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Stress testing is a
simple form of scenario
analysis. Rather than consider the evolution of risk factors over
several time steps, stress testing considers changes in risk factors over
a single time step. That horizon is usually a single trading day, but
stress testing can be considered over longer horizons—a week, two weeks, a
quarter or even a year. Usually, stress testing is used to assess
market risk, and that is the
application this article focuses on. However, any scenario analysis that
employs a single time step may be referred to as a stress test.
Used for market risk, a single scenario consists of
projected values for applicable risk factors at the end of the horizon.
Based on these values, a portfolio is
marked-to-market. The result is compared with the portfolio's current
market value, and the portfolio
loss is calculated as the difference between the two.
Scenarios can be constructed in an ad hoc manner. If
management is concerned about the effect of an inverted
yield curve or a
breakdown in a specific correlation,
a scenario can be constructed specifically to assess that eventuality.
Stress testing can also be systematized. A firm may specify certain fixed
scenarios (defined in terms of percent changes in applicable risk factors)
and then perform periodic stress testing with those scenarios. In this
manner, a firm might present stress test results in its daily risk report.
Such stress scenarios may be hypothetical, perhaps reflecting
contingencies that are a recurring concern of management. They can also be
historically based. With that approach, stress scenarios may reflect the
percentage changes in risk factors experienced during selected historical
periods of market turmoil—stock market crashes, currency devaluations,
etc.
Stress testing has much in common with
value-at-risk (VaR). Both
assess market risk. Both consider the change in market risk over a fixed
horizon due to changes in specific risk factors. Indeed, if stress testing
is conducted with randomly generated scenarios, the analysis would not be
called stress testing. It would be called a
Monte Carlo VaR
measure.
There is some misunderstanding about the purpose of stress
testing. This can be traced to the early literature on VaR from the
mid-1990s. Like any tool, VaR has limitations, and those limitations were
significant with many of the crude VaR implementations of the day. In
light of those limitations, it became customary to recommend stress
testing as a supplement to VaR. The phrase "VaR should always be
supplemented with stress testing" is familiar to practitioners who worked
in financial risk management
during that period. Actually, the advice was dubious. No one ever
identified how stress testing addressed the limitations of VaR measures of
the day. For the most part, it didn't.
There was a perception that stress testing allowed for the
analysis of extreme events that VaR didn't address. For example, if a
firms was using one-day 90% USD
VaR, results would reflect losses that might be experienced one day out of
ten. What about losses that might be experienced one day out of 100—or one
day out of 1000? On the surface, stress testing, with its ability to
assess arbitrarily extreme events, seemed well suited to answer such
questions. It was not. Although, stress testing can be used to assess
losses under any scenario, it associates no probabilities with those
scenarios. If stress testing indicates that a firm will lose a billion
dollars under one extreme scenario, it is difficult to make sense out of
the result. Is that a scenario that will occur once every thousand days or
once every thousand years? Given an extreme enough scenario, it is
possible to predict ruin for any portfolio.
Used as a supplement to VaR, stress testing is primarily
useful for offering an intuitive sense of what sorts of scenarios are
causing the VaR to be what it is. In this way, it can be a nice supplement
for VaR.
The one significant shortcoming of VaR that stress testing
does address is sudden changes in historical correlations. If two
currencies have been pegged to one another, they will exhibit a high
historical correlation. A VaR analysis based on that historical
correlation will not address the risk that one of the currencies may be
devalued relative to the other. If this is a scenario that concerns
management, a simple stress test will offer more insights than would, say,
a VaR analysis performed with a modified correlation assumption.
In summary, stress testing can be a nice supplement for
VaR analyses, and many firms use it for that purpose. For assessing the
risk of a breakdown in historical correlations, stress testing can be
valuable. Other than that, as a tool for addressing vaguely defined
limitations of a VaR measure, stress testing is largely a placebo.
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