Are Interest Rate Swaps Used to Manage Banks’ Earnings?

This is the html version of the file http://accounting-net.actg.uic.edu/Department/Songpaper.pdf.
G o o g l e automatically generates html versions of documents as we crawl the web.
To link to or bookmark this page, use the following url:

http://www.google.com/search?q=cache:7mCiMqCRvucJ:accounting-net.actg.uic.edu/Department/Songpaper.pdf+FAS+133+%22Ineffectiveness+in+earnings%22&hl=en

Google is not affiliated with the authors of this page nor responsible for its content.

These search terms have been highlighted:

fas

133

ineffectiveness

in

earnings

Are Interest Rate Swaps Used to Manage Banks’ Earnings?

Chang Joon Song

Michigan State University

Eli Broad Graduate School of Management

Department of Accounting & Information Systems

N242 North Business Complex

East Lansing, MI 48824-1122

(517) 432-3033

cjsong@msu.edu

January 2004

I am very grateful to my advisor, Thomas Linsmeier. I also thank the members of my

dissertation committee, Bruce Bettinghaus, Roger Calantone, and K. Ramesh. This paper also

benefited from comments from Jun-Koo Kang, Christian Mastilak, and seminar participants at

Michigan State University. The author is solely responsible for all remaining errors.

Abstract

Previous research has shown that loan loss provisions and security gains and losses are

used to manage banks’ net income. However, these income components are reported below

banks largest operating component, net interest income (NII). This study extends the literature by

examining whether banks exploit the accounting permitted under past and current hedge

accounting standards to manage NII by entering into interest rate swaps. Specifically, I

investigate whether banks enter into receive-fixed/pay-variable swaps to increase earnings when

unmanaged NII is below management’s target for NII. In addition, I investigate whether banks

enter into receive-variable/pay-fixed swaps to decrease earnings when unmanaged NII is above

management’s target for NII. Swaps-based earnings management is possible because past and

current hedge accounting standards allow receive-fixed/pay-variable swaps (receive-

variable/pay-fixed) to have known positive (negative) income effects in the first period of the

swap contract. However, entering into swaps for NII management is not costless, because such

swaps change the interest rate risk position throughout the swap period. Thus, I also examine

whether banks find it cost-beneficial to enter into offsetting swap positions in the next period to

mitigate interest rate risk caused by entering into earnings management swaps in the current

period. Using 546 bank-year observations from 1995 to 2002, I find that swaps are used to

manage NII. However, I do not find evidence that banks immediately enter into offsetting swap

positions in the next period. In sum, this research demonstrates that banks exploit the accounting

provided under past and current hedge accounting rules to manage NII. This NII management

opportunity will disappear if the FASB implements full fair value accounting for financial

instruments, as foreshadowed by FAS No. 133.

I. INTRODUCTION

This study examines whether interest rate swaps are used to manage bank holding

companies’ (hereafter, banks) earnings. Previous research has shown that loan loss provisions

(LLP) and security gains and losses (SGL) are used (1) to manage earnings and taxes, and (2) to

reduce regulatory costs (e.g., Moyer, 1990; Scholes et al., 1990; Warfield and Linsmeier, 1992;

Beatty et al., 1995; Collins et al, 1995; Ahmed et al., 1999; Beatty et al., 2002). As distinct from

previous studies, this study shows that net interest income (NII) can be managed by using

interest rate swaps (hereafter, swaps). The main difference between earnings management using

LLP and SGL and earnings management using swaps is where the managed earnings are

reported in the income statement. Swap transactions directly affect NII, the first primary subtotal

in banks’ income statements. In contrast, LLP and SGL directly affect net income, not NII.

NII is a significant portion of earnings in banks’ income statement. In 2002, NII is 3.5%

of total bank assets, while LLP and SGL are 0.68% and 0.1% of bank assets, respectively (see

Table 1 in Section II). In addition, Ryan (2002, p. 212) indicates that NII is the main source of

banks’ income. Despite the significance of NII, research has not investigated any methods that

bank managers may exploit to manage this largest component of earnings. Given the importance

of NII, the objective of this study is to examine whether banks manage NII by using interest rate

swaps.

Two pieces of anecdotal evidence suggest this may be the case. First, according to the

recent report by Baker Botts L.L.P (2003) to the Board of Directors of the Federal Home Loan

Mortgage Corporation (known as Freddie Mac), $420 million of operating earnings were

transferred from 2001 into subsequent years by entering into a series of swap transactions.

1

Freddie Mac deferred its earnings because realized NII far exceeded its expectations and it did

not want to inflate NII expectations in future periods.

Second, Partnoy (2003, p. 45) suggests in his book, Infectious Greed: How Deceit and

Risk Corrupted the Financial Markets that:

There were a few ugly stories about firms using swaps to manipulate their

accounting results. One bank contemplated internal swaps −swaps with itself−

whereby it would set aside reserves depending on how much profit it wanted to

declare in a particular quarter.

Swaps are private agreements between two parties to exchange cash flows in future

periods based on a predetermined formula (Hull, 1997). The most common type of interest rate

swap is the “plain vanilla” swap. Under this swap agreement, one party (e.g., Bank A) pays to the

other party (e.g., Bank B) cash flows equal to interest at a predetermined fixed rate on a notional

amount for a specified number of periods. At the same time, Bank A receives from the Bank B

cash flows equal to interest at a variable rate (e.g., LIBOR

, prime rate, etc.) on the same

notional amount for the same periods. In this example, the swap is a receive-variable/pay-fixed

swap (hereafter, RV swap) for Bank A, while the same swap is receive-fixed/pay variable swap

(hereafter, RF swap) for Bank B.

Swap valuation is based on the expected net cash flows between fixed and variable legs

of the swap. Suppose the interest yield curve is upward sloping (the most frequent case). This

implies that forward interest rates are expected to increase (see Section III for details). Therefore,

the variable rate payer’s (Bank B) future cash outflows from the variable leg of the swap are

expected to increase. Given these expected variable swap cash flows, to construct an at-the-

money swap Bank A and Bank B need to agree upon a fixed interest rate that makes the initial

1

The London Interbank Offered Rate (LIBOR) is the rate of interest offered by banks on deposits from other banks

in Eurocurrency markets (Hull, 1997). This rate has become a common variable rate swap index.

2

value of the swap zero. Since the current period interest rate is the lowest point on the upward-

sloping variable rate yield curve, the interest rate for the fixed leg of the swap must be set equal

to a higher value that equates the present value of expected cash flows to be exchanged between

Bank A and Bank B.

Due to this mechanism and assuming an upward-sloping yield curve, banks holding RF

swaps will receive positive cash inflows in the early periods of the swap. Similarly, banks

holding RV swaps will experience negative cash outflows in early swap periods. Moreover,

given the positive and negative cash flow effects from the swap’s initial period cash flows are set

by interest rates at the swap inception date, managers know the exact initial period cash flow

effect of swaps. If the accounting model reflects this economic effect in NII, managers can

exploit this opportunity to manage NII.

Past and current hedge accounting models permit reporting of the net cash flows from the

swaps as adjustments to reported interest revenue and expenses of hedged items. Thus, under

these hedge accounting models, the positive or negative cash flow effects in the early periods of

the swap generally are reflected in NII in income statements. However, there is an additional

issue in these hedge accounting models: recognition of any changes in fair values of hedging

swaps. Since managers do not have knowledge at swap inception as to the direction of future

interest rate changes, recognizing any unrealized fair value gains or losses on swaps due to

unexpected interest rate changes may counteract the earnings management effects of recognizing

the initial swap cash flows in NII. Then, managers would not be able to fully exploit this NII

management opportunity using swaps, resulting in a less attractive tool to manage earnings.

Under past and current hedge accounting standards, however, bank managers often can

directly manage NII without having to recognize any counteracting effects on net income. Prior

3

to Financial Accounting Standard Board Statement No. 133 (FAS No. 133), Accounting

Derivative Instruments and Hedging Activities,

interest rate swaps accounted for as hedges were

not recognized at fair value (Herz, 1994).

This hedge accounting model recognized only

periodic net cash settlements under the swap in NII. Thus, the concern about counteracting

earnings management effects by recognizing unrealized fair value gains or losses on swaps was

not an issue.

In contrast, swaps are required to be recognized at fair values in post-FAS No. 133

periods. However, this does not mitigate the NII management opportunity as long as the swap is

accounted for as a hedge because it is also required that corresponding hedged items’ gains or

losses be recognized in earnings.

Specifically, if a swap is designated as a fair value hedge,

changes in fair values of both swaps and hedged items are recognized in earnings. As long as a

fair value hedge is effective, gains (losses) on hedged items are offset by losses (gains) on swaps,

resulting in no counteracting effects on either NII or net income. If a swap is designated as a cash

flow hedge, gains or losses on the swap are recognized in other comprehensive income (OCI) not

net income. Thus, the recognition of unrealized gains or losses on swaps accounted for as cash

flow hedges also does not have any counteracting current period effect on NII (see Appendix for

details).

In sum, as long as the swap is accounted for as a hedge, the mandated fair value

recognition of swaps under FAS No. 133 generally does not eliminate the NII management

2

FAS No. 133 is amended by Financial Accounting Standard Board Statement No. 138 (FAS No. 138), Accounting

for Certain Derivative Instruments and Certain Hedging Activities-An Amendment of FASB Statement No. 133

and by Financial Accounting Standard Board Statement No. 149 (FAS No. 149), Amendment of Statement 133 on

Derivative Instruments and Hedging Activities.

3

The accounting guidance supporting this hedge accounting model was issued in Emerging Issue Task Force Issue

Nos. 84-7 and 84-36.

4

In order for managers to be able to treat earnings management swaps as hedges, the following two conditions must

be met: (1) prior to putting on the earnings management swaps, the hedge ratio is less than 1, and (2) appropriate

hedged items exist in interest earnings assets and liabilities to support hedge accounting treatment. I assume that

banks have ability to meet both conditions.

4

opportunity provided by recognizing periodic cash flow settlements in NII.

As a result, I

hypothesize that banks enter into RF swaps accounted for as hedges to manage NII upward if

unmanaged NII is expected to be below management’s target for NII. Similarly, I hypothesize

that banks enter into RV swaps accounted for as hedges if they want to transfer current earnings

into future periods because unmanaged NII exceeds management’s target for NII.

The decision to enter into swaps for NII management purposes, however, is not costless.

Entering into additional swaps to manage earnings is costly because such investments change

banks’ interest rate risk positions. Therefore, if maintaining risk management equilibrium is

crucial, banks may seek to mitigate quickly the additional interest rate risk by entering into

offsetting swap positions at the start of the next period. For example, if banks use RF swaps to

increase earnings, they may enter into RV swaps at the start of the next period to mitigate the

interest rate risk taken on by entering into the RF swaps this period. As long as earnings

management swaps and reversing swaps are well matched, the concern about the cost of using

swaps for earnings management can be somewhat mitigated.

However, banks may not necessarily enter into offsetting swap positions. Depending

upon interest rate changes in the initial period and the length of maturity of NII management

swaps, it may be difficult to enter into well-matched offsetting swaps in subsequent periods.

Therefore, instead of entering into offsetting swap positions immediately in the next period, bank

managers may observe both initial and subsequent periods’ interest rate changes and current

period earnings realizations before deciding whether or not to enter into offsetting swap positions.

I, therefore, also test whether or not risk management costs are significant enough to cause banks

5

When swaps are accounted for as trading instruments, bank managers are unable to manage earnings (either NII or

net income) by predetermined amounts by entering into swap contracts. Trading swaps’ unrealized gains or losses,

after adjustment for net of periodic net cash settlements, are recognized in earnings. Since these net effects are

reported outside NII, there is no NII management opportunity. In addition, due to the uncertainty about future

interest rate changes at swap inception, the net effect on net income is unknown (see Appendix for details).

5

entering into earnings management swaps to generally enter into opposite swap positions early in

the subsequent period.

Using a sample of 546 bank-year observations from 1995 to 2002, I find that, after

controlling for investments in RF and RV swaps for risk management purposes, bank managers

appear to enter into swaps to manage NII. Specifically, I find that if unmanaged NII is less

(greater) than the target, banks enter into RF (RV) swaps to increase (decrease) NII. In addition,

I provide evidence that bank managers do not appear to immediately enter into offsetting swap

positions in subsequent periods to mitigate the additional interest rate risk taken on by investing

in swaps to manage NII. A possible explanation for this latter finding is that, instead of strictly

maintaining risk management equilibrium, managers consider subsequent periods’ interest rate

changes and the new NII target before deciding on entering into new swap positions in the

subsequent period.

This paper contributes to the current literature by providing evidence on whether swap

instruments are widely used to manage earnings in the banking industry. To the best of my

knowledge, this is the first study showing that derivative instruments are used for earnings

management rather than risk management purposes.

Secondly, while most of previous studies

focus on LLP and SGL as tools to manage banks’ total net income (Moyer, 1990; Beatty et al.,

1995; Collins et al., 1995; Ahmed et al., 1999; Beatty et al., 2002), this study shows that swaps

often are used to manage NII, an intermediate and significant component of total net income.

However, this NII management opportunity arises only if swaps are accounted for as hedges

6

Barton (2001) and Pincus and Rajgopal (2002) find a substitute relationship between derivatives usage and

discretionary accruals management by nonfinancial companies. Since earnings are a sum of cash flows and

accruals, they show that smoothing cash flows with derivatives has (1) a direct effect on the volatility of earnings

by smoothing cash flows, and (2) an indirect effects on earnings management by reducing the need to smooth

earnings through discretionary accruals. These studies assume that derivatives are used for risk management

purposes only. In contrast, this study examines whether derivatives are used for both risk management and

earnings management purposes.

6

under either the past and current hedge accounting models. Interestingly, it should be noted that

this NII management opportunity will be eliminated if the FASB moves to a full fair value model

for financial instruments, as foreshadowed in FAS No. 133.

This paper is organized as follows. Section II provides evidence on importance of NII.

Section III explains how swap instruments are used for both risk and earnings management

purposes. Section IV develops the hypotheses. Section V introduces the research design. Section

VI defines the sample and provides descriptive statistics. Section VII presents results. Section

VIII provides conclusions and implications.

II. IMPORTANCE OF NET INTEREST INCOME

The relative importance of NII to bank managers is supported by several sources. First,

NII is the main source of banks’ earnings (Ryan, 2002, p.212). Table 1 provides a summary of

average U.S. commercial banks’ income components as a percentage of total assets. For all

commercial banks in 2002, net interest income is 3.5% on average of total assets. In contrast,

LLP and SGL are only 0.68% and 0.1% of total assets, respectively. For medium sized banks,

the importance of NII is even greater. Specifically, for these banks LLP and SGL are only 0.54%

and 0.04% of total assets, respectively, while NII is 3.94% of total assets.

7

In December 2000, Financial Accounting Standards Board (FASB) issued a Special Report regarding accounting

for financial instruments and similar items prepared by Financial Instruments Joint Working Group of standard

setters (JWG). JWG tentatively concluded that all derivatives are not interest-bearing financial instruments (FASB,

2000b, p. 244). Therefore, consistent with the full fair value accounting for derivatives described in this paper, fair

value gains or losses after adjustment for swap cash receipts and payments are reported outside NII in the income

statement (FASB, 2000b, paragraph 137 (e)).

7

All Banks

10 Largest Banks

Medium Sized

Banks

(Ranked 101

through 1000)

Income and expenses as a percentage of average net consolidated assets

Interest revenue

5.29

4.78

5.88

Interest expense

(1.80)

(1.65)

(1.94)

Net interest income

3.50

3.13

3.94

Loan loss provision

(0.68)

(0.73)

(0.54)

Net interest income after loan

loss provision

2.82

2.40

3.40

Non-interest income

2.53

2.32

2.38

Non-interest expense

(3.46)

(3.15)

(3.74)

Gains on investment account

securities

0.10

0.13

0.04

Income before taxes

1.98

1.69

2.08

Taxes

(0.65)

(0.57)

(0.69)

Net income

1.33

1.12

1.40

Source: Federal Reserve Bulletin, “Profits and Balance Sheet Developments at U.S. Commercial

Banks in 2002,” June 2003. The statistics are based on regulatory call report; thus

represent commercial banks, not bank holding companies.

Table 1. Average U.S. Commercial Banks’ Income Components as a Percentage of Total Assets

Second, bank regulators pay attention to six items in their CAMELS rating to determine

safety and soundness of banks: Capital adequacy, Asset quality, Management, Earnings,

Liquidity, and Sensitivity to market risk. The judgment rating on earnings is based on several

factors, including (1) the level, trend, and stability of earnings, and (2) the quality and sources of

earnings (FDIC, 2002). Given that NII is the main source of banks’ income (Ryan, 2002, p. 212);

managers may want to ensure that NII is stable and growing.

Third, the relative importance of NII as a bank performance indicator is supported by

SEC disclosure requirements. SEC Industry Guide 3 requires banks to make disclosures about

the level and changes in NII. Specifically, banks are required to provide an analysis of net

interest income, which contains information about (1) the average outstanding amounts of

8

interest-earnings assets and interest-bearing liabilities, (2) the average yield earned and paid, and

(3) the interest earned and paid. Another required disclosure is a rate-volume analysis. This

disclosure decomposes the change in net interest income into two components: (1) interest rate

effects, which represent the effects on NII due to changes in interest rates and (2) volume effects,

which represent the effects on NII due to changes in volume of interest-earning assets and

interest-bearing liabilities.

Last, research evidence supports the importance of NII as an indicator of bank’s

performance. Eccher et al. (1996) find that NII is a significant factor in explaining banks’

market-to-book ratio. Similarly, Barth et al. (1990) show that the stock market puts different

weights on earnings components, with the greatest emphasis being placed on earnings before

SGL. Considering NII is a significant portion of earnings before SGL, they provide additional

evidence supporting the relative importance of NII to bank managers.

In sum, due to the significance of NII as a component of total bank earnings, managers

may have a strong incentive to manage NII. Interest rate swaps provide an ideal mechanism to

manage NII because the first period NII effect from entering into swaps is known precisely at

swap inception. However, to achieve this NII management outcome, it is required that banks

account for the new swaps as hedging instruments. Next, I will present economic and accounting

models for swaps to explain (1) how banks use swaps to hedge interest rate risk, and (2) how NII

management is possible under the past and current accounting models. Since earnings

management effects are closely related to the economics of swap valuation, I also will describe

the relationship between swap valuation and swap-based earnings management.

8

For more detailed information, see Ryan (2002).

9

III. SWAPS AS RISK AND EARNINGS MANAGEMENT TOOLS

A. Swaps as Interest Rate Risk Management Tools

Suppose Bank A issues a $1 million fixed-rate (11.85%) loan and Bank B issues a $1

million variable-rate (1-year LIBOR) loan. Since Bank A’s cash inflows from the loan are fixed

regardless of future changes in interest rates, the fair value of the loan will change as interest

rates change. Thus, Bank A’s loan is exposed to fair value risk. In contrast, because Bank B’s

cash inflows from the loan are updated based on the prevailing interest rate, fair value risk

generally is not an issue. Rather, future cash flows will fluctuate with changes in the interest rate.

Thus, Bank B primarily is exposed to cash flow risk.

To hedge these risks, Bank A and Bank B can consider a three-year swap initiated at

January 1, Year 1, where Bank A agrees to pay a rate of 11.85% on the notional amount of $1

million to Bank B and in return Bank B agrees to pay 1-year LIBOR on the same notional amount

to Bank A. The net payments are agreed to be exchanged at the end of every year. This swap is

summarized in Figure 1.

Bank B

11.85% × $1 million

Bank A

LIBOR × $1 million

Figure 1. Interest rate swap between Bank A and Bank B

By entering into the swap as shown in Figure 1 (the swap is a RV swap for Bank A, but a

RF swap for Bank B), Bank A and Bank B each can hedge their respective fair value and cash

flow risks. Specifically, for Bank A, the RV swap effectively converts the fixed-rate loan into a

10

variable-rate loan. As described in Figure 2, for Bank A, cash inflows from the fixed-rate loan are

offset by cash outflows from the fixed-rate leg of the swap. Thus, the net interest cash flows in

the loan and swap are the variable-rate cash inflows from the swap. This implies that the RV

swap has effectively caused the fixed-rate loan to become a variable-rate loan; hence Bank A’s

fair value risk is hedged.

Loan

11.85% × $1M

LIBOR × $1M

Loan

Bank B

Bank A

11.85% × $1M

LIBOR × $1M

Fair Value Hedge

Cash Flow Hedge

Figure 2. Fair Value and Cash Flow Hedges of Loans using a Swap

On the other hand, for Bank B, the RF swap effectively converts the variable-rate loan

into a fixed-rate loan. As shown in Figure 2, variable-rate cash inflows from the loan are offset

by cash outflows of the variable-leg of the swap. The net interest cash flows become the fixed

(11.85%) cash inflows from the fixed leg of the swap. Therefore, Bank B effectively converts the

variable-rate loan into a fixed-rate loan. Thus, Bank B’s cash flow risk is hedged.

Table 2 summarizes effective interest rates on the combined loan and swap, assuming

that 1-year LIBOR for Years 1 through 3 is 10%, 12.01%, and 14.03%, respectively. Note that

after considering swap effects, Bank A’s loan effectively becomes a variable-rate loan and Bank

B’s loan is converted effectively into a fixed-rate loan.

11

Year 1

Year 2

Year 3

LIBOR

10.00% 12.01% 14.03%

Loan Interest Inflows

11.85%

11.85%

11.85%

Swap-Receive

Variable

10.00% 12.01% 14.03%

Swap-Pay

Fixed (11.85%) (11.85%) (11.85%)

Bank A

Effective Int. Rate

10.00%

12.01%

14.03%

Loan Interest Inflows

10.00%

12.01%

14.03%

Swap-Receive

Fixed

11.85% 11.85% 11.85%

Swap-Pay

Variable (10.00%) (12.01%) (14.03%)

Bank B

Effective Int. Rate

11.85%

11.85%

11.85%

Table 2. Effective interest rates after using swaps

Fixed- or variable-rate liabilities also can be hedged using swaps. Figure 3 provides an

example of a liability hedge. Suppose Bank A has a $1 million variable-rate (1-year LIBOR)

liability and Bank B has a $1 million fixed-rate (11.85%) liability. Therefore, Bank A’s liability is

exposed to a cash flow risk because interest payments for the liability will depend on future

interest rates. In contrast, Bank B’s liability is exposed to a fair value risk because interest

payments for the liability are predetermined. By entering into the swap as shown in Figure 1,

both Bank A and Bank B can hedge their risks. As described in Figure 3, the RV swap effectively

converts Bank A’s variable-rate liability into a fixed-rate liability, thus the cash flow risk is

hedged. Also Bank B’s RF swap effectively converts the fixed-rate liability into a variable-rate

liability, thus the fair value risk is hedged.

Bank A

Bank B

LIBOR × $1M

11.85% × $1M

LIBOR × $1M

Liability

Liability

11.85% × $1M

Cash Flow Hedge

Fair Value Hedge

Figure 3. Cash Flow Hedge of a Variable-Rate Liability using a RV Swap

12

In sum, by using swaps, fixed-rate and variable-rate assets & liabilities can be converted

into variable-rate and fixed-rate assets & liabilities, respectively. During the conversion process,

either cash flow risk or fair value risk is hedged. Although banks can convert variable- or fixed-

rate assets and liabilities into fixed- or variable-assets and liabilities, interest risks cannot be

removed completely. For example, if Bank A hedges the cash flow risk of a variable-rate liability

by using a RV swap, this hedging process transforms the cash flow risk into fair value risk; risk

is changed but not eliminated.

In general, banks’ interest rate risks are caused by maturity mismatches. For example,

suppose Bank B has only a $1 million variable-rate loan asset which will mature tomorrow and

be reinvested at the prevailing interest rate, while the funding source is a fixed-rate (11.85%)

liability that will mature three years later. If the variable interest rate falls below 11.85%

tomorrow, then a loss will occur because the lower variable interest revenue on the renewed

loans will not cover the higher fixed interest expense. The opposite is true if the variable interest

rate increases. Therefore repricing and/or maturity differences between assets and liability make

cash flows and earnings volatile. To reduce cash flow and/or earnings volatility, banks often

attempt to match the duration of their assets/liabilities portfolio. This goal can be achieved using

swaps by converting, for example, variable-rate assets into fixed-rate assets or fixed-rate

liabilities into variable-rate liabilities.

B. Swap Valuation

In the Table 2 example, because the interest rate yield curve is upward-sloping (the most

frequent case

), the swap’s fixed interest rate (11.85%) is set to be greater than the variable

interest rate (10%) at Year 1. Given this relationship, Bank B (Bank A) will receive (pay) cash

9

See yield curves from 1995 to 2002 in Figure 7, Section VI.

13

flows from Bank A (Bank B) at the end of Year 1 by entering into RF (RV) swaps. The reverse is

true if the interest rate yield curve is downward-sloping. To understand the relationship between

fixed and variable swap rates, I next describe swap valuation.

Swap interest rates are based on the relation between spot and forward interest rates. The

n-year spot interest rate is defined as the per annum interest rate on an investment that is made

for a period of time starting today and lasting for n years (Hull, 1997). For example, if you invest

$1 million for two years and will receive $232,100 interest at the end of the second year without

receiving any other interest payments during the periods, the 2-year spot interest rate is 11% per

annum.

Sometimes the n-year spot interest rate is called the n-year zero-coupon yield.

Year (n)

Spot rate for n-year investment

(% per annum)

Forward rate for n

th

year

(% per annum)

1 10%

2 11%

12.01%

3 12%

14.03%

Table 3. Spot and Forward Interest Rates

Forward interest rates are defined as the interest rates implied by current spot rates for

periods of time in the future (Hull, 1997). For example, suppose the second column in Table 3

represents current spot interest rates for years 1 through 3 and you want to invest $1 million for

two years. Then, you have two options: (1) invest $1 million for two years at the current two-

year spot rate, which will yield (1+.11)

2

× $1 million, or (2) invest $1 million for one year at

10%, the current one-year spot rate, and then invest the accumulated sum at the end of the first

year at the second year’s expected one-year spot rate, which is the forward rate. Assuming an

efficient market, there should be no arbitrage gains between these two options and thus the

10

Assuming annual compounding, $1,000,000×(1+0.11)

2

− $1,000,000 = $232,100.

14

second year forward rate is the estimate of the second year’s one-year spot rate. This guarantees

that the following equations will hold.

)

1

(

)

1

(

)

1

(

2

1

1

2

2

r

r

r

+

⋅

+

=

+

(1)

)

1

(

)

1

(

)

1

(

)

1

(

3

2

2

1

1

3

3

r

r

r

r

+

⋅

+

⋅

+

=

+

(2)

where , and represent current spot rates for 1-year (=10%), 2-years (=11%), and 3-years

(=12%), respectively. Also,

is a forward rate defined as expected 1-year spot interest rate for

year j as of the end of year i. For example,

represents Year 2’s expected 1-year spot rates as

of the end of Year 1.

is 12.01% from equation (1), implying that the expected 1-year spot

interest rate at the end of the Year 1 is 12.01%. Similarly,

is 14.03% which is the forward

rate at the end of the Year 2. As shown in Figure 4, the forward interest rate curve is always

above the spot interest rate curve as long as the spot rate yield curve is upward-sloping (see Hull

(1997), p. 80 for the proof).

1

r

2

r

3

r

j

i

r

2

1

r

2

1

r

3

2

r

Figure 4. Spot and Forward Rate Yield Curves

11

If the spot yield cure is downward-sloping, the forward yield curve is always below the spot yield curve.

Time to maturity

15

Suppose Bank B wants to enter into a RF swap to hedge the fixed-rate liability as shown

in Figure 3. Given the current yield curve in Figure 4 and assuming the notional amount is $1

million, expected cash flows from the variable leg of the swap are shown in the third column of

Table 4.

12

Note that variable cash flows at the end of the period are determined based on the one-

year forward rate (e.g., LIBOR) at the beginning of each period in Figure 4. For example, since

the interest rate at the swap inception is 10%, Bank B pays $100,000 at the end of the Year 1

because the variable rate used to determine the Year 1 cash flow is set at the beginning of Year 1.

This implies that, when entering a swap transaction, there is no uncertainty about the first period

net cash flow.

13

Date

Forward

LIBOR

Expected

Variable

Cash Outflows

Expected Fixed

Cash Inflows

Expected

Net

Cash Flows

PV of

Net Cash

Flows

Jan. 1, Year 1

Dec.31, Year 1

10%

$100,000

$118,500

+ $18,500

$16,818

Dec.31, Year 2 12.01%

$120,100

$118,500

− $ 1,600

− $ 1,299

Dec.31, Year 3 14.03%

$140,300

$118,500

− $21,800

− $15,517

Total $360,400 $355,500

− $ 4,900

$ 0

Table 4. Cash Flows from a RF Swap

If the two banks seek to enter into an at-the-money swap, the next step is that Bank A and

Bank B must set an interest rate for the fixed leg of the swap that makes the initial swap value

zero. Let k be the Bank B’s fixed cash inflow from the swap. Then, equation (3) should hold.

Thus, k is $118,500, which means the fixed coupon-interest rate of the swap is 11.85%.

0

)

12

.

0

1

(

)

300

,

140

(

)

11

.

0

1

(

)

100

,

120

(

)

1

.

0

1

(

)

000

,

100

(

3

2

=

+

−

+

+

−

+

+

−

k

k

k

(3)

12

It is assumed that there is no credit risk.

13

Hull (1997), p. 112.

14

error)

(rounding

0

)

12

.

0

1

(

800

,

21

)

11

.

0

1

(

600

,

1

)

1

.

0

1

(

500

,

18

3

2

=

+

−

+

+

−

+

+

16

The expected fixed and net cash flows from the RF swap are shown in the fourth and fifth

columns of Table 4, respectively. Note that the first net cash flow is positive and second and

third net cash flows are negative. If the yield curve is upward sloping, the following statements

about the swaps are always true:

15

(1) if the forward rate (i.e., 10%) is less than the fixed interest

rate (i.e., 11.85%) of the swap, then the net cash flows are positive, (2) if the forward rate (i.e.,

12.01% and 14.03%) is greater than the fixed interest rate (i.e., 11.85%) of the swap, then the net

cash flows are negative.

16

In this example, the net cash flow in Year 1 is positive, and this

positive cash flow is offset with negative future cash flows, resulting in zero initial present value

of the swap. In general, if the fixed interest rate is set at α % as shown in Figure 5, the expected

RF swap payments up to period t will generate positive net expected cash flows. From the period

t to maturity, net expected cash flows from the RF swap will be negative. As shown in column 6

of Table 4, the sum of present values of these net positive and negative cash flows is zero at the

initiation of an at-the-money swap contract.

15

The reverse is true when yield curve is downward sloping.

16

See Chapter 5 of Hull (1997) for more details.

17

t

Figure 5. Relationship between forward rate and net cash flows of swaps

To understand the net economic effects of swaps, Table 5 summarizes the economic

effects during Year 1 under the assumption that interest rates move as expected.

At the end of

Year 1, Bank B receives a positive net cash flow of $18,500 from Bank A, but the present value

of Bank B’s commitment to pay cash flows to Bank A in years 2 and 3 is $18,500. Thus, there are

no net economic effects for either Bank A or Bank B from the swap.

17

Hull (1997), p. 125.

18

At the end of Year 1, 1-year and 2-year spot interest rates are 12.01% and 13.01%, respectively. This implies that

(1) Year 2’s forward interest rate becomes the actual 1-year spot interest rate as expected, and (2) Year 3’s

forward interest rate remains the same as before.

18

Date

Forward

LIBOR

Expected

Variable

Cash Outflows

Expected Fixed

Cash Inflows

Net

Cash Flows

PV of

Net Cash

Flows at

12/31/Year 1

Dec.31, Year 2 12.01%

$120,100

$118,500

− $ 1,600

− $ 1,428

Dec.31, Year 3 14.03%

$140,300

$118,500

− $21,800

− $17,070

Fair Value Loss − $18,500

Realized Cash Inflows at Dec. 31, Year 1

$18,500

Net Economic Effect of the swap

$ 0

Table 5. Expected Net Economic Effects from RF Swap at End of Period 1

However, if the variable interest rate moves unexpectedly, net effects could be either

positive or negative depending upon directional changes in interest rates. This implies that net

economic effects of a swap itself are uncertain, creating interest rate risk.

C. Swaps as Net Interest Income Management Tools

In this section, I describe how accounting standards account for the economics of swaps.

As shown in Table 5, the accounting model needs to capture two economic effects: (1)

realization of the net cash flows caused by the difference in interest rates between the fixed and

the variable legs of a swap, and (2) changes in the present value of future expected cash flows.

Let us call the first effect the cash settlement effect and the second effect the fair value effect.

The cash settlement effect provides bank managers with NII management opportunities because

past and current hedge accounting models permit reporting of the net cash settlement under the

swap as adjustments to reported interest revenue and expenses of hedged items. This is

consistent with the economic outcome from hedging activities. Recall, Table 2 previously

demonstrated how swaps can be used to change the current period effective net interest rate for

banks. Bank A (Bank B) effectively converted a fixed-rate (variable-rate) loan into a variable-rate

19

error)

(rounding

500

,

18

)

1301

.

0

1

(

800

,

21

)

1201

.

0

1

(

600

,

1

3

2

−

=

+

−

+

+

−

19

(fixed-rate) loan by using a RV (RF) swap. By recognizing the cash settlement effects from the

swap contract as adjustments to reported interest revenue or expenses, reported NII from the

hedged item will reflect the same interest rate on the hedged transaction as illustrated in Table 2.

Moreover, because the first period cash flow settlement under the swap is set equal to the

difference between the variable and fixed interest rates at swap inception, bank managers can use

the accounting permitted by this hedge accounting model to change NII by a known amount in

the first period. Specifically, if the interest rate yield curve is upward sloping, managers can

increase (decrease) NII by known amounts in Year 1 by entering into a RF (RV) swap position.

However, as shown in the example in Table 5, this cash settlement effect could be

counteracted by the fair value effect if changes in forward rates are recognized in net income as

unrealized gains or losses. However, past and current hedge accounting standards do not require

recognition of most or any of the fair value effect in net income. This is because (1) fair value

changes for hedging swaps were not required to be recognized prior to FAS No. 133, and (2)

post FAS No. 133, banks are required to recognize changes in fair value of both swaps and

hedged items during the same time period for both fair value and cash flow hedges. Since under

hedging accounting, the unrealized gains or losses on hedging swaps often offset the opposite,

corresponding changes in the fair value of the hedged items, there is generally no fair value

effect on net income (see Appendix for details). Therefore, as long as swaps are designated as

hedges, managers can adjust NII to reflect the change in net interest rate effectuated by the swap

without any significant countervailing effect on reported net income.

In contrast to hedging swaps, accounting rules for trading swaps did not change post-FAS

No. 133. Under this fair value accounting model, the cash settlement and fair value effects are

20

If the yield cure is downward-sloping, a RF (RV) swap will decrease (increase) earnings at the early periods of the

swap contract.

20

both required to be recognized in net income (not NII). Therefore, the two effects can offset

because there are no counteracting gains or losses on designated hedged items for trading swaps.

In addition, because management has no knowledge at swap inception as to the direction of

future fair value changes, the net effect of trading swaps on net income is uncertain. In sum, this

suggests that bank managers cannot use trading swaps to manage earnings by a predetermined

amount.

Because the accounting treatment for new swap acquisition under the full fair value

accounting is identical to the accounting for trading swaps under the current partial fair value

hedge accounting model, the NII management opportunity would be lost if FASB were to adopt

full fair value accounting for financial instruments, as foreshadowed by FAS No. 133.

IV. Hypothesis Development

In contrast to prior studies’ focus on using derivatives for risk management purposes (e.g.,

Smith and Stulz, 1985; Froot et al., 1993; DeMarzo and Duffie, 1995), this study argues that

derivatives, specifically interest rate swaps, also can be used to meet earnings targets. As shown

in Section III, when the interest rate yield curve is upward sloping (the typical case), the decision

to enter into a RF swap will generate positive net cash flows in early contract periods. Moreover,

there is no uncertainty about net swap cash flows in the first period because the amount is

predetermined by the difference in fixed and variable interest rate indices at swap inception.

Therefore, because net swap cash settlements are reported in NII when the swap is accounted for

as a hedge, managers know with certainty the magnitude of the first period NII effect when

entering into a swap contract. As a consequence, my first research hypothesis is (assuming an

upward sloping interest rate yield curve) that bank managers will exploit the known positive

21

The cash settlement and fair value effects are reported outside NII. Therefore, trading swaps also provide no

opportunity to manage NII.

21

(negative) effect of RF (RV) swaps on NII to manage earnings. Specifically, banks will enter

into RF swaps if they anticipate that unmanaged NII will be less than management’s target for

NII. In contrast, if the current year’s unmanaged NII exceeds targeted NII, managers may want

to defer NII to future periods. This goal can be attained by entering into RV swaps because

(assuming an upward sloping interest rate yield curve) RV swaps will have a negative NII effect

in early swap periods. This analysis leads to my first hypothesis (stated in alternative form).

H1: After controlling for investments in RF and RV swaps for risk management

purposes and assuming an upward sloping interest rate yield curve, (1) if

unmanaged NII is below management’s target for NII, banks will enter into

additional RF swaps to increase current NII, or (2) if unmanaged NII exceeds

management’s target for NII, banks will enter into additional RV swaps to defer

current NII to future periods.

Using swaps for NII management purposes is not costless, however, because the NII

management swaps will move banks’ swap portfolio away from the amount desired for risk

management purposes.

If maintaining an equilibrium risk management level throughout the

entire period is critical, banks need to minimize the risk effects induced by NII management

swaps. This can be achieved, albeit imperfectly, by entering into offsetting swaps in the

subsequent period. For example, if banks use RF swaps to increase current NII, they could enter

into similar magnitude RV swaps in the next period to offset the change in risk exposure caused

by entering into the RF swap this period. The reverse is true for RV swaps.

However, banks may not find it cost-effective to immediately enter into offsetting swaps

positions in the subsequent period because it may be difficult to enter into well-matched

offsetting swap positions when significant changes in the current period interest rate yield curve

occur subsequent to the acquisition of a NII management swap contract. Thus, instead of

22

Conversations with derivative dealers indicate that transactions costs are only 2 basis points (.0002) of the

notional amount of the swap contract.

22

immediately entering into offsetting swaps, bank managers may find it cost-effective to delay

entering into swap positions in the subsequent period until they know the distance from earnings

targets and the subsequent period interest rate risk exposure.

To test whether or not banks find it cost-effective to immediately enter into offsetting

swap position in the subsequent period to mitigate the effects arising from entering into swaps

for earnings management purposes, I propose this second research hypothesis (stated in

alternative form).

H2: If banks use either RF swaps or RV swaps to manage NII, they will enter into

offsetting swap positions in the subsequent period to mitigate the interest rate risk

induced by entering into swaps for earnings management purposes.

V. RESEARCH DESIGN

A. Hypothesis 1

To test H1, I estimate the following model:

it

it

it

it

it

LTGAP

Y

GAP

DIFF

NETSWAP

ε

α

α

α

α

+

∆

+

∆

+

+

=

∆

3

2

1

0

1

(4)

where: ∆NETSWAP

it

: Change in net swap positions for bank i in period t, i.e.,

∆(RFSWAP−RVSWAP), where RFSWAP (RVSWAP) is notional

amounts of RF swaps (RV swaps). ∆NETSWAP is deflated by beginning

total assets.

DIFF

it

: difference between NII target and unmanaged NII for bank i in period t

deflated by beginning total assets (a more precise definition is provided by

equations (5)-(9)),

∆GAP1Y

it

: Change in 1-year GAP for bank i in period t deflated by beginning total

assets.

∆LTGAP

it

: Change in long-term GAP for bank i in period t deflated by beginning

total assets.

23

To explain changes in net swap positions, I first introduce two variables (∆GAP1Y and

∆LTGAP) that measure the basic risk management relationship between swap positions and

interest rate risk. Changes in asset/liability compositions influence net changes in swap positions

because interest rate risk is mainly driven by the maturity mismatch in asset/liability

composition.

GAP1Y and LTGAP are defined as the differences between interest-earning

assets and interest-bearing liabilities that will respectively mature or reprice within one year or

subsequent to one year.

Positive (negative) GAP1Y indicates that interest rate sensitive assets

that mature or reprice within one year are greater (less) than similar interest rate sensitive

liabilities. Similarly, positive (negative) LTGAP indicates that interest rate sensitive assets that

mature or reprice outside a one-year period are greater (less) than similar interest rate sensitive

liabilities.

To achieve risk management objectives, bank managers may want to enter into new swap

positions as interest rate risk changes (i.e., as GAP positions change). For example, suppose that

both (1) GAP1Y and LTGAP at year t-1 are positive, and (2) ∆GAP1Y and ∆LTGAP increase.

Since during period t both GAP positions moved further away from zero when compared to the

positions at period t-1, interest rate risk is increased. Thus, managers may want to hedge these

increased risks. Specifically, because interest rate sensitive assets and liabilities that mature or

23

Previous studies find that several variables (such as size, levels of deposit financing, liquidity, and bank capital)

influence the decision to use swaps. However, there are no studies examining what characteristics of companies

affect the use of certain type of swaps, i.e., RF swaps or RV swaps. For example, it is known that there is

economies of scale regarding initiating and maintaining a hedging program (e.g., Booth et al., 1984; Mian, 1996;

Geczy et al., 1997, Haushalter, 2000, Kim and Koppenhaver, 1992). This implies that bank size is positively

associated with the level of total swap usage. However, there is no reason to believe that bank size has a certain

relationship with using more RF swaps than RV swaps or vice versa. Therefore, I do not include these variables in

equation (4).

24

Total interest-earning assets are computed as a sum of interest-earning deposits, securities, federal funds sold,

securities purchased under agreements to resell, and loan and lease financing receivables. Total interest-bearing

liabilities are computed as a sum of interest-bearing deposits, federal funds purchased, securities sold under

agreements to repurchase, commercial paper, other borrowed money, mortgage indebtedness, and subordinated

notes and debentures. One year maturity information is obtained from the Interest Sensitivity Schedule in the FR

Y9-C report.

24

reprice within one-year require frequent resetting of the instrument’s interest rates, a positive

∆GAP1Y implies that cash flow risk has increased. To hedge this additional cash flow risk,

managers may choose to increase RF swaps in Year 1 to convert cash flow sensitive net assets

into fair value sensitive net assets. Similarly, because interest rate sensitive assets and liabilities

that mature or reprice in periods outside one-year have fixed interest rates for extended time

periods, a positive ∆LTGAP implies that fair value risk is increased. To hedge this additional fair

value risk, managers may enter into RV swaps in Year 1 to convert increased fair value sensitive

net assets into cash flow sensitive net assets. When the signs of ∆GAP1Y and ∆LTGAP at t-1

are different from this example, the same rationale can be applied to predict what swap positions

should be entered into to maintain the same risk level.

Note, as illustrated above, I expect that positive changes in GAP1Y and LTGAP may

induce management to enter into different net swap positions for risk management purposes, i.e.,

management either will increase RF or RV swaps depending on whether there has been an

increase in ∆GAP1Y or ∆LTGAP, respectively. Therefore, I use net swap positions as the

dependent variable in equation (4) instead of total notional amounts of swaps.

The net swap

position is defined as the difference in notional amounts between RF and RV swaps. As stated

previously, I expect that positive ∆GAP1Y (∆LTGAP) to be associated with positive changes in

RF (RV) swaps. This implies that ∆GAP1Y (∆LTGAP) is positively (negatively) associated with

changes in net swap positions, ∆NETSWAP. Thus, I predict

2

α

and

3

α

to be positive and

negative, respectively.

After controlling for changes in net swap positions for risk management purposes, H1

predicts that managers may enter into additional swaps for NII management purposes. To test

25

Most previous studies (e.g., Kim and Koppenhaver, 1992; Jagtiani, 1996; Carter and Sinkey, 1998) use total

notional amounts to examine the relationship between the use of interest rate swaps and bank characteristics.

25

whether bank managers appear to enter into RF and RV swaps for NII management purpose, I

first must identify the direction and amount by which NII is needed to be managed to meet

targeted NII. As defined in equation (5), this is measured by the difference between the NII

target (NIIT) and unmanaged NII (UNII).

it

it

it

UNII

NIIT

DIFF

−

=

(5)

it

it

it

AEA

NIM

NIIT

⋅

=

−1

(6)

where, NIIT

it

: net interest income target for bank i in period t

UNII

it

: unmanaged net interest income for bank i in period t

NIM

it-1

: net interest margin percentage (NII/average interest-earning assets) for

bank i in period t-1

AEA

it

: average interest-earning assets for bank i in period t

Similar to the prior year net income threshold used by Degeorge et al. (1999), this study

bases its net interest income target (NIIT

it

) on the prior year’s net interest margin percentage

(NIM

it-1

).

26

In specific, to control for annual changes in the net earning assets of sample banks,

NIIT

it

is estimated in equation (6) by multiplying prior year’s NIM

it-1

by current year’s average

earnings assets (AEA

it

). If UNII is less than NII target, H1 predicts that bank managers will use

RF swaps to manage NII upward. Similarly, if UNII is greater than reported NII, then H1

predicts that bank managers will use RV swaps to manage NII downward.

To estimate unmanaged net interest income (UNII), a firm-specific NIM beta (

1

,

i

β

) is

estimated in equation (7) by regressing the individual banks’ quarterly NIM (

) on the

average historical quarterly industry NIM (

).

iq

NIM

q

INDNIM

iq

q

i

i

iq

INDNIM

NIM

ε

β

β

+

+

=

1

,

0

,

(7)

26

Net interest margin is defined as ratio of NII to average earning assets. I selected it as the target because my

examination of 36 bank earnings releases in 2002 indicated that 31 of these banks compare current period’s NIM

and/or NII to same amount in the prior period when assessing bank performance.

26

where, NIM

iq

: net interest margin percentage (NII/average interest-earning assets) for

bank i at quarter q

INDNIM

q

: industry average net interest margin percentage for bank i at quarter q

To estimate equation (7), I use a maximum of 32 and a minimum of at least 24 of the 32

quarterly observations immediately prior to the target period.

27

Equation (7) derives

, which

captures the firm specific NIM sensitivity to industry average NIM. Each bank’s unmanaged

NIM (UNIM

1

,

i

β

ˆ

it

) then is obtained by plugging the estimated betas from equation (7) and the test

period’s quarterly industry average NIM into equation (8).

∑

=

+

=

4

1

1

,

0

,

)

ˆ

ˆ

(

q

q

i

i

it

INDNIM

UNIM

β

β

(8)

where,

it

UNIM

: predicted value of unmanaged net interest margin for bank i at year t

INDNIM

q

: industry average net interest margin percentage for bank i at quarter q

To control for periodic changes in banks net interest earnings assets (like in equation (6)),

this unmanaged NIM is multiplied by current year’s average interest-earning assets to get UNII

as in equation (9).

it

it

it

AEA

UNIM

UNII

⋅

=

(9)

where, UNII

it

: unmanaged net interest income for bank i at year t

it

UNIM

: predicted value of unmanaged net interest margin for bank i at year t

AEA

it

: average interest-earning assets for bank i at year t

DIFF (as defined in equation (5)) reflects the difference between target (NIIT) and

unmanaged net interest income (UNII) and is used to define the degree to which bank managers

27

At least 24 observations are used to estimate equation (7) to (i) improve stability of regression estimates, and (ii)

minimize any effects that prior period earnings management may have on equation (7) estimates by increasing the

probability that the regression observations reflect periods in which NII was managed both upward and downward

and, therefore, increasing the probability that earnings management effects are averaged away in the estimation

procedure.

27

seek to manage NII. If banks manage NII using swaps, DIFF should be associated with the

∆NETSWAP (∆(RFSWAP-RVSWAP)) position after controlling for changes in swaps due to

risk management purposes. If the DIFF is positive, it implies that banks have managed NII

upward by increasing RF swap positions. Increasing RF swap positions causes a positive

∆NETSWAP and, therefore, a positive coefficient on DIFF. Similarly, a negative DIFF implies

that banks have managed NII downward by decreasing their ∆NETSWAP (by increasing RV

swaps), which again suggests a positive coefficient on DIFF.

Thus, to test H1, I assess whether

1

α

in equation (4) is positive.

B. Hypothesis 2

H2 predicts that after increasing swap positions for NII management in the current period,

bank managers may attempt to immediately offset these positions in subsequent periods to

mitigate the deleterious risk management effects caused by entering into NII management swaps.

However, this action may neither be cost-effective nor feasible because the ability to achieve

perfect offset becomes increasingly more difficult as the current period interest rate yield curve

changes during the time period after swaps are entered into to manage NII. To test whether or not

bank managers find it cost-effective to immediately enter into offsetting swap positions in the

subsequent period, I add DIFF

it-1

to equation (4).

it

it

it

it

it

it

LTGAP

Y

GAP

DIFF

DIFF

NETSWAP

ε

δ

δ

δ

δ

δ

+

∆

+

∆

+

+

+

=

∆

−

4

3

1

2

1

0

1

(10)

28

The test documented in the text assumes increases in net swap positions can occur by either entering into RF

swaps at year-end or failing to replace RV swaps maturing near year-end. Similarly, decrease in net swap

positions are assumed to occur by entering into RV swaps at year-end or failing to replace RF swaps maturing

near year-end. As a follow-on test, I also assess whether NII management occurs primarily by purchasing RF and

RV swaps near year-end.

28

where: ∆NETSWAP: Change in net swap positions, i.e., ∆(RFSWAP−RVSWAP), where

RFSWAP (RVSWAP) is notional amounts of RF swaps (RV swaps).

∆NETSWAP is deflated by beginning total assets.

DIFF: NII target − Unmanaged NII deflated by beginning total assets,

∆GAP1Y: Change in 1-year GAP deflated by beginning total assets.

∆LTGAP: Change in long-term GAP deflated by beginning total assets.

DIFF

it-1

is used to assess (1) if banks manage their NII upward by entering into RF swaps

at t-1, (2) whether banks also enter into RV swaps at t to offset the NII management effects in

subsequent periods. If this is true, then DIFF

it-1

should be negatively associated with

∆NETSWAP

it

. Similarly, if banks manage their NII downward by entering into RV swaps at t-1,

then DIFF

it-1

should be negatively associated with ∆NETSWAP

it

if offsetting swaps are entered

into in period t. Therefore, if bank managers find it cost-effective to enter into offsetting swap to

mitigate interest risk, I predict

2

δ

to be negative. However, if bank managers do not find it cost-

effective to make such offsetting swap acquisition,

2

δ

will be zero. The expected sign on other

variables are the same as in equation (4).

VI. SAMPLE AND DESCRIPTIVE STATISTICS

A. Sample

Panel A of Table 6 describes the sample selection process. To identify swap users, I start

with all risk management derivative activities reported in bank holding companies’ regulatory

data (FR Y-9C) from 1995 to 2002. I found that 598 banks (2,073 observations) report non-zero

derivative notional amounts including swaps. From this list, I delete banks (bank-year

observations) that do not meet the following conditions. First, Beatty et al. (2002) show that

public banks have a much greater proclivity to manage earnings than do private banks. Therefore,

I include only public banks in the sample and delete a total of 267 private banks (618

29

observations). Second, to ensure that sample banks were active derivative users, I also excluded

101 banks (101 observations) having only one non-zero derivative observation in FR Y-9C

reports. Finally, because FR Y-9C reports provide income information on a calendar year basis, I

deleted 9 banks (26 observations) having non-December 31 fiscal year-ends. These sample

selection criteria create an initial sample of 221 banks (1,328 bank-year observations) that are

active derivative users.

Insert Table 6 here

For these 221 active derivative users, I manually collected information from annual

reports about swap activities accounted for as hedges. For these sample banks, I deleted 36 banks

(519 observations) because they did not use interest rate swaps during the sample period. Since

at least 24 quarter observations are needed to estimate NIM beta, and first differences are used to

construct variables, a total of 39 banks (263 observations) also are excluded from the sample due

to missing data. The final sample consists of 146 banks (546 observations). Panel B of Table 6

provides the number of final sample observations by year. The numbers of banks are evenly

distributed across the sample period.

B. Descriptive Statistics

Panel A of Table 7 reports overall swap positions of sample banks. Average investments

in RF swaps as a percentage of total assets are almost two times greater than for RV swaps.

Specifically, the notional amounts of RF swaps are on average 5.24% of total assets, while the

notional amounts of RV swaps are 2.01% of total assets on average. Figure 6 graphs the trend of

sample banks’ swap usage from 1996 to 2002. For RV swaps, the mean notional amounts

deflated by total assets are stable over the sample period. In contrast, the mean notional amounts

30

of RF swaps deflated by total assets are decreasing over the sample period. One interesting item

is the dramatic decrease in RF swaps in the FAS No. 133 adoption year (2001). However, the

trend recovers in 2002.

Insert Table 7 & Figure 6 here

To determine whether swap usage is significantly different before and after FAS No. 133,

I test for differences in the mean notional swap amounts deflated by total assets. The results are

reported in Panel B of Table 7. While mean difference in RV swaps between pre- and post-FAS

No. 133 is not significant, the mean of RF swaps before FAS No. 133 is significantly greater

than after FAS No. 133. The notional amounts of RF swaps before FAS No. 133 is 5.67% of

total assets, but only 4.07% after FAS No. 133. This difference, however, is driven by the decline

in RF swap usage in the FAS No. 133 adoption year. In the year subsequent to FAS No. 133

adoption, the mean difference in RF swap usage between the pre- and post-period is not

statistically significant.

To better understand the nature of sample banks, I compare firm-characteristics of sample

(swap-using) banks to non-swap using banks. Panel A of Table 8 tabulates this comparison.

From a sample of banks indicating in FR Y-9C that they registered with the SEC, I find 815 non-

swap users (3,504 observations) from 1996 to 2002. My sample banks (146 banks) therefore

comprise 15.2% of swap-using and non-swap using banks, suggesting that only a small

percentage of banks use swaps. Average total assets of swap users ($42 billion) are significantly

greater than that of non-swap users ($910 million). This is consistent with previous studies

showing that larger banks are more likely to use swaps (e.g., Booth et al., 1984; Kim and

Koppenhaver, 1992). The average NIM for non-swap-using banks is slightly greater than swap-

using banks, but the difference is not statistically significant.

31

Insert Table 8 here

I also compare maturity gaps between users and non-users. Swap users’ GAP1Y (13.39%

of total assets) is significantly greater than non-users (2.33% of total assets). In contrast, swap

users’ LTGAP (2.56% of total assets) is significantly less than non-users (12.97% of total assets).

While swap users’ GAP1Y and LTGAP are both positive, GAP1Y is significantly larger than

LTGAP. Thus, if banks are primarily entering into swaps for risk management purposes, this

suggests a greater demand for RF swaps than RV swaps because RF swaps provide the

mechanism to manage short-term interest rate risk, i.e., GAP1Y. Consistent with this prediction,

I find that average notional amount of RF swaps ($4.6 billion) is greater than the notional

amount of RV swaps ($1.6 billion) during the sample period.

The direction of NII management using either RF or RV swaps depends on whether yield

curves during the sample periods are upward or downward sloping. Figure 7 plots monthly

averages interest rate yields from 1995 to 2002 for 3-month, 6-month, 1-year, 3-year, 5-year, and

10-year constant maturity treasury bills. Except for long-term maturities in the year 2000, yield

curves are uniformly upward sloping. Given this yield curve environment, RF swaps (RV swaps)

generally can be used to increase (decrease) earnings in the early periods of contracts, as

predicted in hypothesis 1.

Insert Figure 7 here

Given the upward sloping interest rate yield curve, I estimate the potential change in NII

from entering into swaps during the sample period. To compute this estimate, I multiplied the

difference in interest rate between fixed and variable legs by the annual change in the notional

32

amount of swaps for the period.

In this calculation, I do not separate out the income effects of

swaps used for risk management and earnings management purposes. Preliminary results are

reported in Panel B of Table 8.

For RF swaps, the mean difference in interest rates between

fixed and variable legs of swaps is 1.38%. For RV swaps, the mean difference is -0.94%. The

mean dollar magnitude net effect of swaps on NII is $41 million. On average, banks increase NII

by 12 cents per share using swaps.

Table 9 shows descriptive statistics for the variables used to test hypothesis 1 and 2. All

variables are deflated by beginning total assets. Average ∆NETSWAP is 0.5% of total assets.

Estimated firm-specific NIM betas have a large cross-sectional variation. Average ∆GAP1Y and

∆LTGAP are 2.2% and 0.04% of total assets, respectively. Average DIFF is -0.15% of total

assets.

Panel B of Table 9 shows pairwise correlations among variables. Consistent with

hypothesis 1, ∆NETSWAP is positively (negatively) associated with ∆GAP1Y (∆LTGAP). In

addition, the pairwise correlations between ∆GAP1Y and ∆LTGAP and DIFF

t

and DIFF

t-1

are -

0.93 and 0.44, respectively. Both these correlations are statistically significant, suggesting

potential multicollinearity problem. To assess the extent of this problem, I estimate the variance

inflation factor (VIF) for each of the variables included in equations (4) and (10). VIF values for

DIFF

it

, ∆GAP1Y

it

and ∆LTGAP

it

in equation (4) are 1.02, 7.75 and 7.79, respectively. The VIF

values for DIFF

it

, DIFF

it-1

, ∆GAP1Y

it

and ∆LTGAP

it

in equation (10) are 1.24, 1.25, 6.86 and

6.92, respectively. Neter et al. (1996) suggest that mean VIF values considerably larger than 1

are indicative of serious multicollinearity problems. Therefore, it appears that multicollinearity

problems exist in both equations and tests of the significance on ∆GAP1Y and ∆LTGAP may be

29

The estimated economic effects of decreased swaps may not accurate because information about fixed interest

rates for decreased swaps is not available. I use current swaps’ weighted average fixed interest rates.

30

Since data collection is not yet complete, the reported statistics are based on 58 observations.

31

For the majority of sample banks, the NIM betas used in to estimate DIFF are positive and statistically significant.

Sample banks’ mean NIM beta and standard deviation are 0.08 and 0.17, respectively.

33

affected.

Due to this concern, I first test the confounded effects of the risk management

variables by testing whether ∆GAP1Y or ∆LTGAP are jointly significant in both equations (4)

and (10). Next, to separately evaluate the magnitude and sign of the coefficients on the risk

management variable absent any influence due to collinearity, I also estimate two separate

regressions containing either ∆GAP1Y or ∆LTGAP only.

Insert Table 9 here

VII. RESULTS

Table 10 reports regression results relating to H1. The regression model assesses whether

annual changes in net swap positions can be explained in terms of two sets of variables; one

relating to risk management effects (∆GAP1Y and ∆LTGAP), and the other relating to NII

management (DIFF). In terms of the risk management variables, equation (4) predicts changes in

net swap positions are positively and negatively associated with ∆GAP1Y and ∆LTGAP,

respectively. For equation (4), the coefficient on ∆GAP1Y is significantly positive, but the

coefficient on ∆LTGAP is positive and not statistically significant. However, as mentioned in the

previous section, there are significant collinearity issues with the ∆GAP1Y and ∆LTGAP

variables. To better isolate the sign and statistical significance of these two variables, I first test

whether ∆GAP1Y and ∆LTGAP are jointly significant. The associated F-test indicates

significance at the 1% level. I also estimate two separate regressions that only included either

∆GAP1Y or ∆LTGAP. Individual coefficients on the risk management variables in these

regressions behave as predicted. The coefficients on ∆GAP1Y and ∆LTGAP are significantly

32

However, the low VIF for DIFF suggests that the high degree of correlation between ∆GAP1Y and ∆LTGAP will

not cause bias in DIFF coefficient (Wooldridge, 1999).

34

positive and negative, respectively. The joint results, therefore, indicate that net swap positions

are positively and negatively associated with ∆GAP1Y and ∆LTGAP, respectively, suggesting

that banks change their net swap positions for risk management purposes.

Insert Table 10 here

Given this risk management relationship, I next examine whether banks also manage net

swap positions for NII management purposes. The coefficient on DIFF is significantly positive

across each of the different regression specifications. Therefore, it appears that changes in swap

positions are related to NII management after controlling for changes in interest rate risk. These

results are consistent with H1.

Table 11 presents estimates of equation (10), which are used to assess whether banks

enter into opposite swap positions in the subsequent period to offset the increased risk induced

by entering into swaps for NII management. Despite adding the lagged DIFF variable to the

estimated regression, the inferences remain the same for variables common to equation (4) and

(10). The coefficient on ∆GAP1Y is significantly positive, but the coefficient on ∆LTGAP is

positive and not statically significant. An F-test indicates that ∆GAP1Y and ∆LTGAP are jointly

significant at 5% significance level. Similarly, individual coefficients on ∆GAP1Y and ∆LTGAP

reported in column 4 and 5 of Table 11 are significantly positive and negative, respectively.

Therefore, the results of the relationship between changes in net swap positions and ∆GAP1Y or

∆LTGAP remains the same as before.

Insert Table 11 here

In terms of the DIFF variables, the coefficient on DIFF remains positive and significant,

again suggesting that sample banks acquire swaps to manipulate current period NII. In regards to

35

H2, however, the coefficient on lagged DIFF is negative as predicted, but not significant. This

implies that current changes in net swap positions are not associated with prior year’s DIFF,

counter to predictions in H2. A possible explanation is that strictly maintaining risk management

equilibrium by entering into offsetting swap positions is not cost-effective. Managers instead

seem to consider subsequent periods’ earnings and risk management positions before entering

into new swap positions in the subsequent period.

VIII. CONCLUSIONS

This study examines whether interest rate swaps are used as earnings management tools

by banks. Current and past hedge accounting models permit bank managers to increase

(decrease) NII by predetermined amounts by acquiring RF swaps (RV swaps). I examine

whether banks managers exploit this opportunity to manage NII. I provide evidence that after

controlling for risk management-based swap acquisitions, banks also change swap positions to

manage NII. Specifically, I provide evidence suggesting that if unmanaged NII is below

management’s target for NII, banks increase investments in RF swaps to increase NII. Similarly,

I provide evidence suggesting that if unmanaged NII is above management’s target for NII,

banks increase investments in RV swaps to defer NII to future periods.

Using swaps for earnings management purposes, however, is not costless because it

causes banks’ net swap position to deviate from risk management equilibrium. As a result, I also

test whether managers enter into offsetting swap positions in subsequent periods to mitigate

additional risk induced by entering into swaps for earnings management purposes. My research

findings show that this is not the case. A possible explanation is that the decision to enter into

36

new swap positions in the subsequent period depends primarily on current period interest rate

changes and the distance from the current NII target.

In sum, this study provides evidence that bank managers exploit accounting permitted by

current and past hedge accounting models to manage NII. This research contributes to the

literature by documenting for the first time that swaps are used for both earnings and risk

management purposes. Interestingly, it should be noted that if the FASB were to adopt a full fair

value accounting model for financial instruments, as foreshadowed in FAS No. 133, then bank

managers will lose the opportunity to exploit the accounting model by acquiring swaps for

earnings management purposes.

37

APPENDIX

Hedge Accounting for Interest Rate Swaps Pre- and Post-FAS No. 133

A. Before the Adoption of FAS No. 133

Before the adoption of FAS No. 133, there was no level a authoritative accounting

guidance for interest rate swaps (Herz, 1994).

33, 34

Emerging Issues Task Force (EITF) Issues

Nos. 84-7 and 84-36 provided the only accounting guidance. These EITF issues address the

accounting at inception (84-36) and termination of an interest rate swap (84-7). This guidance

can be summarized as follows (Wishon and Chevalier, 1985; Herz, 1994):

• For swaps not designated as hedging instruments, swaps are recorded at fair values in

balance sheet and changes in fair values are recognize as unrealized gains or losses in

net income (not NII).

• For swaps designated as hedge instruments,

o Swaps are recognized at historical cost (usually zero) in the balance sheet and

interest income and expense is adjusted by periodic net cash settlements under

the swap contract.

o Gain or loss from the settlement of termination should be deferred and

recognized when offsetting gains or losses on hedged items are recognized.

B. After the Adoption of FAS No. 133

A fundamental decision made by the FASB in FAS No. 133 is that derivative instruments

meet the definition of assets and liabilities and should be measured at fair value, because fair

value is the most relevant measure for financial and derivative instruments.

33

Statement on Auditing Standards (SAS) No. 69, The Meaning of ‘Present Fairly in Conformity with Generally

Accepted Accounting Principles’ in the Independent Auditor’s Report, specifies five levels in the GAAP hierarchy

with level a being the most authoritative. EITF Issues are found in level c.

34

In contrast, accounting guidance for currency swaps were explicitly addressed by Financial Accounting Standard

Board Statement No. 52 (FAS No. 52), Foreign Currency Translation in the period prior to FAS No. 133.

38

Under FAS No. 133, interest rate swaps either (1) are treated as stand-alone instruments

or (2) can be designated as either a fair value hedge or cash flow hedge. Stand-alone derivatives

are fair valued in the balance sheet with changes in these fair values recognized in current net

income as unrealized gains or losses. In a fair value hedge, a derivative is entered into to hedge

the exposure to change in fair value of an asset or liability. In a cash flow hedge, a derivative is

entered into to hedge the exposure to variable cash flows. If swaps are accounted for as a fair

value hedge: (1) NII income captures the net periodic cash settlements under the swap, and (2)

unrealized gains or losses on the hedging instruments and the hedged items are recognized in

earnings as they occur. Therefore, the net effect of (2) on earnings is the extent to which the

hedge is not effective in offsetting changes in fair values. This is called hedge ineffectiveness. In

contrast, if swaps are accounted for as a cash flow hedge, FAS No. 133 requires that (1) NII

income captures the net periodic cash settlements under the swap, and (2) to the extent a hedge is

effective, unrealized gains or losses on derivatives are reported initially in other comprehensive

income (OCI) and reclassified into earnings at the time the hedged item affects earnings. The

ineffective portion of a cash flow hedge is recognized in earnings immediately.

C. Example

As initially presented in Section III, suppose that (1) Bank A has $1 million of 3-year,

variable-rate (1-year LIBOR) assets, and (2) Bank B also has $1 million of 3-year, fixed-rate

(11.85%) assets. Bank A’s assets reprice at the end of each year. Bank A wants to hedge its cash

flow risk and Bank B wants to hedge its fair value risk. Thus, they agree to enter into a swap

contract. Under this swap agreement, Bank A pays to Bank B variable interest rate on $1 million.

At the same time, Bank A receives from Bank B fixed interest (11.85%) on $1 million. This swap

39

is a RF swap for Bank A and a RV swap for Bank B. Given the current yield curve in Figure 4,

cash flows for Bank A and Bank B are as follows:

Date

Jan. 1, Year 1

Cash Flows

Dec. 31, Year 1

Cash Flows

Dec. 31, Year 2

Expected CF

Dec. 31, Year 3

Expected CF

Spot Rate

Forward Rate

10%

11.00%

12.01%

12.00%

14.03%

Variable-Rate

Asset (1,000,000)

100,000

120,100

140,300

1,000,000

Swap-Rec. Fixed

118,500

118,500

118,500

Swap-Pay Var.

(100,000)

(120,100)

(140,300)

B

A

N

K

A Total (1,000,000)

118,500

118,500

1,118,500

Fixed-Rate Asset

(1,000,000)

118,500

118,500

118,500

1,000,000

Swap-Rec. Var.

100,000

120,100 140,300

Swap-Pay Fixed

(118,500)

(118,500) (118,500)

B

A

N

K

B Total (1,000,000)

100,000

120,100

140,300

Table A. Cash flows from assets and swaps

At the end of Year 1, under FAS No. 133, Bank A and Bank B need to know the fair value

of both the swap and their assets to be able to mark them to market. Suppose one-year and two-

year spot rates at the end of the Year 1 are 12% and 13%, respectively. Then, the fair values (i.e.,

present value of expected cash flows discounted at expected spot interest rate) of the assets and

swap at the end of Year 1 are as follows:

35

000

,

000

,

1

)

12

.

0

1

(

300

,

140

,

1

)

11

.

0

1

(

100

,

120

)

1

.

0

1

(

000

,

100

3

2

=

+

+

+

+

+

36

000

,

000

,

1

)

12

.

0

1

(

500

,

118

,

1

)

11

.

0

1

(

500

,

118

)

1

.

0

1

(

500

,

118

3

2

=

+

+

+

+

+

40

Date

Dec. 31, Year 2

Expected CF

Dec. 31, Year 3

Expected CF

PV Gain/Loss

Spot Rate

12%

13%

Forward Rate

14.01%

Variable-Rate

Asset

120,000

140,100

1,000,000

1,000,000 0

Swap-Rec. Fixed

118,500

118,500

Swap-Pay Var.

(120,000)

(140,100)

Swap-Net (1,500)

(21,600)

(18,268)

(18,268)

B

A

N

K

A Total

118,500

1,118,500

981,732 OCI (18,268)

Fixed-Rate Asset

118,500

118,500

1,000,000

981,732

(18,268)

Swap-Rec. Var.

120,000

140,100

Swap-Pay Fixed

(118,500)

(118,500)

Swap-Net 1,500

21,600

18,268

37

18,268

B

A

N

K

B Total

120,000

140,100

1,000,000 NI 0

Table B. Fair values of the Bank A and Bank B’s assets and swaps at the end of Year 1

Before adoption of FAS No. 133, Bank A’s journal entries for Year 1 are provided in

Table C. Since prior to FAS No. 133 fair value recognition of the swap and hedged item is not

required by the hedge accounting model, only the interest on the hedged item and the net positive

interest rate effect from the RF swap is recognized in NII.

37

error)

rounding

(

268

,

18

)

13

.

0

1

(

600

,

21

)

12

.

0

1

(

500

,

1

2

−

=

+

−

+

+

−

38

error)

rounding

(

732

,

981

)

13

.

0

1

(

500

,

118

,

1

)

12

.

0

1

(

500

,

118

2

=

+

+

+

41

Before FAS No. 133 (Bank A, RF swap)

01-01-Year 1

Assets 1,000,000

Cash 1,000,000

(Record investment)

12-31-Year 1

Cash 100,000

Interest Revenue 100,000

(Record interest on assets)

Cash 18,500

Interest Revenue 18,500

(Record cash flow from swap)

Table C. Bank A’s Journal Entries before FAS No. 133

Each bank’s journal entries for Year 1 after FAS No. 133 adoption are provided in Table

D. The first column of Table D represents journal entries when Bank A’s RF swap is not

designated as a hedge, and therefore, treated as a stand-alone derivative.

If swaps are not

designated as hedge, the income statement effects of the swap affect net income not NII.

Moreover, changes in fair value of swaps mitigate the earnings increasing effect from the RF

swap on net income. Specifically, Bank A can increase its non-interest income by entering into

the RF swap by $18,500. However, due to the recognition of the fair value loss on the swap (loss

$18,268) the net effect on earnings is only $232.

The second column of Table D presents Year 1 journal entries when Bank A’s RF swap is

accounted for as a cash flow hedge. Bank A’s RF swap increases NII by $18,500. This positive

effect is not mitigated by fair value loss on the swap because to the extent it is effective changes

in the fair value of the swap are reported in OCI under a cash flow hedge. Therefore, to the

extent it is effective in Year 1 of the hedge, the valuation of the swap itself does not have an

effect on earnings under a cash flow hedge.

39

The same accounting was prescribed for trading swaps prior to FAS No. 133.

42

No Designation (Bank A)

Bank A (Cash Flow Hedge, RF swap)

Bank B (Fair Value Hedge, RV swap)

01-01-Year 1

Assets 1,000,000

Cash 1,000,000

(Record investment)

01-01-Year 1

Assets 1,000,000

Cash 1,000,000

(Record investment)

01-01-Year 1

Assets 1,000,000

Cash 1,000,000

(Record investment)

12-31-Year 1

Cash 100,000

Interest Revenue 100,000

(Record interest on assets)

Cash 18,500

Swap payable 18,500

(Record cash flow from swap)

Swap payable 232

Non-interest income 232

(Record fair value of swap, $18,500-

$18,268 = $232)

12-31-Year 1

Cash 100,000

Interest Revenue 100,000

(Record interest on assets)

Cash 18,500

OCI 18,500

(Record cash flow from swap)

OCI 18,500

Interest Revenue 18,500

(Reclassify into earnings)

OCI 18,268

Swap payable 18,268

(Record fair value of swap,

see Table B)

12-31-Year 1

Cash 118,500

Interest Revenue 118,500

(Record interest on assets)

Interest Expense 18,500

Cash 18,500

(Record cash flow from swap)

Unrealized loss on assets 18,268

Assets 18,268

(Record change in fair value of

hedged item, see Table B)

Swap Receivable 18,268

Unrealized gain on swap 18,268

(Record fair value of swap, see Table B)

Income Statement

Income Statement

Income Statement

Interest Revenue

100,000

Interest revenue

118,500

Interest revenue

Interest Expense

118,500

(18,500)

NII

Non-interest Income

100,000

232

NII

118,500 NII

Non-interest income

Unrealized loss on assets

Unrealized gain on swap

100,000

(18,268)

18,268

NI

100,232 NI

OCI

118,500

(18,268)

NI 100,000

Table D. Journal Entries after FAS No. 133

40

At swap inception, spot and forward interest rates in Year 2 and Year 3 are expected to be 12.01% and 14.03%. However, actual spot and forward interest rates

are 12% and 14.01%. These unexpected interest rate changes cause the difference between $18,500 and $18,268.

43

The third column of Table D represents Year 1 journal entries when Bank B’s RV swap is

accounted for as a fair value hedge. Bank B’s RV swap decreases NII by $18,500. The change in

fair value of the swap is perfectly offset by the change in fair value of hedged item, resulting in

zero effect on net income.

This example in Table D represents the case of a perfect hedge. However, hedging is not

always perfect because of (1) differences between the variable rate indices under the swap (e.g.,

LIBOR) and hedged item (e.g., prime rate) and/or (2) differences in critical terms between swaps

and hedged items, such as notional amounts, maturities, interest payment dates. FAS No. 133

requires reporting any hedge ineffectiveness in earnings. Under the fair value hedge accounting,

since the changes in fair value of both a hedged item and a hedging instrument are reported as

they occur, the effective and ineffective amounts of the hedging relationship are recognized in

earnings. In contrast, under the cash flow hedge, it is required to decide whether a hedge is

effective, because the portion of the hedge income deferred in OCI is limited to the extent to

which a hedging instrument protects against exposure to changes in cash flow risk. Therefore,

the deferred amount reported in OCI represents the effective hedge amount. The ineffective

portion of a cash flow hedge is reported immediately in net income. All hedging relationships

should be assessed both prospectively and retrospectively as to whether the relationships have

been and will be highly effective. If the hedge fails the effectiveness test at any time, the hedge

ceases to qualify for hedge accounting.

If certain conditions are met,

FAS No. 133 allows a shortcut method to simplify

necessary computations to determine hedge effectiveness (FAS No. 133, paragraph 68). If the

41

The following conditions should be met: (1) the notional amount of the swap matches the principal amount of

hedged item, (2) the fair value of the swap is zero at the inception, (3) the formula for computing net settlements

under the swap is the same for each net settlement, (4) the hedged item is not prepayable unless embedded call or

put option mirrored in swap, and (5) index for variable leg of the swap is the same as hedged benchmark rate.

44

shortcut method criteria are met, it is assumed that there is no hedge ineffectiveness. Under the

shortcut method, banks compute and recognize immediately the fair values of swaps in the

balance sheet. In addition, the fair value of the hedged items is adjusted by the same amount as

the change in the fair value of the swap, guaranteeing perfect effectiveness. As a result, under the

shortcut method, (1) there is no need to compute the fair values of the hedged item because a

perfect hedge is assumed, and (2) a journal entry for hedge ineffectiveness is not necessary.

Therefore, under the shortcut method, interest expense equals the net cash interest payment for

the hedged item and swap (FAS No. 133, paragraph 118). Table E (on the next page)

summarizes swaps’ effects on NII and net income pre- and post-FAS No. 133 and provides the

basis for the statements made about NII and net income management in Section II.

45

Hedging Instrument

Stand-alone Derivative

Effect of

Periodic net

Cash flows

Effect of

unrealized gains

or losses

(Perfect hedge or

short-cut method)

Effect of

unrealized gains

or losses

(Imperfect hedge)

Effect of

net CF

from swap

Effect of

unrealized gains

or losses

(Perfect hedge or

short-cut method)

Effect of

unrealized gains

or losses

(Imperfect hedge)

Pre-FAS

No. 133

NII

Not required to

recognize

Not required to

recognize

Post-FAS

No. 133

NII

Required to

recognize in net

income. However,

no net effect on

net income due to

no ineffectiveness

The amount of

ineffectiveness

affects net income

(not NII)

Adjusted in

unrealized gains

or losses on swaps

(no effect on NII)

Required to

recognize in net

income.

(not NII)

Required to

recognize in net

income.

(not NII)

Table E. Swaps’ effects on NII and net income pre- and post-FAS No. 133

46

References

Ahmed, A. S., C. Takeda, and S. Thomas, 1999, Bank Loan Loss Provisions: A Reexamination

of Capital Management, Earnings Management and Signaling Effects, Journal of

Accounting and Economics, Vol. 28, pp. 1-25.

Baker Botts L.L.P, 2003, Report to the Board of Directors of the Federal Home Loan Mortgage

Corporation: Internal Investigation of Certain Accounting Matters.

Barth, M. E., W. H. Beaver, and M. A. Wolfson, 1990, Components of Earnings and the

Structure of Bank Share Prices, Financial Analysts Journal, Vol. 46, No. 3, pp. 53-60.

Barton, J., 2001, Does the Use of Financial Derivatives Affect Earnings Management Decisions?,

The Accounting Review, Vol. 76, No. 1, pp. 1-26.

Beatty, A., S. L. Chamberlain, and J. Magliolo, 1995, Managing Financial Reports of

Commercial Banks: The Influence of Taxes, Regulatory Capital, and Earnings,

Journal of Accounting Research, Vol. 33, No. 2, pp. 231-261.

Beatty, A., B. Ke, and K. Petroni, 2002, Differential Earnings Management to Avoid Earnings

Declines and Losses Across Publicly and Privately-Held Banks, The Accounting

Review, Vol. 77, No. 3, pp. 547-570.

Booth, J. R., R. L. Smith, and R. W. Stolz, 1984, Use of Interest Rate Futures by Financial

Institutions, Journal of Bank Research, Vol. 15, pp. 15-20.

Carter, D. A. and J. F. Sinkey, 1998, The Use of Interest Rate Derivatives by End-users: The

Case of Large Community Banks, Journal of Financial Services Research, Vol. 14,

pp. 17-34.

Collins, J. H., D. A. Shackelford, and J. M. Wahlen, 1995, Bank Differences in the Coordination

of Regulatory Capital, Earnings, and Taxes, Journal of Accounting Research, pp.

263-291.

Degeorge, F., J. Patel, and R. Zeckhauser, 1999, Earnings Management to Exceed Thresholds,

Journal of Business, Vol. 72, No. 1, pp. 1-33.

DeMarzo, P.M. and D. Duffie, 1995, Corporate Incentives for Hedging and Hedge Accounting,

The Review of Financial Studies, Vol. 8, No. 3, pp. 743-771.

Eccher, E. A., K. Ramesh, and S. R. Thiagarajan, 1996, Fair Value Disclosures by Bank Holding

Companies, Journal of Accounting & Economics, Vol. 22, pp. 79-117.

Federal Deposit Insurance Corporation (FDIC), 2002, DOS Manual of Exam Policies: Basic

Examination Concepts and Guidelines, Section 1.1, February 2002.

47

Financial Accounting Standards Boards, 1981, Statement of Financial Accounting Standards No.

52: Foreign Currency Translation, Norwalk, CT.

Financial Accounting Standards Boards, 1998, Statement of Financial Accounting Standards No.

133: Accounting for Derivative Instruments and Hedging Activities, Norwalk, CT.

Financial Accounting Standards Boards, 2000a, Statement of Financial Accounting Standards No.

138: Accounting for Certain Derivative Instruments and Certain Hedging Activities,

An Amendment of FASB Statement No. 133, Norwalk, CT.

Financial Accounting Standards Boards, 2000b, Recommendations on Accounting for Financial

Instruments and Similar Items, Financial Accounting Series No. 215-A, Special

Report by Joint Working Group of Standard Setters.

Financial Accounting Standards Boards, 2003, Statement of Financial Accounting Standards No.

149: Amendment of Statement 133 on Derivative Instruments and Hedging Activities,

Norwalk, CT.

Froot, K. A., D. S. Scharfstein, and J. C. Stein, 1993, Risk Management: Coordinating Corporate

Investment and Financing Policies, The Journal of Finance, Vol. 48, No.5, pp. 1629-

1658.

Geczy, C., B. A. Minton, and C. Schrand, 1997, Why Firms Use Currency Derivatives, The

Journal of Finance, Vol. 52, No.4, pp. 1323-1354.

Haushalter, G. D., 2000, Financing Policy, Basis Risk, and Corporate Hedging: Evidence from

Oil and Gas Producers, The Journal of Finance, Vol. 55, No. 1, pp. 107-152.

Herz, R. H., 1994, Accounting and Financial Reporting for Derivatives and Synthetics, Chapter

43 in The Handbook of Derivatives and Synthetics, McGraw-Hill.

Hull, J. C., 1997, Options, futures, and other derivatives, Prentice-Hall, Inc, 3

rd

edition.

Jagtiani, J., 1996, Characteristics of Banks That Are More Active in the Swap Market, Journal of

Financial Services Research, Vol. 10, pp. 131-141.

Kim, S. and G. D. Koppenhaver, 1992, An Empirical Analysis of Bank Interest Rate Swaps,

Journal of Financial Services Research, pp. 57-72.

Mian, S. L., 1996, Evidence on Corporate Hedging Policy, Journal of Financial and

Quantitative Analysis, Vol. 31, No. 3, pp. 419-439.

Moyer, S. E., 1990, Capital Adequacy Ratio Regulations and Accounting Choices in

Commercial Banks, Journal of Accounting and Economics, Vol. 13, pp. 123-154.

48

Neter, J., M. H. Kutner, C. J. Nachtsheim, and W. Wasserman, 1996, Applied Linear Statistical

Model, McGraw-Hall, Inc, 4

th

edition.

Partnoy, F., 2003, Infectious Greed: How Deceit and Risk Corrupted the Financial Markets,

Henry Holt and Company, LLC, 1

st

edition.

Pincus, M. and S. Rajgopal, 2002, The Interaction between Accrual Management and Hedging:

Evidence from Oil and Gas Firms, The Accounting Review, Vol. 77, No. 1, pp. 127-

160.

Ryan, S. G., 2002, Financial Instruments and Institutions: Accounting and Disclosure Rules,

John Wiley & Sons, Inc.

Scholes, M., G. P. Wilson, and M. A. Wolfson, 1990, Tax Planning, Regulatory Capital Planning

and Financial Reporting Strategy for Commercial Banks, Review of Financial Studies

3, No. 4, pp. 625-650.

Smith, C. W. and R. M. Stulz, 1985, The Determinants of Firms’ Hedging Policies, Journal of

Financial and Quantitative Analysis, Vol. 20, No. 4, pp. 391-405.

Warfield, T. D. and T. J. Linsmeier, 1992, Tax Planning, Earnings Management, and Differential

Information Content of Bank Earnings Components, The Accounting Review, Vol. 67,

No. 3, July 1992, pp.546-562.

Wishon, K. and L. S. Chevalier, 1985, Interest Rate Swaps – Your Rate or Mine?, Journal of

Accountancy, September 1985, pp.63-84.

Wooldridge, J. M., 1999, Introductory Econometrics: A Modern Approach, South-Western

College Publishing.

49

Figure 6

Mean & Median of Notional Amount of Interest Rate Swaps as Percentage of Total Assets from 1995 to 2002

SWAP / TA

Year

50

Figure 7

Interest Rate Yield Curves from 1995 to 2002

1995

1996

1997

1998

1999

2000

2001

2002

1995

1996

1997

1998

1999

2000

2001

2002

1

2

3

4

5

6

7

3-Month

6-Month

1-Year

3-Year

5-Year

10-Year

Maturity

Inte

res

t R

ate

(%

)

1995

1996

1997

1998

1999

2000

2001

2002

51

Table 6

Descriptive Statistics for Sample Banks

Panel A. Sample selection procedures

# of Banks

# of

Observations

Banks that report non-zero derivative notional amounts in Y9-C

data from 1995 to 2002

598

2,073

Private banks

(267)

(618)

Only one observation of non-zero derivative notional amounts

reported in Y9-C

(101)

(101)

Non December fiscal year end

(9)

(26)

Total derivative users

221

1,328

Non-swap observations

(36)

(519)

Total swap users

185

809

Missing data due to first differencing and NIM beta estimation

(39)

(263)

Final sample

146

546

Panel B. Number of observations by year

Year

# of observations

1996

84

1997

90

1998

83

1999

77

2000

66

2001

70

2002

76

Total 546

52

Table 7

Descriptive Statistics of Swap Usage

Panel A. Descriptive statistics for swaps

N

Mean

Median

Std. Dev.

RFSWAP ($ Million)

546

4,636

200

14,350

RVSWAP ($ Million)

546

1,625

26

8,143

RFSWAP / TA

546

0.0524

0.0268

0.0752

RFSWAP / TA

546

0.0201

0.0046

0.0424

Panel B. Descriptive statistics for swaps before and after FAS No. 133

Before FAS No. 133

(N = 400)

After FAS No. 133

(N = 146)

Year 2002

(N = 76)

Mean

4,957

3,758

4,063

Median

231

181

200

RFSWAP ($ Million)

Std.

Dev.

14,919

12,668

14,698

Mean

1,655

1,544

1,936

Median

30

25

25

RVSWAP ($ Million)

Std.

Dev.

8,765

6,152

7,777

Mean

0.0567

0.0407

§

0.0438

Median

0.0321

0.0170

0.0201

RFSWAP / TA

Std.

Dev.

0.0805

0.0569

0.0600

Mean

0.0200

0.0206

0.0217

Median

0.0046

0.0063

0.0063

RVSWAP / TA

Std.

Dev.

0.0450

0.0344

0.0358

RFSWAP: Notional amounts of receive-fixed/pay-variable swaps

RVSWAP: Notional amounts of receive-variable/pay-fixed swaps

TA: Total assets

§

: The mean of RFSWAP/TA is statistically different (.05 level) from that of the same number before FAS No. 133 using t-test. All

other variables are not statistically different across the pre-FAS No. 133 and post-FAS No. 133 period.

53

Table 8

Descriptive Statistics for Swap users & Non-users and Economic Effects of Swaps on NII

Panel A. Descriptive statistics for swap users and non-users

Non-swap users (1)

(N = 3,504)

Swap users (2)

(N = 546)

Difference

(1) – (2)

Number of banks

815

146

Mean

910

42,233

− 41,323

***

Median

419

10,831

TA ($ Million)

Std.

Dev.

1,616

88,318

Mean

0.0527

0.0422

0.0105

Median

0.0427

0.0422

NIM

Std.

Dev.

0.4680

0.0087

Mean

0.0233

0.1339

− 0.1106

***

Median

0.0191

0.1371

GAP1Y / TA

Std.

Dev.

0.1829

0.1665

Mean

0.1297

0.0256

0.1041

***

Median

0.1287

0.0184

LTGAP / TA

Std.

Dev.

0.1690

0.1551

NIM: Net interest margin

GAP1Y: 1-year maturity gap

LTGAP: Long-term gap

TA: Total assets

***

Significant at the 0.01 level for a two-tailed t-test

54

Panel B. Economic effects of swaps on NII

Variable

N

Q1

Mean

Median

Q3

Std.

Dev.

Interest Rate Spread

RF Swaps (%)

58

0.339

1.384

0.806

1.70

1.549

RV Swaps (%)

58

-1.540

-0.938

-0.590

-0.01

1.195

Net effect ($million)

58

1.36

41.27

4.29

42.35

83.36

Net effect (per share)

58

0.009

0.123

0.052

0.118

0.201

Interest rate spread: The difference in interest rates between variable and fixed legs of a swap.

55

Table 9

Descriptive Statistics for Variables in Regression Model

Panel A. Descriptive statistics for variables in regression model

Variable N

Q1

Mean

Median

Q3

Std.

Dev.

∆NETSWAP 546

-0.0128

0.0053

0

0.0192

0.0427

DIFF

t

546 -0.0043

-0.0015

-0.0016

0.0016 0.0064

DIFF

t

-1

490

†

-0.0033

-0.0008

-0.0006

0.0022 0.0061

∆GAP1Y 546

-0.0421

0.0222

0.0135

0.0756

0.1331

∆LTGAP 546

-0.0566

0.0004

0.0062

0.0640

0.1263

Panel B. Pearson correlation (p-value)

DIFF

t

DIFF

t

-1

†

∆GAP1Y

∆LTGAP

∆NETSWAP

0.094

(0.028)

0.024

(0.595)

0.121

(0.005)

-0.093

(0.031)

DIFF

t

0.437

(< .0001)

-0.044

(0.309)

0.082

(0.056)

DIFF

t

-1

†

-0.086

(0.057)

0.125

(0.006)

∆GAP1Y

-0.933

(< .0001)

ASSET: Total assets

∆NETSWAP: Change in net swap positions which is the difference between RF swaps and RV

swaps, i.e., ∆(RFSWAP−RVSWAP). This variable is deflated by beginning total

assets.

DIFF: The difference between NII target and unmanaged NII deflated by beginning total

assets. Positive (negative) DIFF represents the magnitude by which unmanaged

NII misses (meets) target NII.

∆GAP1Y: Change in 1-year maturity gap deflated by beginning total assets.

∆LTGAP: Change in long-term gap deflated by beginning total assets.

†

: Correlation of DIFF

t

-1

is based on 490 observations. 57 observations are excluded from the

analysis due to insufficient data to calculate the lagged first difference in DIFF.

56

Table 10

Regression Results for H1

it

it

it

it

it

LTGAP

Y

GAP

DIFF

NETSWAP

ε

α

α

α

α

+

∆

+

∆

+

+

=

∆

3

2

1

0

1

Variable Expected

sign

Coefficient Estimate

(Standard Error)

Intercept 0.00444

(0.00206)

**

0.00534

(0.00188)

***

0.00627

(0.00186)

***

DIFF

it

+ 0.62599

(0.28399)

**

0.66044

(0.28217)

**

0.67899

(0.28366)

**

∆GAP1Y

it

+ 0.07771

(0.03784)

**

0.04017

(0.01361)

***

∆LTGAP

it

− 0.04251

(0.03998)

−0.03410

(0.01442)

**

N

Adj. R

2

546

0.0211

546

0.0209

546

0.0153

∆NETSWAP: Change in net swap positions which is the difference between RF swaps and RV

swaps, i.e., ∆(RFSWAP−RVSWAP). This variable is deflated by beginning total

assets.

DIFF: The difference between target NII and unmanaged NII deflated by beginning total assets.

Positive (negative) DIFF represents the magnitude by which unmanaged NII

misses (meets) target NII.

∆GAP1Y: Change in 1-year maturity gap deflated by beginning total assets.

∆LTGAP: Change in long-term gap deflated by beginning total assets.

***

Significant at the 0.01 level for a two-tailed t-test

**

Significant at the 0.05 level for a two-tailed t-test

57

Table 11

Regression Results for H2

it

it

it

it

it

it

LTGAP

Y

GAP

DIFF

DIFF

NETSWAP

ε

δ

δ

δ

δ

δ

+

∆

+

∆

+

+

+

=

∆

−

4

3

1

2

1

0

1

Variable Expected

sign

Coefficient Estimate

(Standard Error)

Intercept 0.00466

(0.00222)

**

0.00582

(0.00202)

***

0.00679

(0.00201)

***

DIFF

it

+ 0.68699

(0.33538)

**

0.70924

(0.33508)

**

0.71917

(0.33635)

**

DIFF

it-

1

− -0.11956

(0.35683)

-0.08203

(0.35574)

-0.07977

(0.35774)

∆GAP1Y

it

+ 0.08826

(0.04047)

**

0.04195

(0.01552)

***

∆LTGAP

it

− 0.05305

(0.04281)

-0.03319

(0.01648)

**

N

Adj. R

2

490

†

0.0190

490

0.0179

490

0.0114

∆NETSWAP: Change in net swap positions which is the difference between RF swaps and RV

swaps, i.e., ∆(RFSWAP−RVSWAP). This variable is deflated by beginning total

assets.

DIFF: The difference between target NII and unmanaged NII deflated by beginning total assets.

Positive (negative) DIFF represents the magnitude by which unmanaged NII

misses (meets) the target NII.

∆GAP1Y: Change in 1-year maturity gap deflated by beginning total assets.

∆LTGAP: Change in long-term gap deflated by beginning total assets.

***

Significant at the 0.01 level for a two-tailed t-test

**

Significant at the 0.05 level for a two-tailed t-test

†

: 56 observations are excluded from the analysis due to insufficient data to calculate the

lagged first difference in DIFF.

58