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Risk and (Ornplian C
On( e banks began hi face truly volatile foreign
ex hange markets, suddenly the halanr e sheet
became inadequate as a communication tool, and
controls on the balance sheet missed an important
potential source of loss,,.
Best Practices in Risk Measurement: Why Increasing
Derivatives Activity Caused Banks to Turn to Value at Risk
by Michelle McCarthy, Risk Product Managei IQ Financial Systems, Inc.
STAGE 1: BAI.ANCE SHEET CONTROLS
It was easier in the 60s. When the Bretton Woods
agreement was still in effect, when accountancy for banks
was dominated by accrual rather than mark-to-market
accounting, and when the only derivatives in existence
were traded by speculators and commodities firms, bank
management was simpler. Without foreign exchange risk,
duratan rk, or dervati-,e product risk, a balance $heet
was a very effective mechanism for communicating the
risks a bank faced to management within the firm, and to
investors and analysts outside the firm. Controls on the
principal size of on-balance sheet assets controlled risk
effectively. With the addition of gap reporting, banks could
easily grasp and control their risks. Balance sheet
exposures could be easily attributed back to the business
groups that generated them, in order to measure those
groups’ return on capital.
However, once banks began to face truly volatile foreign
exchange markets, suddenly the balance sheet became
inadequate as a communication tool, and controls on the
balance sheet missed an important potential source of loss.
In addition, when banks began to cease holding assets to
maturity, making them available for sale, they faced losses
based on interest rate fluctuations. Once again, the balance
sheet is a poor vehicle for expressing this risk it treats a
one-year maturity asset identically to a 30-year maturity
asset, even though the latter asset subjects its holder to
much greater interest rate risk if it is sold before maturity.
Finally, once banks began entering into interest rate and
currency swaps and options in the 1980s, they were posed
with another category of instrument which disappears from
a balance sheet, yet poses real risk of loss.
STAGE 2: EXPOSURE CONTROLS
In the late 70s, managers at banks began to report and limit
exposures to interest rate and foreign exchange risk.
Without proper controls on these items, business people in
these firms would have very poor incentives — the so-called
‘free option on wealth.’ The larger the foreign exchange or
interest rate risk positions they took, the greater thcii
institution’s opportunity for gain or loss. If they were
compensated based on profits, they faced an asymmetric
return: great financial gain if their position gained. hut
limited personal losses if the institution suffered a
significant loss. The incentives were there to create very
large positions if these were not controlled. Bank managers
did not fail to note this, and took steps to manage it cn
reporting and limiting the exposures taken.
Exposures (also known as sensitivities or positions)
describe how long or short the institution is various ke
segments of the market, usually by measuring how much a
portfolio gains or loses for a small change in the price or
rate of that market segment. Interest rates are normally
shifted by one basis point, foreign exchange rates by one per
cent, and all transactions repriced under such a change.
Exposure measurement provides an elegant way to get a
picture of what disappears from the balance sheet
particularly, for instrtiments which cost no cash upfront, but
have the ability to generate a loss if rates or prices change.
It is not easy, however, to judge whether a busines
group’s profitability justifies its exposures, the same way
one might judge whether their profitability justifies their
balance sheet usage; the figures are not comparable. And
setting limits on exposures can be both insufficient and too
complex to control the risks of certain types of portfolios.
Multi-asset class portfolios, arbitrage portfolios, and
hedged derivative portfolios cannot be controlled through
exposure measurement alone.
Multi asset class portfolios
Let’s posit two hypothetical portfolios, traded by tw
hypothetical New Zealand portfolio managers, employed by
the same bank. One trades the bonds of Australia and the
UK. dabbles in convertible bonds and equities from these
countries as well, and keeps open foreign exchange
positions. The other trades the money market instruments of
Mexico and Argentina, and and also keeps some open
foreign exchange and equity positions in these countries. It
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2. INFORMA1K)N TF( HN(i[(3(Y
manager would have a difficult time determining who had
pros Ided the best return on equity, as not all of these
s are on the balance sheet, And even computing
equity for the on-balance sheet portions would he
should not the riskier Mexican and Argentinian
posiu require a higher return. een if their current value
is the same?
Arbitrage portfolios
When portfolio managers deliberately take low risk
positions, buying one asset and selling another that is sery
5imlar, what should be the constraint on the strategy? I low
inager detei mine whether going long 100 million of
Id short 100 million ofasset b is riskier or less risky
other arbitrage strategy. in which the portfolio
manager buss 1 billion of asset x and sells I billion of asset
v Clearly, the less correl:ied ihe two assets in the pair, the
riskier the strategy hut exposure measurements include no
information about correlation.
Hedged derivative portfolios
Swaps traders ordinarily enter into swaps, then sell or buy
duration weighted money market instruments or bonds to
extinguish their risk. They may buy these at different points
of the yield curve; they may rely more heavily on
government bonds rather than money market instruments,
When they do this, they take risks that are difficult to assess
just by conducting exposure measurement. Their managers
might make use of a grid like this one to assess whether
their risks are excessive. See table 1 above.
The rules that would be required to control the mix of
curse, spread and outright duration risks in a swap book
like this could be very complex and yet not necessarily
sufficient. For example, we might make a rule that. for this
particular currency. (I) total sensitivity to a one basis point
move could not be greater than 500 overall, and (2) that
sensitivity to the first third of the yield curse could not
differ from the second third of the yield curve by more than
30 per cent, while the difference between the sensitivity of
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“one: 44171 549 1000
.Jte: www.iqfincincial.com
IQ Financial Systems, Inc. is an international provider of software and
services to financial institutions, As a spin-off of Bankers Trust, it draws
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Risk and Compliance
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FINANCIAL SYSTEMS

3. Pd I tNt (iRMAI ION 1 F( FIN()I OCY
Risk and Compliance
the second third and the third third could not exceed 25 per
cent. and 13) that government interest rate risk could not
account for more than 40 per cent of total sensitivity.
Without obser ing the historical correlation of these
sectors, and their volatility, to measure how much loss
could be sustained through duration, curve and spread
changes. it would be hard to assess whether this long-
winded rule controls risk appropriately, excessively, or not
at all. And once we have gone to the trouble of conducting
a volatility and correlation analysis, we have done almost
all the work required for a measurement and control system
that is at once more simple and more capable Value at
Risk, or VaR.
STAGE 3: VALUE AT RISK CONTROLS
In the mid- to late I 980s, a few banks began to put in place
VaR measures and controls. ‘1 hcs included Bankers Trust
and Citibank; US commercial banks were keen to
demonstrate appropriate risk controls as they began to run
large deriatives operations. In the late 70s Bankers Trust
There are a variety of VaR models. Some, such as
the Monte Carlo simulation and historical
simulation models, are better for portfolios
containing options (including convertibles and
mortgages) and convex interest rate instruments
had begun to assess the potential loss of its lending book,
and to attribute capital to these lending activities in order to
better measure return on equity: the extension of this
philosophy to market risks was a natural one.
Under VaR measurement, banks use systems that
assemble their exposures to hundreds, or even thousands of
key risk factors, such as foreign exchange rates, interest
rates, equity and commodity prices. These exposures come
from their on- as well as off-balance sheet instruments.
Their systems store historical information about these risk
factors, to show how volatile their price of yield movements
have been historically, and how highly correlated they have
been to the other factors.
VaR models all run a bank’s current exposures in one
fashion or another in order to determine what kind of worst-
case losses these exposures could have generated had they
been held in the past. This measure provides a number
benefits. Instead of trying to place limits on many single
types of assets, as was shown in the examples above, a VaR
system instead limits how much loss they are capable of
generating together — a single, simpler figure. Further, a
portfolio’s potential loss can be thought of as the amount of
capital which is supporting that portfolio, allowing for
return on capital calculation for that activity.
Because of the regulatory requirements in GlO
countries, banks in these countries commonly measure the
potential losses of their market risks if these risks were held
for two weeks, and the 99 per cent worst case two-week
period occurred.
There are a variety of’ VaR models. Some, such as th
Monte Carlo simulation and historical simulation model’
are better for portfolios containing options (includin
convertibles and mortgages) and convex interest rate
instruments. For portfolios with significant positions in
emerging or illiquid markets, many prefer the historical
simulation method as it better represents the higher
incidence of extreme price changes in these models than do
parametric methods.
Beyond Value at Risk: a suitable risk framework
VaR provides an excellent way to communicate. compar.
and limit risks in a hank, and to view returns in light of thu
risks taken to earn them, It is superior to relying on
balance sheets or exposures alone to limit risk-taking — but
it is not perfect. Firstly, because VaR relies on historical
data to estimate risk, it will be inaccurate when the future
does not much resemble history. Secondly. if banks take
very large risk positions, larger than the standard trading
volume in the market, VaR will underestimate risk
Thirdly, it does not adjust for the chance that an individur
holding might not behave like a broad market risk factor
ie. that there can be losses on single issues which are not
market wide. This type of risk is classic credit risk, or
specific equity risk.
Good risk frameworks contain a number of elements:
VaR & Exposure Limits: Limits on the VaR of portfolios,
as well as on selected exposures
• Stress Testing: Conducting scenario analysis — ignoring
the historically-based VaR analysis, and instea’
subjecting their an institution’s portfolio to hypothetici
market shocks (or replays of well-known historical ones
to see whether they are overexposed to shocks that they
believe to be possible
• Liquidity and Credit Limits: Constraining position size
across many assets, to ensure that they are not
overconcentrated in credit or market risks, helping to
avoid unexpected and destabilizing loss from individual
issuers or being too large for the marketplace
• Backtesting the VaR model: Predicting tomorrow’s 9(
per cent confidence potential loss using the VaR modei
then comparing it the next day to the actual mark-to
market of the portfolio. Ifthe model is a good one, 99 per
cent of the time losses will be less than were predicted.
However, one per cent of the time, losses will exceed this
number — and they may do it in grand style
Where VaR models have let institutions down, one of these
steps has usually not been followed. VaR is not an ironclad
prediction of potential future loss, but it is an excellent use
of historical information blended with portfolh
information, in limiting and rewarding risk-taking. m
Forfurther information, contact:
IQ Financial Si’stems
Tel: 44-] 71-549-1000
Web: www iq.financial. corn
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