certain number of basis points, the
U.S. dollar depreciates by a certain percent, and so
on. In
contrast, in the VaR framework, there is no unique configuration
of the underlying risk factors that is identified with
the value of, say, a portfolio falling below a given
level. Again, however, stress tests and VaR analysis
provide different
information and are considered to be complementary. Techniques
for stress testing
Stress-testing techniques fall into two general categories:
sensitivity tests and scenario tests. Sensitivity tests
assess the impact of large movements in financial variables
on portfolio values without specifying the reasons for
such movements. A typical example might be a 100 basis
point increase across the yield curve or a 10% decline
in stock market indexes. These tests can be run relatively
quickly and are commonly used as a first approximation
of the portfolio impact of a financial market move. However,
the analysis lacks historical and economic content, which
can limit its usefulness for longer term risk-management
decisions.
Scenario tests are constructed either within
the context of a specific portfolio or in light of historical
events
common across portfolios. In a stylized version of the
specific portfolio approach, risk managers identify a
portfolio's key financial drivers and then formulate scenarios
in which
these drivers are stressed beyond standard VaR levels.
For the event-driven approach, stress scenarios are based
on plausible but unlikely events, and the analysis addresses
how these events might affect the risk factors relevant
to a portfolio. Commonly used events for historical scenarios
are the large U.S. stock market declines in October 1987,
the Asian financial crisis of 1997, the financial market
fluctuations surrounding the Russian default of 1998,
and financial market developments following the September
11,
2001, terrorist attacks in the United States.
The choice
of portfolio-based or event-based scenarios depends on
several factors, including the relevance of
historical events to the portfolio and the firm resources
available for conducting the exercise. Historical scenarios
are developed more fully since they reflect an actual
stressed market environment that can be studied in great
detail,
therefore requiring fewer judgements by risk managers.
Since such events may not be relevant to a specific portfolio,
hypothetical scenarios that are directly relevant can
be crafted, but at the cost of a more labor-intensive and
judgmental process. Hybrid scenarios are commonly used,
where risk managers construct scenarios that are informed
by historical market movements that may not be linked
to
a specific event. Historical events also can provide
information for calibrating movements in other market factors,
such
as firm credit quality and market liquidity. More generally,
risk managers always face a trade-off between scenario
realism and comprehensibility; that is, more fully developed
scenarios generate results that are more difficult to
interpret.
With
respect to credit risk, stress testing is of two main
types: stress testing of credit spreads, such as corporate
bond spreads, in trading portfolios and the less frequent
stress testing of loan portfolios. Stress testing credit
spreads in trading portfolios is reasonably straightforward
and more directly related to market risk analysis. For
stress testing of loan portfolios, variables such as
borrower
credit ratings and collateral values are stressed, often
using scenarios based on shocks to the macroeconomy.
Although based on a common source of risk, efforts to integrate
credit risk stress tests for both trading and loan portfolios
have been hindered by several factors, such as differences
in accounting treatment and a lack of trading in certain
credit instruments. At an even more basic level, many
firms
lack sufficient historical data for such analyses as
well as the system infrastructure to generate integrated
credit
risk profiles. Supervisory issues and uses
Supervisors of financial institutions monitor the current
condition and risk exposures of individual financial
institutions. Hence, supervisors now generally work
to understand and
assess whether institutions' risk-management systems
actually measure and assist managers in controlling
the relevant
financial risks. Although risk-management systems vary
widely across financial institutions, supervisors have
worked to set forth general principles that are widely
applicable; for example, see the Trading and Capital
Market Activity Manual of the Federal Reserve System
(2003). With
respect to stress testing, supervisors are concerned
that institutions monitor their risk exposures with
appropriate
reference to unlikely events that could cause portfolio
losses. Furthermore, they are interested in ensuring
that stress testing procedures are detailed in the
firm's risk-management
policies and that senior management actively uses the
information, for example, in setting trading limits.
As highlighted
in the CGFS survey, some supervisory concerns remain,
including the need to improve credit and liquidity
risk stress testing
as well as the need to integrate market and credit risks
across the institution.
In addition to assessing firms'
risk-management practices, supervisors have developed
stress-testing tools
for their
own monitoring purposes. As summarized by Collier et
al. (2003), the Federal Deposit Insurance Corporation uses
a stress-testing model to identify depository institutions
that are potentially vulnerable to real estate markets.
The model is calibrated to the New England real estate
crisis of the early 1990s, which caused the closure of
several depository institutions. With regard to interest
rate risk, the Federal Reserve System maintains a duration-based
valuation model that examines the impact of a 200-basis-point
increase in rates on bank portfolio values; see Sierra
and Yeager (2003). The model can be used to detect banks
that would appear to be the most vulnerable to rising
interest
rates.
Supervisors have recently been developing similar
tools for assessing national financial systems overall.
For example,
macroeconomic stress-testing techniques, as surveyed
by Sorge (2004), are used to assess the vulnerability of
a
financial system to exceptional, but plausible, macroeconomic
shocks. These stress tests have become an important component
of the Financial Sector Assessment Programs (FSAPs) initiated
by the International Monetary Fund in the late 1990s
and conducted by national policymakers. There are two main
methodological approaches here. The piecewise approach
evaluates the vulnerability of the financial sector to
individual risk factors, such as nonperforming loan ratios,
by forecasting their behavior under various macroeconomic
stress scenarios. The integrated approach analyzes the
sensitivity of the financial system to multiple risk
factors
by generating a distribution of aggregate portfolio losses
that could occur under macroeconomic stress scenarios.
Hoggarth
et al. (2004) summarize the FSAP for the United Kingdom.
Their macroeconomic scenarios were derived using
the Bank of England's own macroeconometric model and
were supplied to ten large domestic banks as inputs to
their
own assessments. For example, one stress scenario was
based on the macroeconomic impact of a 35% decline in global
stock prices; another scenario was based on a 12% decline
in domestic real estate prices; the magnitudes for these
hypothetical macroeconomic scenarios were consistent
with
the range of historical estimates and broadly corresponded
to movements that tended to occur with less than a 1%
probability. FSAP provided UK policymakers with evidence
supporting
the stability of their banking system with respect to
a wide range of plausible adverse shocks. Conclusion
Stress testing is an appealing risk-management
tool because it provides risk managers with additional
information on
possible portfolio losses arising from extreme, although
plausible, scenarios. In addition, stress scenarios can
often be an effective communication tool within the firm
and to outside parties, such as supervisors and investors.
In fact, the U.S. banking firm JP Morgan Chase provided
internal stress-testing results in its 2003 and 2004
annual reports to investors. Hence, stress testing
may be increasingly
used by financial firms for both internal and external
purposes. Jose A. Lopez
Senior Economist References
[URLs accessed June 2005.]
Collier, C., S. Forbush, and D.A. Nuxoll. 2003. "Evaluating
the Vulnerability of Banks and Thrifts to a Real Estate Crisis." FDIC
Banking Review 15 (fourth quarter) pp. 19-36.
http://www.fdic.gov/bank/analytical/banking/2003dec/
Committee
on the Global Financial System. 2005. "Stress
Testing at Major Financial Institutions: Survey Results
and Practice." Working group report, Bank
for International Settlements.
http://www.bis.org/publ/cgfspubl.htm
Federal
Reserve System. 2003. Trading
and Capital-Markets Activities Manual.
http://www.federalreserve.gov/boarddocs/supmanual/default.htm#trading
Hoggarth,
G., A. Logan, and L. Zicchino. 2004. "Macro
Stress Tests of UK Banks." Manuscript, Bank
of England.
http://www.bis.org/publ/bppdf/bispap22t.pdf
Sierra,
G.E., and T.J. Yeager. 2004. "What Does the
Federal Reserve's Economic Value Model Tell Us about
Interest Rate Risk at U.S. Commercial Banks?" FRB
St. Louis Review 86 (November/December) pp. 45-60.
http://research.stlouisfed.org/publications/review/04/11/SierraYeager.pdf
Sorge,
M. 2004. "Stress-Testing
Financial Systems: An Overview of Current Methodologies." Working
paper no. 165, Monetary and Economic Department,
Bank for International Settlements.
http://www.bis.org/publ/work165.htm
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