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Risk limits (or simply
limits) are a device for authorizing specific
forms of risk taking. A pension fund hires an
outside investment manager to invest some of its assets in
corporate bonds. The fund
wants the manager to take risk on its behalf, but it has a specific form
of risk in mind. It doesn’t want the manager investing in equities,
precious metals, or pork belly
futures. It communicates its intentions
with investment guidelines. These specify acceptable investments. They
also specify risk limits, such as requirements that:
the portfolio’s
duration always be less than 7 years;
all
bonds have a credit rating of triple-B or better.
The first is an example of a
market risk limit; the second of a
credit
risk limit.
When an organization authorizes a risk limit for risk-taking
activities, it must specify three things:
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a
risk metric,
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a
risk measure
for calculating the value of the risk metric on an ongoing basis, and
-
a value for the risk metric that is not to be exceeded.
At any point in time, a limit’s utilization
is the actual amount of risk being taken, as quantified by the risk
measure. Any instance where utilization exceeds the risk limit is called a
limit violation.
Suppose a bank’s corporate lending department is authorized to lend to a
specific counterparty subject to a
credit exposure
limit of GBP 10MM.
For this purpose, the bank measures credit exposure as the sum amount of
outstanding loans and loan commitments to the counterparty. The lending
department lends the counterparty GBP 8MM, causing its utilization of the
limit to be GBP 8MM. Since the limit is GBP 10MM, the lending department
has remaining authority to lend up to GBP 2MM to the counterparty.
A metals trading firm authorizes a trader to take gold price risk
subject to a 2000 troy ounce
delta limit. Using a specified measure of delta, his portfolio’s delta
is calculated at 4:30 PM each trading day. Utilization is calculated as
the absolute value of the portfolio’s delta.
For managing credit risk, a firm will generally set an exposure credit
limit for each counterparty to which it has credit exposure. This is
standard procedure in many contexts. It could be a bank making corporate
loans, a derivative dealer transacting with counterparties, a company
extending trade credit to customers or a credit card company providing
credit to cardholders. All entail credit risk. All are contexts where
credit exposure limits are used.
A firm may also use aggregate credit exposure limits. A bank might set
credit exposure limits by industry. It might also set a total exposure
credit limit for all its corporate lending activities.
For monitoring market risk, many organizations segment portfolios in
some manner. They may do so by trader and trading desk. Commodities
trading firms may do so by delivery point and geographic region. A
hierarchy of market risk limits is typically specified to parallel such
segmentation with each segment of the portfolio having its own limits.
Limits generally increase in size as you move up the hierarchy—from
traders to desks to the overall portfolio or from individual delivery
points to geographic regions to the overall portfolio.
Exhibit 1 illustrates how a hierarchy of market risk limits might be
implemented for a trading unit. A risk metric is selected, and risk limits
are specified based upon this. Each limit is depicted with a cylinder. The
height of the cylinder corresponds to the size of the limit. The trading
unit has three trading desks, each with its own limit. There are also
limits for individual traders, but only those for trading desk A are
shown. The extent to which each cylinder is shaded green corresponds to
the utilization of that limit. Trader A3 is utilizing much of his limit.
Trader A4 is utilizing little of hers.
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A typical system of market risk limits is
depicted. Each limit is indicated with a cylinder. The height of the
cylinder corresponds to the size of the limit. The trading unit has
three trading desks, each with its own limit. There are also limits
for individual traders, but only those for trading desk A are shown.
The extent to which each cylinder is shaded green corresponds to the
utilization of that limit. |
For such a hierarchy of risk limits to work, an organization must have
a suitable risk measure to calculate utilization of each risk limit on an
ongoing basis. Below, we describe three types of market risk limits,
culminating with VaR limits.
A stop-loss limit indicates an
amount of money that a portfolio’s single-period market loss should not
exceed. Various periods may be used, and sometimes multiple stop-loss
limits are specified for different periods. A trader might be given the
following stop-loss limits:
1-day EUR 0.5MM,
1-week EUR 1.0MM,
1-month EUR 3.0MM.
A limit violation occurs whenever a portfolio’s single-period market
loss exceeds a stop-loss limit. In such an event, a trader is usually
required to unwind or otherwise
hedge material
exposures—hence the name stop-loss limit.
Stop-loss limits have shortcomings. Single-period market loss is a
retrospective risk metric. It only indicates risk after the financial
consequences of that risk have been realized. Also, it provides an
inconsistent indication of risk. If a portfolio suffers a large loss over
a given period, this is a clear indication of risk. If the portfolio does
not suffer a large loss, this does not indicate an absence of risk!
Another problem is that traders cannot control the specific losses they
incur, so it is difficult to hold traders accountable for isolated
stop-loss limit violations. However, the existence of stop-loss limits
does motivate traders to manage portfolios in such a manner as to avoid
limit violations.
Despite their shortcomings, stop-loss limits are simple and convenient
to use. Non-specialists easily understand stop-loss limits. A single risk
metric can be applied consistently across an entire hierarchy of limits.
Calculating utilization is as simple as marking a portfolio to market.
Finally, because portfolio loss encompasses all sources of market risk,
just one or a handful of limits is required for each portfolio or
sub-portfolio. For these reasons, stop-loss limits are widely implemented
by trading organizations.
Exposure limits are limits based
upon an exposure risk metric. For limiting market risk, common metrics
include: duration, convexity, delta,
gamma, and
vega. Crude exposure limits may also be
based upon notional amounts.
These are called notional limits.
Many exposure metrics can take on positive or negative values, so
utilization may be defined as the absolute value of exposure.
Exposure limits address many of the shortcomings of stop-loss limits.
They are prospective. Exposure limits indicate risk before its financial
consequences are realized. Also, exposure metrics provide a reasonably
consistent indication of risk. For the most part, traders can be held
accountable for exposure limit violations because they largely control
their portfolio’s exposures. There are rare exceptions. A sudden market
rise may cause a positive-gamma portfolio’s delta to increase, resulting
in an unintended delta limit violation.
For the most part, utilization of exposure limits is easy to calculate.
There may be analytic formulas for certain exposure metrics. At worst, a
portfolio must be evaluated under multiple market scenarios with some form
of interpolation applied to assess exposure.
Exposure limits pose a number of problems. A hierarchy of exposure
limits will depend upon numerous risk metrics. Not only is delta different
from gamma, but crude oil delta is different from natural gas delta.
Because a portfolio or sub-portfolio can have multiple exposures, it will
require multiple exposure limits. An
equity derivatives trader might have
delta, gamma, and vega limits for each of 1000 equities—for a total of
3000 exposure limits.
Exposure limits are ineffective in contexts where
spread trading,
cross-hedging, or similar strategies minimize risk by taking offsetting
positions in correlated assets. Large exposure limits are required in
order to accommodate each of the offsetting positions. Because they cannot
ensure reasonable hedging, the exposure limits allow for net risk far in
excess of that required by the intended hedging strategy.
With the exception of notional limits, non-specialists do not easily
understand exposure limits. It is difficult to know what might be a
reasonable delta limit for an electricity trading desk if you don’t have
both:
a technical understanding of what delta means, and
practical familiarity with the typical size of market fluctuations
in the electricity market.
This, and the sheer number of exposure limits that are often required,
makes it difficult for managers to establish effective hierarchies of
exposure limits.
Value-at-risk (VaR) limits combine many of the
advantages of exposure limits and stop-loss limits.
Like exposure metrics,
VaR
metrics are prospective. They indicate risk before its economic
consequences are realized. Also like exposure metrics, VaR metrics provide
a reasonably consistent indication of risk. Finally, as long as
utilization is calculated for traders in a timely and ongoing manner, it
is reasonable to hold them accountable for limit violations. As with
exposure limits, there are rare exceptions. Consider a trader with a
negative gamma position. While she is responsible for hedging the position
on an ongoing basis, it is possible that a sudden move in the underlier
will cause an unanticipated spike in VaR.
As with stop-loss limits, non-specialists intuitively understand VaR
metrics. If a portfolio has 1-day 90% USD VaR of 7.5MM, a non-specialist
understands that such a portfolio will lose less than USD 7.5MM an average
of 9 days out of 10.
With VaR limits, a single metric, such as 1-day 99% USD VaR, can be
applied consistently across an entire hierarchy of limits. In theory, VaR
encompasses all sources of market risk. Just one limit is required for
each portfolio or sub-portfolio.
VaR aggregates across assets. Depending upon the sophistication of a
VaR measure, it can reflect even the most
complex hedging or
diversification effects. Accordingly, VaR limits are perfect for
limiting risk with spread trading, cross-hedging, or similar trading
strategies.
VaR limits have one significant drawback: utilization may be
computationally expensive to calculate. For many portfolios, VaR is easy
to calculate. It can often be done in real time on a single processor. For
other portfolios, it may take minutes or hours to calculate, even with
parallel processors.
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