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subject: A Regressive Approach To Hedge Accounting At Novelis [print this page]

A Regressive Approach to Hedge Accounting at Novelis

One of the more important decisions to be made during the life of a hedge is how to

assess its effectiveness. Both ASC 815 (FAS 133) and IAS 39 require companies to

assess hedge effectiveness at the inception of the relationship and on a periodic basis

throughout its life. This requirement includes a forward-looking prospective assessment and a

backward-looking retrospective assessment. Choosing the right method is important because

if your test results fail to meet the criteria you establish for them, you must discontinue hedge

accounting for that hedge and changes in fair value must be recognised in earnings.

Moreover, once you have selected a method, you cannot change it without de-designating

the hedge relationship.

Companies may elect to forgo periodic

effectiveness testing by asserting that the

critical terms of the exposure match those of

the derivative. The problem with this method

is that auditors and regulators have taken a

very narrow definition of the term "match'. A

payment date that is different by as little as

one day may make the critical terms match

method inappropriate. Many companies have

been burned by using critical terms match and

then being told by their auditors or the SEC

that the method was inappropriate. This has

led to more than a few financial restatements.

Given the risks of the critical terms match,

many companies now use the dollar offset

method as their default method for assessing

hedge effectiveness. The popularity of this

method arises from its ease of use. The

change in the value of the derivative is

compared to the change in the value of the

hedged item. If the ratio of the two changes

lies within a predetermined range - say 80%

to 125% - the hedge may be deemed to be

highly effective.

Small changes, big problems

The risk of the dollar offset method is that a

seemingly good hedge can fail this test without

warning, especially if markets are relatively

stable. Assume you have $500m in variablerate

debt, hedged with an interest rate swap. If

the derivative changes in value by $15,000 and

the hedged item changes by $10,000, the

hedge will fail because the ratio of the two

changes falls outside of the 80-125 range. It

does not matter that both changes are small

relative to the notional amount. This can be

frustrating when you know that most of the

time, the hedge would have been effective, but

dollar offset is not a "most of the time' method

of testing.

Companies not wanting to bear the risks

associated with critical terms match or the

dollar offset method are increasingly turning to

regression analysis to assess hedge

effectiveness. Regression analysis is a

statistical method where changes in the

derivative and changes in the hedged item are

measured at regular intervals over time and a

line is mathematically drawn through the

measurements. The slope of that line is an

important output; it represents the overall ratio

of derivative to hedged item. It is like doing a

series of dollar offset tests and then averaging

the results. Therefore, a few measurements may

fall outside the range without causing the

overall hedge relationship to fail. Regression

analysis is also useful when there is basis

difference between the derivative and the

exposure, as is often the case with commodity

hedges.

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Regression analysis, however, is more

complicated than dollar offset and can be

confusing to set up. You must specify the

number of samples to be used, the sampling

frequency, whether measurements will be made

on a periodic or cumulative basis, and what

range of slope values will constitute a highly

effective hedge. Because regression analysis is

a statistical technique, it is also important to

assess how strongly the data support the

conclusion and whether or not the results could

merely be the effect of random chance. For

this, you must specify limits for R-squared and

either the F-statistic or T-statistic. While it is

possible to perform these calculations in a

spreadsheet, if you have more than one or two

hedges, it may be a good idea to find a system

to maintain the underlying data and to perform

the mathematical heavy lifting.

Practical application

As the largest supplier of flat-rolled

aluminium products and the largest recycler of

used beverage cans in the world, Novelis has

significant exposures to commodity and

energy prices, exchange rates and interest

rates. We manage these exposures through

an active programme of derivative

transactions. Given that the notional value of

these programmes is greater than 50% of

annual revenue, it is critical that we account

for them properly.

Novelis has used Reval since 2005.

Initially, we used the system to support

hedge accounting for our interest rate swaps

and long-term energy contracts. In 2008, as

a part of our adoption of FAS 157, we

expanded our use of Reval to include the

valuation of more than 10,000 metal and

exchange rate derivatives, which we account

for as economic hedges at fair value through

profit and loss.

Novelis has two credit facilities of almost

$2bn (US), which are priced at LIBOR plus a

spread. Under these facilities, we have the

option to reset the interest rate calculation

basis from 1-month to 3-month LIBOR. That

means that on a given day each month, we

may elect to set the rate for the following

month at that day's 1-month LIBOR rate.

Alternatively, at quarter end, we may elect

to lock the rate in at 3-month LIBOR for the

following quarter, after which time we

would again choose either a 1-month or 3-

month reset period. At each reset date, we

consider the spreads and take an active view

on whether a 1-month or 3-month reset

would be most economic.

Despite the flexibility in this arrangement,

we wanted to further reduce our exposure to

interest rate fluctuations and so elected to

swap the majority of our debt to fixed rate

using interest rate swaps with a variable leg

that reset against 3-month LIBOR on a

quarterly basis. Assessing hedge

effectiveness in this case is not

straightforward. Although the LIBOR rates of

the loan and the swap generally track each

other, they are not linked; moreover, the

spread also changes and could even reverse

in certain market conditions. To counter this,

we conduct our effectiveness testing on the

assumption that, if our only option was to

base our interest rate exposure on 3-month

LIBOR, the hedge would be more effective

than if we could only re-price our debt

monthly using 1-month LIBOR. We therefore

set up our hedge relationship to compare a

quarterly interest rate swap with a term

borrowing with monthly resets, and apply

regression analysis to establish the changes

in the relationship over a period of time.

Reval has made the process of using

regression analysis relatively easy. When we

set up the hedge designation, we select

regression analysis for both prospective and

retrospective testing and specify the number

of measurements and their frequency - in our

case, we chose 36 months. We also

establish limits for slope (80% to 125%), Rsquare

(at least 80%), and the F-statistic and

T-statistic appropriate for our sample size

and our desired 95% confidence level. To

perform our initial prospective assessment,

Reval creates proxy trades for the derivative

and the exposure. These will be backdated

by 37 months and their valuations will be

measured at monthly intervals using historic

market data. The system generates the

regression results which it then compares to

the limits we established; this determines

whether the hedge passes or fails.

We use regression analysis as a dualpurpose

test, combining prospective and

retrospective testing into a single process.

Each month, the system replaces the oldest

backdated values with current values and

regenerates the results. We can see at a

glance, whether or not each hedge is

effective and we can identify any hedges

that may be at risk of failing in the future.

This is a highly efficient process.

Using regression analysis will not

guarantee that our hedges will always be

effective, nor can it make a bad hedge look

good, but we believe it reduces the risk of

false failure inherent with the dollar offset

method. From Novelis' standpoint, the fact

that Reval supports regression analysis and

allows us to have a highly efficient closing

process is a double-win. As we consider

applying hedge accounting to our metal and

foreign exchange derivatives, we expect that

we will continue to use regression analysis

for effectiveness testing.

by: Reval

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