5.; $.35. 1.
f 2,“ Jun 5;?

   

 

 

. .....:,.=. . .4. ‘.

 
 

law

5.3% ....,..

    

   
   

IT.»
2...? .

 

 

 

maul
l
7):: 1
6 “Bi/LIZ'J'E‘

This is to certify that the
dissertation entitled

ARE INTEREST RATE SWAPS USED TO MANAGE BANKS’
EARNINGS?

presented by
CHANG JOON SONG

has been accepted towards fulﬁllment
of the requirements for the

Department of Accounting and

Ph-D- degree in Information Systems

 

 

W\A%W

' - Wt PFofessor’s Signa‘t’ure
‘7 // /o 4

Date

 

MSU is an Aﬂinnative Action/Equal Opportunity Institution

 

LIBRARY
Michigan State
University

 

 

 

PLACE IN RETURN BOX to remove this checkout from your record.
To AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6/01 cJCIRC/DateDue.p65-p.15

 

 

ARE INTEREST RATE SWAPS USED TO MANAGE BANKS’ EARNINGS?
By

Chang Joon Song

A DISSERTATION
Submitted to
Michigan State University

In partial fulﬁllment of the requirements
For the degree of

DOCTOR OF PHILOSOPHY
Department of Accounting and Information Systems

2004

ABSTRACT
ARE INTEREST RATE SWAPS USED TO MANAGE BANKS’ EARNINGS?
By

Chang Joon Song

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 (N11). 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 N11 is below management’s target for N11.
In addition, I investigate whether banks enter into receive-vanable/pay-ﬁxed swaps to
decrease eamings when unmanaged N11 is above management’s target for N11. 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 N11 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 F ASB implements

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

Dedicated to my wife and best friend, J ihyun
and to my loving family.

iv

ACKNOWLEDGEMENTS

My very ﬁrst journey as a researcher is complete. This journey would not have
been accomplished without the incredible support from my committee: Thomas
Linsmeier (chair), K. Ramesh, Bruce Bettinghaus, and Roger Calantone. I especially
thank Tom for being patient with me and for helping me to grow as a researcher.

I am very grateful both to the other faculty members in the Department of
Accounting and Information Systems and to my PhD. student colleagues, who have
challenged me with fresh viewpoints.

Finally, I am especially thankful for the love and support of my wife, J ihyun, my
parents, J in-Hang and Kyung-Bin, my brothers, Young-Joon and Kyung-Joon, my
adorable nephews, all of my in-laws, my host family in Lansing, John, Bonnie, Jack and
Jeff, my former graduate advisor in Seoul, Professor Manwoo Lee, who show me the joy
of accounting beginning in my freshman year, Professor Jun-Koo Kang in the ﬁnance
department, Il-Joo Foundation for providing me with a scholarship for ﬁve years, and
many friends near and far who have always been there for me.

Today, I am taking the ﬁrst step of my second journey.

TABLE OF CONTENTS

LIST OF FIGURES .......................................................................................................... vii
LIST OF TABLES ........................................................................................................... viii
CHAPTER I: INTRODUCTION ........................................................................................ 1
CHAPTER II : IMPORTANCE OF NET INTEREST INCOME ....................................... 9
CHAPTER III: SWAPS AS RISK AND EARNINGS MANAGEMENT TOOLS ......... 12
l. Swaps as Interest Rate Risk Management Tools ...................................................... 12
2. Swap Valuation ......................................................................................................... 15
3. Swaps as Net Interest Income Management Tools ................................................... 20
CHAPTER IV: HYPOTHESIS DEVELOPMENT .......................................................... 23
CHAPTER V: RESEARCH DESIGN .............................................................................. 26
1. Hypothesis 1 .............................................................................................................. 26
2. Hypothesis 2 .............................................................................................................. 31
CHAPTER VI: SAMPLE AND DESCRIPTIVE STATISTICS ...................................... 33
1. Sample ....................................................................................................................... 33
2. Descriptive Statistics ................................................................................................. 34
CHAPTER VII: RESULTS .............................................................................................. 39
CHAPTER VIII: CONCLUSIONS .................................................................................. 42
APPENDIX ....................................................................................................................... 59
HEDGE ACCOUNTING FOR INTEREST RATE SWAPS PRE- AND POST-F AS
NO. 133 ......................................................................................................................... S9
BIBLIOGRAPHY ............................................................................................................. 69

vi

LIST OF FIGURES

Figure 1. Interest Rate Swap between Bank A and Bank B .............................................. 44
Figure 2. Fair Value and Cash Flow Hedges of Loans using a Swap ............................... 44
Figure 3. Cash Flow Hedge of a Variable-Rate Liability using a RV Swap .................... 44
Figure 4. Spot and Forward Rate Yield Curves ................................................................ 45
Figure 5. Relationship between Forward Rate and Net Cash Flows of Swaps ................. 45
Figure 6 Mean & Median of Notional Amount of Interest Rate Swaps as Percentage of
Total Assets from 1995 to 2002 ................................................................................ 46
Figure 7. Interest Rate Yield Curves from 1995 to 2002 .................................................. 47

vii

LIST OF TABLES

Table 1. Average US. Commercial Banks’ Income Components as a Percentage of Total

Assets ........................................................................................................................ 48
Table 2. Effective Interest Rates after using Swaps ......................................................... 49
Table 3. Spot and Forward Interest Rates ......................................................................... 50
Table 4. Cash Flows from a RF Swap .............................................................................. 50
Table 5. Expected Net Economic Effects from RF Swap at the end of Period 1 ............. 51
Table 6 Descriptive Statistics for Sample Banks .............................................................. 52
Table 7 Descriptive Statistics of Swap Usage .................................................................. 53
Table 8 Descriptive Statistics for Swap Users & Non-users and Economic Effects of

Swaps on N11 ............................................................................................................. 54
Table 9 Descriptive Statistics for Variables in Regression Model ................................... 56
Table 10 Regression Results for H1 ................................................................................. 57
Table 11 Regression Results for H2 ................................................................................. 58
Table A. Cash Flows from Assets and Swaps .................................................................. 62

Table B. Fair Values of the BankA and Bank B’s Assets & Swaps at the end of Year 1 63

Table C. Bank A’s Journal Entries before FAS No. 133 .................................................. 64
Table D. Journal Entries after FAS No. 133 ..................................................................... 65
Table E. Swaps’ Effects on N11 and Net Income Pre- and Post-FAS No. 133 ................. 68

viii

CHAPTER 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 a1, 1995; Ahmed et al.,
1999; Beatty et al., 2002). As distinct from previous studies, this study shows that net
interest income (N 11) 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 N11.

N11 is a signiﬁcant portion of earnings in banks’ income statements. In 2002, N11
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 Chapter II). In addition, Ryan (2002, p. 212) indicates that
N11 is the main source of banks’ income. Despite the signiﬁcance of N11, research has not
investigated any methods that bank managers may exploit to manage this largest
component of earnings. Given the importance of N1], 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 LLP (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. 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 Mark_e_t§ 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, BankA receives from 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 BankA,
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 yield curve is also upward sloping (see

Chapter 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

 

' 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.

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 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 the swap. If the accounting model
reﬂects this economic effect in N11, managers can exploit this opportunity to manage NII.
Past and current hedge accounting models permit reporting of the net cash ﬂows
from the swap as adjustments to reported interest revenue or expense of the hedged item.
Thus, under these hedge accounting models, the positive or negative cash ﬂow effects in
the early periods of the swap generally are reﬂected in N11 in income statements.
However, there is an additional issue in these hedge accounting models: recognition of
any changes in the fair value of the hedging instrument. 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 N11. Then, managers would not be able to ﬁrlly 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 to Financial Accounting Standard Board Statement No. 133 (F AS No.
133), Accounting Derivative Instruments and Hedging Activities,2 interest rate swaps
accounted for as hedges were not recognized at fair value (Herz, 1994).3 This hedge
accounting model recognized only periodic net cash settlements under the swap in N11.
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 value in post-F AS No. 133
periods. However, this does not mitigate the N11 management opportunity as long as
swaps are accounted for as hedges because it is also required that corresponding hedged
items’ gains or losses be recognized in earnings.4 Speciﬁcally, if a swap is designated as
a fair value hedge, changes in fair values of both swaps and hedged items are recognized
immediately 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 N11 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,

 

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 A ctivities-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.

‘ 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 I, 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.

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 N11 (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 F AS No. 133 generally does not eliminate the N11
management opportunity provided by recognizing periodic cash ﬂow settlements in N11.5
As a result, I hypothesize that banks enter into RF swaps accounted for as hedges to
manage NII upward if unmanaged N11 is expected to be below management’s target for
N11. 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 N11.

The decision to enter into swaps for N11 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

 

5 When swaps are accounted for as trading instruments, bank managers are unable to manage earnings
(either N11 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
immediately 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).

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
N11 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 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 N11 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 ﬁrst consider subsequent periods’ interest rate changes and the
new NII target before deciding on entering into new swap positions in the subsequent

period.

This dissertation 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.6 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 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. 133.7

This dissertation is organized as follows. Chapter 11 provides evidence on
importance of N11. Chapter III explains how swap instruments are used for both risk and
earnings management purposes. Chapter IV develops the hypotheses. Chapter V

introduces the research design. Chapter VI deﬁnes the sample and provides descriptive

 

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 (I) 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.

7 In December 2000, Financial Accounting Standards Board (FASB) issued a Special Report regarding
accounting for ﬁnancial instruments and similar items prepared by the Financial Instruments Joint
Working Group of standard setters (J WG). This Draft Standard proposes to measure virtually all
ﬁnancial instruments at fair value. Therefore, it provides guidance on how to recognize derivatives under
the full fair value accounting model. Consistent with the full fair value accounting for derivatives
described in this dissertation, J WG concludes that fair value gains or losses (after adjustment for swap
cash receipts and payments) are to be reported outside N1] in the income statement (F ASB, 2000b,

paragraph 137 (e)).

statistics. Chapter VII presents results. Chapter VIII provides conclusions and

implications.

CHAPTER II: IMPORTANCE OF NET INTEREST INCOME

The relative importance of N11 to bank managers is supported by several sources.
First, N11 is the main source of banks’ earnings (Ryan, 2002, p.212). Table 1 provides a
summary of average US. 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 N11 is even greater. Speciﬁcally, for these
banks LLP and SGL are only 0.54% and 0.04% of total assets, respectively, while N11 is

3.94% of total assets.

 

INSERT TABLE 1 HERE

 

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 N11 is the main source of
banks’ income (Ryan, 2002, p. 212); managers may want to ensure that N11 is stable and
growing.

Third, the relative importance of N11 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 N11. Speciﬁcally, banks are required to provide
an analysis of net interest income, which contains information about (1) the average
outstanding amounts of 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 N11 due to changes in interest rates and (2) volume effects, which represent the effects
on N11 due to changes in volume of interest-earning assets and interest-bearing
liabilities.”

Last, research evidence supports the importance of N11 as an indicator of bank’s
performance. Eccher et al. (1996) ﬁnd that N11 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 N11 is a signiﬁcant portion of earnings before SGL,
they provide additional evidence supporting the relative importance of N11 to bank
managers.

In sum, due to the signiﬁcance of N11 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

 

8 For more detailed information, see Ryan (2002).

10

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.

11

CHAPTER III: SWAPS AS RISK AND EARNINGS MANAGEMENT TOOLS9 .

l. Swaps as Interest Rate Risk Management Tools

Suppose BankA issues a $1 million ﬁxed-rate (11.85%) loan and Bank B issues a
$1 million variable-rate (I-year LIBOR) loan. Since BankA’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, BankA’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, ﬁrture cash ﬂows
will ﬂuctuate with changes in the interest rate. Thus, Bank B primarily is exposed to cash
ﬂow risk.

To hedge these risks, BankA 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 l-year LIBOR on the
same notional amount to BankA. The net payments are agreed to be exchanged at the end

of every year. This swap is summarized in Figure 1.

 

INSERT FIGURE 1 HERE

 

 

9 See Song (2002) for a comprehensive literature review regarding (1) economic effects of risk
management, (2) past and current hedge accounting standards, and (3) previous studies related to each of
these standards.

12

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 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.

 

INSERT FIGURE 2 HERE

 

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.

13

 

INSERT TABLE 2 HERE

 

F ixed- or variable-rate liabilities also can be hedged using swaps. Figure 3
provides an example of a liability hedge. Suppose BankA has a $1 million variable-rate
(l-year LIBOR) liability and Bank B has a $1 million ﬁxed-rate (11.85%) liability.
Therefore, BankA’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 BankA and Bank B can hedge their
risks. As described in Figure 3, the RV swap effectively converts BankA ’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.

 

INSERT FIGURE 3 HERE

 

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

14

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 oftenattempt 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.

2. 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 ﬂows from BankA (Bank B) at the end of Year I by entering into RF

(RV) swaps. The reverse is true if the interest rate yield curve is downward-sloping. To

 

'0 See yield curves from 1995 to 2002 in Figure 7, Chapter VI.

15

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 annurn 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.ll Sometimes the n-

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

 

INSERT TABLE 3 HERE

 

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: (I) 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 second year forward rate is the

 

" Assuming annual compounding. $1,000, 000x (1 + 0.11)2 - $1,000,000 = $232,100-

16

estimate of the second year’s one-year spot rate. This guarantees that the following

equations will hold.

<1+rz)’=(1+rl)-(1+1r2) (1)
(l+r3)3=(l+r])-(l+lr2)-(l+2r3) (2)

where, r] , r2 and )3 represent current spot rates for l-year (=10%), 2-years (=11%), and

3-years (=12%), respectively. Also, ir j is a forward rate deﬁned as the expected l-year

spot interest rate for year j as of the end of year i. For example, 1"2 represents Year 2’s

expected l-year spot rates as of the end of Year 1. 1’2 is 12.01% from equation (1),

implying that the expected l-year spot interest rate at the end of the Year 1 is 12.01%.

Similarly, 213 is 14.03% which is the one-year 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). ’2

 

INSERT FIGURE 4 HERE

 

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

 

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

17

the third column of Table 4.13 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.14

 

INSERT TABLE 4 HERE

 

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 I? be the Bank B’s ﬁxed cash inﬂow from the swap. Then,
equation (3) should hold. Thus, It- is $118,500, which means the ﬁxed coupon-interest

rate of the swap is 11.85%.

(IT—100,000) + (IT-120,100) + (IF—140,300) _
(1+0.l) (14.0.11)2 (14.0.12)3

 

0 (3)

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

 

'3 It is assumed that there is no credit risk.
" Hull (1997), p. 112.

18

following statements about the swaps are always true:'5 (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 for the swap. In general, if the
ﬁxed interest rate is set at a % as shown in Figure 5, the expected RF swap payments up
to period t will generate positive not 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.

 

INSERT FIGURE 5 HERE

 

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.'7 At the end of Year 1, Bank B receives a positive net cash ﬂow of $1 8,500

from Bank A, but the present value of Bank B’s commitment to pay cash ﬂows to Bank A

 

'5 The reverse is true when yield curve is downward sloping.

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

'7 At the end of Year 1, I-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 l-year spot interest rate as expected,
and (2) Year 3’s forward interest rate remains the same as before.

19

in years 2 and 3 is $18,500. Thus, there are no net economic effects for either BankA or

Bank B from the swap.

 

INSERT TABLE 5 HERE

 

However, if the variable interest rate moves unexpectedly, net effects could be
either positive or negative depending upon the direction of the interest rate change. This

' implies that the net economic effects of a swap are uncertain, creating interest rate risk.

3. 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 settlements under the swap as adjustments to reported
interest revenue and expenses of the hedged item. 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. BankA (Bank B)

effectively converted a ﬁxed-rate (variable-rate) loan into a variable-rate (ﬁxed-rate) loan

20

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.’8

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 F AS 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 N11 to reﬂect the change in net interest rate effectuated by the swap

without any signiﬁcant countervailing effect on reported net income.

 

1: If the yield cure is downward-sloping, a RF (RV) swap will decrease (increase) earnings in the early
periods of the swap contract.

21

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 both required to be recognized in net income (not NII). Therefore, the
two effects can offset because there are no counteracting gains or losses that will be
recognized on designated hedged items. 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.19 Because the
accounting treatment for new swap acquisitions under the full fair value accounting is
identical to the accounting for trading swaps under the current partial fair value hedge
accounting model, the N11 management opportunity would be lost if FASB were to adopt

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

 

'9 The cash settlement and fair value effects are reported outside Nll. Therefore, trading swaps also provide
no opportunity to manage N11.

22

CHAPTER 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 Chapter 111, 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 not swap
cash settlements are reported in N11 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
(negative) effect of RF (RV) swaps on N11 to manage earnings. Speciﬁcally, banks will
enter into RF swaps if they anticipate that unmanaged NIl will be less than management’s
target for N11. In contrast, if the current year’s unmanaged NII exceeds targeted N11,
managers may want to defer N11 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).

23

H1: After controlling for investments in RF and R V swaps for risk
management purposes and assuming an upward sloping interest rate yield
curve, (I) if unmanaged N11 is below management ’3 target for NI], banks
will enter into additional RF swaps to increase current N11, or (2) if
unmanaged NII exceeds management’s target for N11, banks will enter
into additional R V swaps to defer current N11 to future periods.

Using swaps for N11 management purposes is not costless, however, because the
N11 management swaps will move banks’ swap portfolio away from the amount desired
for risk management purposes.20 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 3 N11 management swap contract.
Thus, instead of 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.

 

2° Conversations with derivative dealers indicate that transactions costs are only 2 basis points (.0002) of
the notional amount of the swap contract.

24

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 N11, they will enter
into oﬂsetting swap positions in the subsequent period to mitigatethe

interest rate risk induced by entering into swaps for earnings management
purposes.

25

CHAPTER V: RESEARCH DESIGN

1. Hypothesis 1

To test HI, I estimate the following model:

ANETSWAPi, = a0 + a1 DIFF}, + azAGAPlYi, + a3ALTGAP,-, + 3,, (4)

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

A(RFSWAP-RVSWAP), where RFSWAP (RVSWAP) is notional
amounts of RF swaps (RV swaps). ANETSWAP is deﬂated by
beginning total assets.

DIFFi, : difference between NII target and unmanaged N11 for bank i in

period t deﬂated by beginning total assets (a more precise
deﬁnition is provided by equations (5)-(9)),
AGAPlYi, : Change in l-year GAP for bank i in period t deﬂated by beginning

total assets.
ALT GAP” : Change in long-term GAP for bank i in period t deﬂated by

beginning total assets.

To explain changes in net swap positions, I ﬁrst introduce two variables
(AGAPlY and ALTGAP) 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.2| GAPlY and LTGAP are deﬁned as the

differences between interest-earning assets and interest-bearing liabilities that will

 

2' 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, I996; 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, 1 do not include these variables in equation (4).

26

respectively mature or reprice within one year or subsequent to one year.22 Positive
(negative) GAPlY 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) GAPIY and LTGAP at year t-I are positive, and (2)
AGAPIY and ALTGAP increase. Since during period t both GAP positions moved
further away from zero when compared to the positions at period t-I, 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 reprice within one—year require
frequent resetting of the instrument’s interest rates, a positive AGAPIY 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 ALTGAP 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

 

22 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.

27

increased fair value sensitive net assets into cash ﬂow sensitive net assets. When the
signs of AGAPIY and ALTGAP 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 GAPIY 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 AGAPIY or ALTGAP, respectively. Therefore, I use net
swap positions as the dependent variable in equation (4) instead of total notional amounts
of swaps.23 The net swap position is deﬁned as the difference in notional amounts
between RF and RV swaps. As stated previously, I expect that positive AGAPlY
(ALTGAP) to be associated with positive changes in RF (RV) swaps. This implies that
AGAPIY (ALTGAP) is positively (negatively) associated with changes in net swap

positions, ANETSWAP. Thus, I predict a2 and £13 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 N11 management purposes.
To test whether bank managers appear to enter into RF and RV swaps for N11
management purpose, I ﬁrst must identify the direction and amount by which NII needs
to be managed to meet targeted NII. As deﬁned in equation (5), this is measured by the

difference between the N11 target (NIIT) and unmanaged NII (UNII).

 

2’ 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.

28

DIFFi, = N117}, — W11” (5)
N117}, = N1M,,_l ~AEA,-, (6)

where, N117}, : net interest income target for bank i in period t
UNIIi, : unmanaged net interest income for bank i in period t
NIM,,_1 : net interest margin percentage (N II/average interest-earning
assets) for bank i in period t-I
AEA;, : 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 (N117},) on the prior year’s net interest margin
percentage (N1M,-,_1).2" In speciﬁc, to control for annual changes in the net earning
assets of sample banks, NIIT“ is estimated in equation (6) by multiplying prior year’s
NIM,,_1 by current year’s average earnings assets (ABA), ). If UNII is less than NII

target, HI predicts that bank managers will use RF swaps to manage NII upward.
Similarly, if UNII is greater than reported NII, then H] predicts that bank managers will

use RV swaps to manage NII downward.

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

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

(NIMiq) on the average historical quarterly industry NIM (INDNIMq ).

NIMiq = pm + ,BUINDNIMq + 5,, (7)

where, NIMiq: net interest margin percentage (N II/average interest-earning

assets) for bank i at quarter q
INDNIMq: industry average net interest margin percentage in quarter q

 

2‘ Net interest margin is deﬁned as ratio of N11 to average earning assets. 1 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 N11 to same amount in the prior period when assessing bank performance.

29

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.25 Equation (7)

derives Bu , which captures the ﬁrm Speciﬁc NIM sensitivity to industry average NIM.

Each bank’s unmanaged NIM (UNIMH) then is obtained by plugging the estimated betas

from equation (7) and the test period’s quarterly industry average NIM into equation (8).

.— 4 A A
UN1M,-t = 2 (,6,0 + ,Bi’llNDNIMq) (8)
(H

where, UNIM 11: predicted value of unmanaged net interest margin for bank i at
year t

INDNIMq: industry average net interest margin percentage in 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-

eaming assets to get UNII as in equation (9).

UNI!“ = UNIMu -AEA,-, (9)
where, UNIIi, : unmanaged net interest income for bank i at year t

UNIMu: predicted value of unmanaged net interest margin for bank i at
yeart

AEAi, : 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 (UN 11) and is used to deﬁne the degree to which bank

 

25 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.

30

managers seek to manage NII. If banks manage NII using swaps, DIF F should be
associated with the ANETSWAP (A(RFSWAP-RVSWAP)) position after controlling for
changes in swaps due to risk management purposes. If the DIFF is positive, it implies that
banks have an incentive to manage NII upward by increasing RF swap positions.
Increasing RF swap positions causes a positive ANETSWAP and, therefore, a positive
coefﬁcient on DIFF. Similarly, a negative DIFF implies that banks have an incentive to
manage NII downward by decreasing their ANETSWAP (by increasing RV swaps),
which again suggests a positive coefﬁcient on DIFF”. Thus, to test HI, I assess whether

a] in equation (4) is positive.

2. Hypothesis 2

H2 predicts that after increasing swap positions for N11 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 DIFFi,_1

to equation (4).

 

2" The test documented in the text assumes increases in net swap positions can occur by either entering into
RF swaps or failing to replace matured RV swaps. Similarly, decreases in net swap positions are assumed
to occur by entering into RV swaps or failing to replace matured RF swaps.

31

ANETSWAP” = so + 5101”}, + 52 DIFF,H + 63AGAP1Y,, + 64ALTGAP,, + 5,, (10)

where: ANETSWAP: Change in net swap positions, i.e., A(RFSWAP-RVSWAP), where
RFSWAP (RVSWAP) is notional amounts of RF swaps (RV
swaps). ANETSWAP is deﬂated by beginning total assets.
DIF F: NII target — Unmanaged NII deﬂated by beginning total assets,
AGAPIY: Change in l-year GAP deﬂated by beginning total assets.
ALTGAP: Change in long-term GAP deﬂated by beginning total assets.

DIFF,“ is used to assess if banks manage their NII upward by entering into RF

swaps at t-I, whether banks also enter into RV swaps at t to offset the N11 management

effects in subsequent periods. If this is true, then DIFF},_1 should be negatively
associated with ANEI’SWAP,, . Similarly, if banks manage their NII downward by
entering into RV swaps at t-I, then DIFF},_1 should be negatively associated with

ANE T SWAP,, 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 62 to

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

offsetting swap acquisition, 52 will be zero. The expected signs on the other variables

are the same as in equation (4).

32

CHAPTER VI: SAMPLE AND DESCRIPTIVE STATISTICS

1. 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 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

33

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.

2. 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 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

 

34

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 the 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 F AS 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, 1 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.

 

INSERT TABLE 8 HERE

 

35

I also compare maturity gaps between users and non-users. Swap users’ GAPlY
(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’ GAPlY and LTGAP are both positive,
GAPIY 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., GAPIY. 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 N11 management uSing either RF or RV swaps depends on
whether interest rate 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, l-year, 3-year, 5-year, and lO-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

 

36

Given the general upward sloping interest rate yield curves, I estimate the
potential change in N11 from entering into swaps during the sample period. To compute
this estimate, I multiplied the difference in interest rates between the ﬁxed and variable
legs of sample ﬁrms’ swaps by the annual change in the notional amount of swaps for the
period.27 In this calculation, I do not separate out the income effects of swaps used for
risk management and earnings management purposes. Results are reported in Panel B of
Table 8. For banks having positive net effects of swaps on N11, the mean dollar
magnitude of the net effect is $18 million. On average, these banks increase NII by 8
cents per share using swaps. Similarly, for banks having negative net effects of swaps on
N11, the mean dollar magnitude of the net effect is negative $16 million. These banks, on
average, decrease NII by 6 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 ANETSWAP is 0.5% of
beginning total assets. Average AGAPIY and ALTGAP are 2.2% and 0.04% of
beginning total assets, respectively. Average DIFF is -0.15% of beginning total assets.28
Panel B of Table 9 shows pairwise correlations among variables. Consistent with
hypothesis 1, ANETSWAP is positively (negatively) associated with AGAPIY
(ALTGAP). In addition, the pairwise correlations between AGAPI Y and ALTGAP and

DIFF, and DIFF,_1 are ~0.93 and 0.44, respectively. Both these correlations are

statistically signiﬁcant, suggesting potential multicollinearity problem. To assess the

 

27 In this calculation, 1 use current swaps’ weighted average ﬁxed interest rates. The estimated economic
effects of decreased swaps may not be accurate because information about ﬁxed interest rates is absent
for swaps that no longer exist.

28 For the majority of sample banks, the NIM betas used in to estimate DIF F are positive and statistically
signiﬁcant. However, estimated ﬁrm-speciﬁc NIM betas have a large cross-sectional variation. Sample
banks’ mean NIM beta and standard deviation are 0.08 and 0.17, respectively.

37

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 D] F}, , AGAPII’,, and
LT GAP,, in equation (4) are 1.02, 7.75 and 7.79, respectively. The VIF values for

DIFP},, DIFP},_1, AGAPIY,, and LT GAP” 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
AGAPIY and ALTGAP may be affected.29 Due to this concern, I ﬁrst test the compound
effects of the risk management variables by testing whether AGAPIY or ALTGAP 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

AGAPIY or ALTGAP only.

 

INSERT TABLE 9 HERE

 

 

29 However, the low VIF for DIFF suggests that the high degree of correlation between AGAPI Y and
ALTGAP will not cause bias in DIF F coefﬁcient (Wooldridge, 1999).

38

CHAPTER 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 (AGAPlY and ALTGAP), and the
other relating to N1] management (DIFF). In terms of the risk management variables,
equation (4) predicts changes in net swap positions are positively and negatively
associated with AGAPIY and ALTGAP, respectively. For equation (4), the coefﬁcient on
AGAPlY is signiﬁcantly positive, but the coefficient on ALTGAP is positive and not
statistically signiﬁcant. However, as mentioned in Chapter VI, there are signiﬁcant
collinearity issues with the AGAPIY and ALTGAP variables. To better isolate the sign
and statistical signiﬁcance of these two variables, I ﬁrst test whether AGAPIY and
ALTGAP are jointly signiﬁcant. The associated F-test indicates signiﬁcance at the 1%
level. I also estimate two separate regressions that only included either AGAPIY or
ALTGAP. Individual coefﬁcients on the risk management variables in these regressions
behave as predicted. The coefﬁcients on AGAPIY and ALTGAP are signiﬁcantly
positive and negative, respectively. The joint results, therefore, indicate that net swap
positions are positively and negatively associated with AGAPIY and ALTGAP,

respectively, suggesting that banks change their net swap positions for risk management

purposes.

 

INSERT TABLE 10 HERE

 

39

Given this risk management relationship, I next examine whether banks also
manage net swap positions for N11 management purposes. The coefﬁcient on DIFF is
positive and signiﬁcant 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 HI .

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 N11 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 AGAPlY is signiﬁcantly positive,
but the coefﬁcient on ALTGAP is positive and not statically signiﬁcant. An F-test
indicates that AGAPIY and ALTGAP are jointly Signiﬁcant at 5% signiﬁcance level.
Similarly, individual coefficients on AGAPIY and ALTGAP 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 AGAPI Y or ALTGAP

remains the same as before.

 

INSERT TABLE II HERE

 

In terms of the DIFF variables, the coefﬁcient on DIF F remains positive and
signiﬁcant, again suggesting that sample banks acquire swaps to manipulate current

period NII. In regards to H2, however, the coefﬁcient on lagged DIFF is negative as

40

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.

41

CHAPTER 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 N11 is below management’s target for N11, banks increase investments in RF
swaps to increase NII. Similarly, I provide evidence suggesting that if unmanaged N11 is
above management’s target for N11, banks increase investments in RV swaps to defer N11
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 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

42

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.

43

Figure 1. Interest Rate Swap between Bank A and Bank B

 

Bank A

 

11.85% X $1 million

‘

 

 

 

 

 

LIBOR X $1 million

 

Bank B

 

 

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

 

11.85%X $1M

 

Loan

 

Bank A

11.85% X $1M

 

 

 

‘LIBOR x $1M

 

 

Fair Value Hedge

 

Bank B

LIBOR X $1M

 

Loan

 

 

Cash Flow Hedge

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

 

 

LIBOR X $1M

V

 

Liability

 

Bank A

11.85%X$1M

 

A

LIBOR X $1M

 

 

 

Bank B

11.85%X$IM

 

 

 

 

Cash Flow Hedge

44

Fair Value Hedge

'

Liability

Figure 4. Spot and Forward Rate Yield Curves

 
    

 

 

A Rate
14.03%
Forward Rate
12.01%
Spot Rate
12%
10%
l l 1 4' Time to maturity
l-year 2-year 3-year

Figure 5. Relationship between Forward Rate and Net Cash Flows of Swaps3o

 

 

 

A Forward
rate
Upward-
sloping
yield curve
a % ’

Positive Negative

Net Net

Cash Flows Cash Flows

Maturity

 

I

 

3° Hull (1997), p. 125.

45

53>
NOON room Doom . mam r mam _. now P 0mm w

p P b F L! b P

2582 a<>>m>m Tl-\-/ullil-\-ll.l-

llllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll

    

Z<m$_ m<>>w>m

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

ZSDMS. n_<>>wn_m

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

llllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll

Z<m_2 n_<>>wn_m

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

Z<_Dms_ n_<>>w>m III
Z<w_2 n_<>>w>m IT

Z<_Dms_ n_<>>wn_m I
Z<m_2 m<>>wmmlol

rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr

..-_.o.o

 

-mod

-wod
4... ~ £55m.
bod
-mod

$0.0

 

rmod

«can 3 mag So...— 5094 .5313 oust—33A— ? maakm 3mm :28:— ue «55:2. .235: Z me 5:52 an :32 e 9...»:—

46

 

 

NOON ll
FOON IT
OOON IOI
OOOr lxl
OOOFI+TI
NOOr +
OOOrIﬁTI
OOOF 1.1

 

areas.
39.8 58$ 58>.” .8: 582A.

£82-”

 

ll 7

 

 

 

 

 

 

.. . . OOON.

NOON . OOOF
.i>r . lllltxiinnnnnnnnnnnu

Eco .1 I OOOP ,
88 xllllilixlllllixlllll

OOO w

KOO w
mOO F

88 s 32 EE. 8:5 22> Sam .85.: a. ESE

 

(%) mu 189mm

47

Table 1. Average US. Commercial Banks’ Income Components as a Percentage of

 

 

 

 

 

 

 

 

 

 

 

Total Assets
Medium Sized
Banks
All Banks 10 Largest 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 US.
Commercial Banks in 2002,” June 2003. The statistics are based on regulatory
call report; thus represent commercial banks, not bank holding companies.

 

48

Table 2. Effective Interest Rates after using Swaps

 

 

 

 

 

 

Year 1 Year 2 Year 3

LIBOR 10.00% 12.01% 14.03%

Loan Interest Inﬂows 11.85% 11.85% 11.85%

BankA Swap-Receive Variable 10.00% 12.01% 14.03%
Swap-Pay Fixed (11.85%) (11.85%) (1 1.85%)

Effective Int. Rate 10.00% 12.01% 14.03%

Loan Interest Inﬂows 10.00% 12.01% 14.03%

Ban k B Swap-Receive Fixed 11.85% 1 1.85% 11.85%
Swap-Pay Variable (10.00%) (12.01%) (14.03%)

Effective Int. Rate 1 1.85% 11.85% 1 1.85%

 

 

49

Table 3. Spot and Forward Interest Rates

 

 

 

 

 

 

 

 

 

 

 

 

Spot rate for n-year investment Forward rate for nth year
Year (n) o o
(/o per annum) (/o per annum)
l 10%
2 1 1% 12.01 %
3 12% 14.03%
Table 4. Cash Flows from a RF Swap
Expected . Expected PV of
Date 1:333]? Variable Eégﬁthﬂilgzd Net Net Cash
Cash Outﬂows Cash Flows Flows
Jan. 1, Year 1
Dec.3l, Year 1 10.00% $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 $ 031

 

 

 

 

 

 

3' 18,500+ -l,600 + —21,800

=0(rounding error)
(1+0J) (140.11)2 (1+0.12)3

50

 

 

an; 05 .«o Spam 38285 “0 Z

”223+: «283+:

8:0 OE .58 . I u +
A .e Coon M: Seal 80.7 a

 

 

 

 

 

 

 

O O
OOmd 5 _ 30> Jm .009 «a 953:: :80 O0N=e0m
”38.3% I So..— 02e> ham
ONOKE I 8ng I OOm.w~ E OOmdzm 38.3 m 30> .3003
Owe; m I OOO; m I OOm.w:O OO_.ON_O .XLO.N~ N 30> ._m.o0Q
“Rama — QQ we 032m :80 0269: :30 950530 :80 moms 0
E :80 “02 ~02 35m 3803mm 0Eeta> ORB—om 3Q
.«o >m . Buoomxm

 

 

a 8:0.— 3 Ea 2.. 3 92am .5— 220 385 25:85 .02 Begum .n asap

5]

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) (29
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
1 996 84
1 997 90
1 998 83
1999 77
2000 66
2001 70
2002 76
Total 546

 

52

.6203 mm _ .oZ m<m¢mon 98 mm _ .oZ m<m05 05 00200 5000me bﬁotmuﬂm
Ho: 03 003.20? 560 =< $.03 mam: «.2 .02 m<m 3809 0098:: 080m 05 .3 ~05 Boa £0.5— nOO «500:3 b.3338» mm <Em<3mmd «o 505 0E. .

$00.00 33. 2Q.

3026 vexu$08030t0>0>m002 no 85580 3:232 nm<>>m>m
8030 oﬁagiaaéoxuiozooﬂ mo 85580 .08qu ”.2255—

 

 

 

 

 

wmmOO 38d Omvod .>0Q .Bm

mOOOO MOOOO OVOOO 5:002

h Nod OONOO OONOO 502 <H \ m<>>m>m
OOOOO OOmOO mOwOO .>0Q .Bm

SNOO OhSO ~NmOO 5:002

wmvod KOVOO nOmOO :82 «a. \ macaw:
stun Nm ~ 6 End .>0Q .05

N N Om 5:002

08; 3.2 an: as: €252 O .230?
mam}; OOON— OSJL .>0Q .Em

OON Sﬁ O N .8602

$3 $5 $3. 532 82:3 8 @2500
an u E a: n E 89. u E
NOON 80> mm _ .oZ m<m 00% mg .02 m<m 0080mm

mm N .62 min». new? .050 3&me siege. SNSNEEE méaumuoemQ .m 32ko

VNVOO Ovood ~ON0.0 8% <._. \ m<>>m>m

Nmnod wONOO VNmOO cam sad. \ mask/mum

m3.w ON mNO; can €252 @ m4?m>m

can: 8m 08.4 0% 32:22 a Rama
.>0Q .2m 00:00.2 502 Z

 

omen: EEO no Btuuﬁm game—08¢ b 03:.

.255. Lo\wo.:n.:8a. estawtcmeQ .V 320%

53

ea: 3:353 a as as: 5.0 as a 68035
$0000 3on1 ”<H

new Enouiwaoi— ”$09.4

new 3508 .80»; £5.20

EOE: 00000:: “02 ”SEA

 

 

Em O .O OOONO .>0Q .Em
«am—OO SNOO 5602
:. $36 386 SNOO 502 <9 \ A29:
EEO ONwHO .>0Q .Em
Kmﬁd EEO 5:002
503 mo I mmwﬁo MMNOO 502 and. \ >E<O
386 owned .>0Q Em
NN¢OO >N¢OO $602
386 Need NNmOO 502 3:2
£3» £0; son .05
5:: a? 5602
5834 1 mas. o; 50: €252 a 5
9: mg 9.53 we SEE—Z
6 l 3 6% u a $03 .1. 7O
0050.“me NO 0000.: 925m A: 0003 9030-52

 

numwsieo: ES .200: Rosa. Lo\uo.:§80 SEAIQEQ .V Beck

M—z :0 mﬁagm .«G 300:” GEO-=5”..— ﬁﬂa whom-7:62 a Puma: 96.5% 5G.“ magnum—5w 0>3ﬂtom0n w O—A—HH

£>m->>~c+§-&€ ”88% 38 323,: “oz
385 >m mo 88 68qu Bxc ”Era
mama >m .«o 38 3283 033.5» n>>m
madam mm mo 38 $885 0735; 5mm
39% mm mo SE 3.98:: comm “mud
885m >m E 356:8 38:8 5 mow—3:0 Hm<>>m>m<
393 mm 5 356:8 3:28: E newsman. ”gammy? 63:3

.E>¥>>€xm<3m>ms+z>§¢gxﬁamga 8% “oz

 

 

 

:5 So. So- 8.? So- 9: 33% 55 “8&0 “oz
2 S- _- 8- c. an eoéaa “8&0 .02
«3 who N3 «.3 £3- a: g 32% as 3.825 62
$3 2- a. a. a. 3 “2358/2 oﬁawoz
& .o 85 . 85 mod 82. E 33%, .2: some .02
E s N M: S E Eczema some $2
a? no mg 2.0 woo- E 33 32% 22 3.225 :2
mad mg o: 33 : E “Eamemz’u 358m
son .3 8 EB: :32 5 z 2&5, =2 8 38%

 

Q2 :0 395% 8.8%» SESSQM .m 323%

5
5

Panel A. Descriptive statistics for variables in regression model

Table 9 Descriptive Statistics for Variables in Regression Model

 

 

 

 

 

Variable N Q1 Mean Median Q3 Std. Dev.
ANETSWAP 546 -0.0128 0.0053 0 0.0192 0.0427
DIFF} 546 -0.0043 -0.0015 -0.0016 0.0016 0.0064
DIFF,_, 490* 0.0033 -0.0008 -0.0006 0.0022 0.0061
AGAPIY 546 -0.0421 0.0222 0.0135 0.0756 0.1331
ALT GAP 546 -0.0566 0.0004 0.0062 0.0640 0.1263

Panel B. Pearson correlation (p-value)
DIFF, DIFFH 1 AGA P1 Y ALTGAP
0.094 0.024 0.121 -0.093
METSWAP (0.028) (0.595) (0.005) (0.031)
0.437 -0.044 0.082
DIFF’ (< .0001) (0.309) (0.056)
1 -0.086 0.125
D [F FH (0.057) (0.006)
-0.933
AGAPIY (< .0001)
ASSET: Total assets

ANETSWAP: Change in net swap positions which is the difference between RF swaps
and RV swaps, i.e., A(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) DIF F represents the magnitude
by which unmanaged NII misses (meets) target NII.

AGAPIY: Change in l-year maturity gap deﬂated by beginning total assets.

ALTGAP: Change in long-term gap deﬂated by beginning total assets.

T: Correlation of DIFF}_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

 

Variable Expected sign Coefﬁcrent Estlmate

 

 

(Standard Error)
Intercept 0.00444" 0.00534'" 0.00627"“'
(0.00206) (0.00188) (0.00186)
DIFE-z + 0.62599“ 0.66044“ 0.67899“
(0.28399) (0.28217) (0.28366)
AGA p] y“ + 0.07771" 0.04017‘”
(0.03784) (0.01361)
ALTGAP“ 0.04251 —0.03410”
(0.03998) (0.01442)
N 546 546 546
Adj. R2 0.0211 0.0209 0.0153

 

ANETSWAP: Change in net swap positions which is the difference between RF swaps
and RV swaps, i.e., A(RFSWAP-RVSWAP). This variable is deﬂated by
beginning total assets.

DIFF: The difference between target N11 and unmanaged NII deﬂated by beginning total
assets. Positive (negative) DIFF represents the magnitude by which
unmanaged NII misses (meets) target NII.

AGAPlY: Change in l-year maturity gap deﬂated by beginning total assets.

ALTGAP: Change in long-term gap deﬂated by beginning total assets.

:I' 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

ANETSWAP” = 60 + 61DIFFi, + 62DIFFi,_1 + 53AGAP1YI, + 5,;ALTGAP” + 81°,

 

Coefﬁcient Estimate

Variable Expected sign

 

 

(Standard Error)
Intercept 0.00466" 0.00582'" 0.00679‘"
(0.00222) (0.00202) (0.00201)
mm + 0.68699” 0.70924” 0.71917"
(0.33538) (0.33508) (0.33635)
DIF5,_, — -0.1 1956 -0.08203 0.07977
(0.35683) (0.35574) (0.35774)
AGAplyit + 0.08826“ 0.04195‘”
(0.04047) (0.01552)
ALTGAP” — 0.05305 0.03319"
(0.04281 ) (0.01648)
N 490* 490 490
Adj. R2 0.0190 0.0179 0.0114

 

ANETSWAP: Change in net swap positions which is the difference between RF swaps
and RV swaps, i.e., A(RFSWAP-RVSWAP). This variable is deﬂated by
beginning total assets.

DIFF: The difference between target N11 and unmanaged NII deﬂated by beginning total
assets. Positive (negative) DIF F represents the magnitude by which
unmanaged NII misses (meets) the target NII.

AGAPlY: Change in l-year maturity gap deﬂated by beginning total assets.

ALTGAP: Change in long-term gap deﬂated by beginning total assets.

m Signiﬁcant at the 0.01 level for a two-tailed t—test
" Signiﬁcant at the 0.05 level for a two-tailed t-test

T: 56 observations are excluded from the analysis due to insufﬁcient data to calculate
the lagged ﬁrst difference in DIFF.

58

APPENDIX

HEDGE ACCOUNTING FOR INTEREST RATE SWAPS
PRE- AND POST-F AS NO. 133

59

A. Before the Adoption of FAS No. 133
Before the adoption of F AS No. 133, there was no level (a) authoritative
accounting guidance for interest rate swaps (Herz, 1994).” 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;1-1erz, 1994):

0 Swaps not designated as hedging instruments are recorded at fair value in
balance sheet and changes in fair values are recognize as unrealized gains or
losses in net income (not N11).

0 For swaps designated as hedge instruments,

0 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.

0 Gains or losses from the 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 F AS No. 133 is that derivative
instruments should be measured at fair value, because fair value is the most relevant

attribute for derivative ﬁnancial 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 ’3 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.

60

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) N11 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 on earnings from (2) is limited to 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) N11 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

derivative is recognized in earnings immediately.

C. Example

As initially presented in Chapter III, suppose that (1) BankA has $1 million of 3-
year, variable-rate (l-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

6]

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 is a RF swap for BankA 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:
D t Jan. 1,Yearl Dec.3l,Yearl Dec.31,Year2 Dec.3l,Year3
a 8 Cash Flows Cash Flows Expected CF Expected CF
Spot Rate 10% l 1.00% 12.00%
Forward Rate 12.01% 14.03%
B Variable-Rate 100,000 120,100 140,300
A Asset (1 ,000,000)35 1,000,000
2 Swap-Rec. Fixed 118,500 118,500 118,500
Swap-Pay Var. (100,000) (120,100) (140,300)
A
Total (1,000,000) 1 18,500 1 18,500 1,1 18,500
B . 118,500 118,500 118,500
A F‘xed'Rate ASS“ (1 ,000,000)36 1,000,000
ﬂ Swap-Rec. Var. 100,000 120,100 140,300 4
Swap-Pay Fixed (1 18,500) (118,500) (118,500)
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 F AS 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

100,000 120,1002 +1,140,300 =1,000,000
(1+0J) (1+0.11) (1+0.12)

36

118,500 118,500 "”8’500=1,000,000

+ +
(1+0J) (140.11)2 (1+0.12)3

62

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Dec. 31, Year 2 Dec. 31, Year 3 . .
Date Expected CF Expected CF Fair Value Gain/Loss
Spot Rate 12% 13%
Forward Rate 14.01%
Variable-Rate 120,000 140,100
B Asset 1,000,000 1,000,000 0
I131 Swap-Rec. Fixed 118,500 118,500
K Swap-Pay Var. (120,000) (140,100)
A Swap-Net (1,500) (21,600) (18,268)37 (18,268)
Total 118,500 1,118,500 981,732 0C1 (18,268)
. 118,500 1 18,500
B F‘Xed'Ra‘e Asset 1,000,000 981,73238 (18,268)
g Swap-Rec. Var. 120,000 140,100
K Swap-Pay Fixed (118,500) (118,500)
Swap-Net 1,500 21,600 18,268 18,268
B
Total 120,000 140,100 1,000,000 N3

 

 

Table B. Fair Values of the Bank A and Bank B’s Assets & Swaps at the end of Year 1

Before adoption of FAS No. 133, BankA’s journal entries for Year 1 are provided
in Table C. Since prior to F AS 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 N11.

 

37 -1,500 + —21,600
(1+0.12) (1+0.13)2
38 118,500 +1,118,500
(HO-12) (140.13)2

 

= —18, 268 (rounding error)

 

= 981, 732 (rounding error)

63

 

 

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

 

01-01-Year 1 12-31-Year l
Assets 1 ,000,000 Cash 1 00,000
Cash 1,000,000 Interest Revenue 1 00,000
(Record investment) (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] 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.39 If swaps
are not designated as a hedge, the income statement effects of the swap affect net income
not NII. Moreover, changes in fair value of swaps mitigate the earnings increasing effects
from net cash settlements under the RF swap on net income. Speciﬁcally, BankA 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 BankA’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 fair 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.

64

 

$3.5» vna 8nd; 5050: 0880.90 05 00:00 mownunu 000.. 0000005 0800985 000E. ..x._c.3 one $2 0.3
0008 32005 0.8308 one «one 1300 £30532 633.3 vna $8.2 on 8 300098 0.3 m 30> ona N 80> nm 0008 000085 30308 one «on» 625005 Q85 2 8

 

man 62 man.— Lotn mow—«Em 13.52. .9 05.;

 

 

 

 

 

 

 

 

 

 

 

 

 

$8.05 Go
898— E 8nd— _ E «3.8— E
”cud. @030. no Saw 03:00.33 NR 0888 «08005.82
83.x C 8080 no 00.2 03:00.53
088E $0085.52
83x: :2 cad— _ :2 25.9: :2
Send 3 08095 0080an 8m.m: 0338 0000005 Sodo— 0nn0>0m «308E
8m.w_ _ 030.00 000003
308035 0885 E08806 0835 608036 08an
Am 030,—. 000 do?” no 03? HE @5093
3&5 n85. no ﬂow cod—00.53 Am 055. 000 £an .3 02? new c.5005
8&5 0Ea2000¢ naBm mead. 03.33 903m
3&5 . 50
Am 030,—. 000 .50: @030: Ammmn
mo 029, new 5 omnnno €305 Amwnmnnao 85 @8385 u mead—”toad; duke mo 029 new 3805
3&5 3002 895 0on0>0m 003005 ~m~ 0:505 00803582
303.8 833 eo 82 0.5283: 83: Go as Boga 9.30
3030 Bob Boa :30 3305 3030 Bob 3o: :08 E805 €850 Boa 3o: :80 08005
83: :80 83: Go 83: 2953 830
93.5 03095 .0883 23.3 nmao 93.5 :30
3008 no 60.8.5 @8005 3008 no «00085 B805 @0000 no “mobanm €805
cowﬁ: 0nn0>0x 00885 08.9: 355% 00835 08.2: . 0.505% «08005
sand: :30 89.9: :30 83x: :30
_ nook—WN— _ San—MA..— ~ B0>Amtﬂ
$85002: @8005 .cnonnmo>5 @8005 $5800.02: @8005
©86ch :80 8°68.— nmoo coeds; n30
. 0868.— 832 8°68.— 808< 2568.— 808.0.
~30>Jot8 _ 3053.8 :oﬂﬂzzc
ago >n swoon 83> nab n «son 33... an 38: 3oz :88 0. «son 3 0.53 eeoawaon oz

 

 

65

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. F AS 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 in income as they occur, the effective
and ineffective amounts of the hedging relationship are recognized in earnings. In
contrast under the cash ﬂow hedge, 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 (F AS No. 133, paragraph 68).

 

4' 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

66

If the 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 (F AS No. 133,
paragraph 118). Table E (on the next page) summarizes swaps’ effects on N11 and net
income pre- and post-F AS No. 133 and provides the basis for the statements made about

N11 and net income management in Chapter III.

 

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.

67

m2 62 m<hé0om 68. .0...— 0885 ~02 Una HZ no 0000.5— .0..an .m— 030M.

 

 

 

 

 

 

 

00088800008 on
92 85 on 080 0888 00n
0888 08 080»? no “8&0 08 on m2 oz
32 nonv 82 85 92 no “8&0 onv 0008>80b08 .n0>03om .0888 =2 m<m¢0om
.0888 .0888 0830 no 8880 0E. 8n 8 088800
8n 8 085800 08 8 085800 now00008 no o. 8.850%
s 8830 s 8830 an Sign:
8 000030< 088800 088800 m2 .oZ
on 88:80 0oz on 00.8.8.— 82 m2 93-0.5
A0300: #8808 80.880 A8808 80-880
088n8v no 08008 80.08% 830 898 A0800: 80.80886 no 0800..— 800805: 03oz 8000
00002 no 00008 m0 8n W008— no 00002 no n0n 8880A
08% 88808: no 88» 00800.8: mo 000.cm 080 ow00M=008n 88% 88—008: mo 80am
.8 088 00 08000 0 0 00 E 08.00

 

 

08008009 083-88% .

 

808808 888:

 

 

 

68

BIBLIOGRAPHY

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, PM. 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.

69

Federal Deposit Insurance Corporation (FDIC), 2002, DOS Manual of Exam Policies:
Basic Examination Concepts and Guidelines, Section 1.1, February 2002.

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.
21 S-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 I 33 on Derivative Instruments
and Hedging Activities, Norwalk, CT.

F root, 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, 3rd 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.

70

 

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 A ccounting and Economics, Vol. 13, pp. 123-
154.

Neter, J ., M. H. Kutner, C. J. Nachtsheim, and W. Wasserman, 1996, Applied Linear
Statistical Model, McGraw-Hall, Inc, 4th edition.

Partnoy, F., 2003, Infectious Greed: How Deceit and Risk Corrupted the Financial
Markets, Henry Holt and Company, LLC, 15‘ edition.

Pincus, M. and S. Raj gopal, 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 Flaming, 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.

Song, C. J ., 2002, Derivative Accounting and Related Research Questions, Ph.D. student
2“d-year paper, Michigan State University.

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-
Westem College Publishing.

71

    
 

flllllllllﬂlallllﬂlllﬂljllllllll

179