For release on December 10, 1996
1996 Twenty-Fourth Annual National Conference on
Current SEC Developments
December 10, 1996
Remarks by
Robert C. Lipe
Academic Fellow
Current Accounting Projects
Office of the Chief Accountant
U.S. Securities and Exchange Commission
As a matter of policy, the Securities and Exchange
Commission disclaims responsibility for any private
publications or statements by any of its employees. The
views expressed are those of the author, and do not
necessarily represent the views of the Commission or the
author's colleagues on the staff.
Welcome, to the AICPA conference on current SEC
developments. I am honored to speak here today.
My topic for today is to discuss how to determine whether
hedge accounting is appropriate when initially entering into
a futures contract. First, I will provide a little
background on the topic. Second, I will discuss two
criteria for determining if hedge accounting is appropriate
at inception. Loosely speaking, the criteria are economic
sensibility and evidence from prior years. And finally,
throughout my remarks I will refer to how the issues I am
discussing today played an important role in a registrant
matter at the SEC.
The accounting for buying or selling a futures contract as a
hedge is covered in Statement of Financial Accounting
Standards No. 80, "Accounting for Futures Contracts," as
well as in a recent FASB exposure draft, "Accounting for
Derivative and Similar Financial Instruments and for Hedging
Activities." As Russell Mallett stated earlier in this
session, hedging as defined in SFAS 80 refers to a company
buying or selling a futures contract in order to reduce or
alter a specified risk that the company faces. This risk
can be a risk that market values may move in an unfavorable
direction. Or the risk can arise from unfavorable movements
in interest rates. If the company's usage of futures
contracts meets the criteria set forth in paragraph 4 of
SFAS 80, then the gain or loss on the futures contract is
deferred until the company recognizes its gain or loss on
the underlying asset or transaction. This practice of
offsetting the gains and losses is commonly referred to as
"hedge accounting."
As you may know, the FASB is reconsidering SFAS 80. If the
FASB goes ahead with the new exposure draft, then the rules
will change somewhat. The gains and losses on the futures
contracts would no longer be deferred. However, the
exposure draft will continue the practice of hedge
accounting by accelerating the recognition of the gains or
losses on the underlying. Thus both existing and proposed
accounting standards allow gains and losses on some futures
contracts to be offset against the gains and losses on the
underlying.
With this basic background, I would like to turn to my
specific topic for today. Under what conditions does being
party to a futures contract qualify for this special hedge
accounting treatment? It turned out that one of the first
registrant matters that I faced at the commission hinged on
just this question. Today I will try to provide some
guidance on how the staff addresses this question.
My remarks will focus on the importance of paragraph 4b of
SFAS 80 in determining if a futures contract should qualify
as a hedge. The paragraph requires that, at the inception
of the hedge, it must be probable that changes in the market
value of the futures contract will offset the changes in the
fair value the hedged item. In determining whether future
offset is probable, registrants should address two
questions. First, is there a clear economic relationship
between the prices of the hedged item and the futures
contract? Second, was there a high level of correlation
between these prices during the relevant past periods?
Paragraph 4b requires an evaluation of correlation and
offset both at inception and on an ongoing basis. Since
Russ provided excellent guidance regarding ongoing
assessments earlier in this session, I will focus on
applying these two criteria at the inception of a hedge.
Economic Sensibility
First let's focus on the economics. For hedge accounting to
apply, it must be economically sensible that some common
factor or factors will have opposite effects on the values
of the underlying and the futures contract. For example, if
you own 100 pounds of gold, you can hedge the risk
associated with that inventory by selling a futures contract
for 100 pounds of gold. If the price of gold goes up, the
value of the futures contract goes down. Thus, hedging an
inventory of gold with a futures contract on gold meets the
test of being economically sensible.
Many of the hedges found in practice are similar to this
plain vanilla transaction. However, for a variety of
reasons, registrants will sometimes use strategies that are
less straight forward. For example, they might try to hedge
their gold by selling a futures contract to buy copper.
Paragraph 4b of SFAS 80 mentions that hedge accounting may
be applied to these more complicated transactions. However,
there must be a clear economic relationship between the
underlying and the futures contract. For this to occur in
my example, the prices of gold and copper must move in
similar ways over time. In contrast, hedge accounting would
not be appropriate if the prices of gold and copper reflect
different economic factors.
This example of using copper futures contracts to hedge gold
is similar to the facts concerning the registrant matter
mentioned earlier. The registrant used a hedging instrument
that had some similarity to the underlying asset, but the
correspondence was not perfect. Thus the registrant faced
numerous questions from the staff regarding whether the
economics of this hedge made sense. We kept asking "Is a
high level of correlation among price changes probable?"
Without a convincing economic analysis, hedge accounting as
described in SFAS 80 would not be appropriate.
Evidence from Prior Years
The second criteria for judging correlation at the inception
of the hedge is evidence from past data. In addition to
considering whether the hedge is economically sensible, the
decision to use SFAS 80 also depends on demonstrating a high
level of correlation in past data. How does one do that?
Since a lot of my research involves analyzing accounting and
price data, let me tell you how I would approach it.
The first step is to collect data on past price changes for
the underlying asset and the futures contract. To
illustrate my points, some simulated data are presented in
figure 1 which is attached at the end of this speech.
Figure 1 contains two plots of data. On the vertical axis
in each graph is the return on the underlying asset. The
horizontal axis in panel A is the return on a specific
futures contract, labeled "contract A." The horizontal axis
in panel B is the return to a different hedging instrument,
labeled "futures contract B."
What patterns would we look for in these two plots to
determine whether historical returns on the futures contract
offset the historical returns from the underlying asset?
There should be a downward slope to the scatter plot. In
other words, large positive returns on the asset should be
associated with large negative returns on the hedging
instrument, and vice versa. Both graphs display a downward
slope. Which futures contract will be the better hedge, A
or B? Contract B should provide better offset because the
points on the graph are less dispersed. They are closer to
being on a straight line. Indeed, if contract B were a
perfect hedge, the points would form a straight line.
Looking at these scatter plots is fun, but it is difficult
to draw firm conclusions from just eye-balling the data. It
reminds me of a psychologist asking people what they see
when they look at an ink blot; everyone views them
differently. What you as preparers and auditors need is a
tool to summarize the information in these plots in a
simple, easy to understand manner. The most common tool in
use today is regression analysis.
Figure 2 summarizes the key information provided by a
regression program. It also contains the exact same plots
as figure 1, along with the fitted regression line. When
you run a regression, the program looks for the single
straight line that fits these plots the best. By best, I
mean that the program minimizes the average squared
difference between the data points and the fitted line.
Now remember that the whole purpose of the regression is to
assess the level of correlation between the futures contract
and the underlying asset. Figure 2 contains two measures of
correlation, one is the R2 and the other is the correlation
coefficient. I want to first focus on R2 . For contract A,
R2 is 63%. For contract B, it is 94%. Recall from the
scatter plots that contract B looked like a better hedge.
The regression analysis confirms this because the R2 is
higher for futures contract B. For those of you who are not
familiar with R2, the statistic can be as low as 0% and as
high as 100%. An R2 equal to 0% means that the changes in
the value of the futures contract are unrelated to the
underlying asset. An R2 of 100% implies a perfect
correlation, which would translate into all of the points in
our scatter plot lying on a straight line.
What does the R2 of 63% for contract A tell us? In
essence, it means that 63% of the historical returns to the
underlying asset could have been offset by this futures
contract. Certainly, 63% is not a small number, but it is
important to realize that 63% is less than 100%. Indeed,
37% of the change in value of the underlying cannot be
offset by a hedge using contract A. Thus if past macro-
economic factors are essentially repeated in the future, at
best, contract A can only offset 63% of the gain or loss on
the underlying. That does not seem like a sufficiently high
level of offset to justify hedge accounting.
What is the magic level of R2 which would allow registrants
to apply SFAS 80? I do not want to draw a bright line.
Correlation at inception is a judgment call based on more
than just this single number. Some CPA firms use a minimum
R2 of 80% as guidance, and staff has no objection to that
guidance. In cases where the R2 is less than 80%, so that
more than 20% of value changes are unlikely to offset, I
think staff may question whether hedge accounting is the
right answer.
That concludes my analysis of the R2 statistic. What about
the other regression results? Are they useful? The answer
is yes, but it is difficult for me to describe how they
would be used in my limited amount of time. So I will
simply give you the highlights.
The correlation coefficient you see in figure 2 is another
measure of correlation. Note that R2 equals the correlation
coefficient squared. In other words, looking at panel A, if
you square the correlation coefficient of -.79, the result
is .63, which by definition will equal the R2 of 63%. So in
order to have an R2 of at least 80%, the correlation
coefficient would have to be somewhere between -1.0 and -.9.
The other output consists of the slope coefficient and the
intercept. I used these to draw the line on the scatter
plot. To a registrant, the slope coefficient will help
determine how many futures contracts must be purchased in
order to offset the risk of the underlying asset. If you
want more information about this, you can ask me later or
call me in the office.
Conclusion
I will close with an epilogue of what happened in the
registrant case I mentioned before. The registrant's
historical analysis showed a correlation coefficient of
-.77. But a correlation coefficient of -.77 implies an R2
of only 59%. This seemed low to the staff, and we were
concerned whether the transaction met the criteria in
paragraph 4b of SFAS 80. Sure enough, as Russ described
earlier, this particular hedging transaction ultimately fell
a part. The gains and losses on the futures contract did
not offset the gains and losses on the underlying asset.
The staff concluded that these futures contracts did not
meet the criteria specified in SFAS 80.
Thank you for your attention. Hopefully these remarks will
help you or your co-workers or your clients to better assess
whether hedge accounting is appropriate at the inception of
the transaction.
[figures 1 & 2 omitted from electronic copy]
Regression output:
Contract A:
R-square = 63%. Correlation coefficient = -.794. Slope
= -.671. Intercept = -.04.
Contract B:
R-square = 94%. Correlation coefficient = -.968. Slope
= -.959. Intercept = -.01.