Directory UMM :Data Elmu:jurnal:J-a:Journal Of Banking And Finance:Vol24.Issue10.2000:

Journal of Banking & Finance 24 (2000) 1399±1417
www.elsevier.com/locate/econbase

The risk of foreign currency contingent claims
at US commercial banks
Mukesh K. Chaudhry a, Rohan Christie-David b,
Timothy W. Koch c,*, Alan K. Reichert d
a
Northern State University, Aberdeen, SD, USA
University of Southern Mississippi, Hattiesburg, MS, USA
Darla Moore School of Business, College of Business Administration, University of South Carolina,
The Francis M. Hipp Building, Columbia, SC 29208, USA
d
Cleveland State University, Cleveland, OH, USA
b

c

Received 22 December 1997; accepted 8 July 1999

Abstract

This study investigates the relationship between market-based measures of risk and
foreign currency contingent claims activity at US commercial banks. Speci®cally, four
types of foreign currency contingent claims are examined: purchased foreign currency
option contracts, foreign-exchange swaps, commitments to purchase foreign currency
and forward contracts. Within the context of the Comptroller of the Currency's (OCCÕs)
Banking Circular 277, we di€erentiate between the risk exposure of dealer banks and
non-dealer banks. Empirical results suggest that (i) the use of options tends to increase
all market-based measures of bank risk, (ii) swaps are used primarily for risk-control
purposes and (iii) the use of forward contracts and currency commitments contributes
mildly, if at all, to any type of risk. There is some evidence that swaps activity at dealer
banks increases unsystematic risk. Otherwise, dealer and non-dealer banks appear to
similarly manage foreign currency risk. Ó 2000 Elsevier Science B.V. All rights reserved.
JEL classi®cation: G21
Keywords: Foreign currency; Contingent claims; Banks

*

Corresponding author. Tel.: +1-803-777-6748; fax: +1-803-777-6876.
E-mail address: tkoch@darla.badm.sc.edu (T.W. Koch).

0378-4266/00/$ - see front matter Ó 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 4 2 6 6 ( 9 9 ) 0 0 0 8 6 - 2

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M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1. Introduction
This study empirically investigates the relationship between market-based
measures of risk and foreign currency contingent claims activity at US commercial banks. The impetus is the rapidly growing use of these o€-balance sheet
items and regulatory concerns regarding bank risk management practices. The
oce of the Comptroller of the Currency (OCC) (1993) issued Banking Circular 277 to provide guidance on risk management activities for national banks
and federal branches and agencies of foreign banks entering into derivative
activities. While the circular encourages banks to use derivatives for prudent
purposes, it states
The complexities of ®nancial derivatives raises concerns about some institutionsÕ use of derivatives under some circumstances. National banks
engaging in derivatives transactions must do so in accordance with safe
and sound banking practices. The OCC is concerned about how the use
of ®nancial derivatives can in¯uence the risk of failure of any institution,
and particularly those institutions whose failures might threaten the

solvency of other institutions or negatively a€ect liquidity in the nationÕs
®nancial system.
More recently, central bankers from Europe, Japan and North America agreed
to implement a proposal for monitoring foreign-exchange risk at banks to
better assess risk exposure to interest rates and exchange rates. 1 One component of foreign-exchange risk is the net open position in certain o€-balance
sheet instruments.
The purpose of this research is to examine the breadth of US banksÕ use of
foreign-exchange contingent claims and to investigate the marketÕs perception
of bank risk associated with di€erent levels of usage. We speci®cally examine
bank purchases of foreign currency option contracts, commitments to purchase
foreign currency, and the notional principal amount of forward contracts and
foreign-exchange swaps. Banks use these instruments for varied purposes, as
end-users with the typical objective to reduce undesirable exposure to currency
¯uctuations, and by o€ering derivatives to bank customers as part of dealer
operations. Banks also use these instruments speculatively to increase income.
If management truly attempts to hedge, derivatives should serve to decrease
bank risk, while any speculative use of these instruments will increase risk.
We extend existing research in two important ways. First, we document US
banksÕ use of these four types of foreign-exchange contingent claims and, in the

1
This proposal was introduced in 1995 as an amendment to the Basle Committee Accord with
full implementation by year-end 1997.

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1401

spirit of Saunders et al. (1990), examine the relationship between capital
market measures of bank risk and measures of this foreign-exchange o€-balance sheet activity for a sample of large banks from 1989 to 1993. Second, we
distinguish between in¯uences across dealer banks and other banks that are
active in these markets. This research is particularly important given the focus
of Circular 277 on institutions whose potential insolvency might threaten liquidity ± a clear reference to large banks that run dealer operations and/or
compete across national markets. The analysis allows us to draw inferences
regarding the marketÕs perception of whether banks in the aggregate use these
instruments to hedge or speculate.
The relationship between risk taking by banks and their foreign currency
contingent claims exposure is important to regulators and investors. Regulators are primarily concerned about bank safety and soundness such that the
relationship between these measures and total risk will provide information
about the perceived likelihood of default. The relationships between interest

rate risk and foreign-exchange risk provide similar information regarding how
investors react to unanticipated exposures. This is useful in assessing the
likelihood that market participants will react adversely to undesired exposures
which, in turn, might serve as an indicator of problem banks. While investors
can diversify unsystematic risk away, it is useful to know whether any relationship exists between this risk and the various exposures to identify the appropriate portfolio strategies. Finally, these concerns are exaggerated for
dealer banks whose exposures are presumably the greatest.
Recent studies by Choi and Elyasiani (1997) and Hirtle (1997) examined
similar issues with several di€erences. While Choi and Elyasiani (1997) provide
evidence of a link between a bankÕs derivative activity and its interest rate and
exchange risk betas, we provide evidence on the association between the use of
foreign currency contingent claims by dealer and non-dealer banks and measures of market, systematic, and unsystematic risk in addition to interest rate
and exchange risk measures. Hirtle (1997) examines the relationship between
the interest-rate risk exposure of bank holding companies (BHCs) and derivative usage, particularly interest rate swaps. 2 We focus on foreign currency
derivative activities.

2
Other studies have examined the impact of derivatives on ®rm value. Brewer and Lee (1986),
Brewer et al. (1996), Carter and Sinkey (1998), Gorton and Rosen (1995), Grammatikos et al.
(1986), Morgan et al. (1988), Pillo€ (1995), Schrand (1997) and Venkatachalam (1996) discern some
relationship between the use of interest-rate derivatives and the interest sensitivity of bank or

savings and loan stocks. Pillo€ further concludes that the stock return volatility of derivativesÕ
dealers does not increase with trading activity and suggests that dealers may better use the
instruments to hedge than non-dealers. Carter and Sinkey (1998) conclude, alternatively, that the
use of derivatives reduces the interest sensitivity of stock returns with similar results for dealer and
non-dealer banks.

1402

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

The remainder of the paper is organized as follows. In Section 2 we describe
US bank activity involving foreign-exchange derivatives at year-end 1993.
Section 3 presents the models used to generate the capital market measures of
bank risk and relates these measures cross-sectionally to control variables and
measures of bank foreign-exchange contingent claims activity. We present the
empirical results in Section 4 and a summary with policy implications in
Section 5.

2. US banks' use of foreign-exchange contingent claims
Table 1 presents summary data regarding the use of four types of foreign

currency contingent claims at year-end 1993 for US banks. The summary
statistics provided in Panel A relate to the entire banking sector, while those in
Panels B and C relate to our research sample. In 1993 approximately one-third
of total bank assets was controlled by banks below $10 billion in size, one-third
was managed by banks with $10±50 billion in assets, and the remaining onethird was controlled by banks with assets in excess of $50 billion. It is in the
two largest size groups, especially the 15 banks over $50 billion, where the vast
majority of foreign-exchange contingent claim activity takes place. For example, while the 15 banks with more than $50 billion in assets manage 36.9% of
total industry assets on balance sheet, they manage 76.0% of all forward-exchange contracts, 59.7% of foreign-exchange commitments, 86.2% of currency
options and over 92% of foreign-exchange swaps.
In terms of our research sample, the 112 banks collectively represent 41.1%
of total industry assets with an average bank size of approximately $15 billion
as summarized in Panel B. These banks are collectively involved in 74.3% of
total forward-exchange contracts, 60.6% of all foreign-exchange commitments,
82.3% of current options, and almost 95% of foreign-exchange swaps. Panel C
indicates that our sample includes eleven dealer banks, all of which have assets
over $50 billion. These banks account from 41% to almost 86% of the foreign
currency derivatives activity.

3. Models, methodology and data
The model we use follows the methodology adopted by Flannery and James

(1984a,b), Tarhan (1987) Saunders et al. (1990), Kwan (1991) and Chamberlain
et al. (1997). They ®nd that a multiple-index model with proxies for interest
rate returns, exchange rate changes, and the market return is an appropriate
framework to model commercial bank stock return sensitivity. We focus on
®ve di€erent measures of capital market risk by using ordinary least-squares to
estimate the following three-index market model for each sample bank:

Asset range

Panel A
30 bn
>1±5 bn
>5±10 bn
>10±50 bn
>50 bn
Panel B
Banks in
our sample
Panel C
Dealer

banks

No. of
banks

Total
assets
(Agg)

% of
total

Forwards
(Agg)

% of total

Curr
comm
(Agg)

% of
total

Curr opt
(Agg)

$0
0.091
0.210
2.812
6.037
110.083
746.538

636
690
383
196
47

70
15

$12.38
132.66
192.37
445.46
331.10
1489.52
1521.72

0.3
3.2
4.7
10.8
8.0
36.1
36.9

$0
0.005
0.055
0.225
0.075
2.475
8.985

0
0.04
0.47
1.91
0.64
20.94
76.01

$0
0.001
0.587
0.503
0.180
4.772
8.946

0
0.01
3.91
3.36
1.20
31.8
59.68

112

$1695.06

41.1

$8.656

74.3

$9.084

60.6

11

$814.86

19.8

$4.851

41.6

$6.243

41.6

% of total

Curr
swap
(Agg)

% of total

0
0.01
0.02
0.32
0.70
12.72
86.23

$0
0
0
0
0
18.31
216.08

0
0
0
0
0
7.81
92.15

$712.31

82.3

$222.54

94.9

$630.19

72.8

$201.35

85.9

a
This table gives aggregate dollar values (Agg) for assets and foreign currency contingent claims for the entire banking sector in 1993. The table
presents the aggregate value for banks in the size category and the percentage of the total value for the entire banking sector. Curr, Comm, and Opt
refer to currency, commitments, and options, respectively; mn and bn refer to million and billion, respectively.

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

Table 1
Summary statistics for assets and foreign currency contingent claims of all bank holding companies in the US banking system 1993a (in US$ billions)

1403

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M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

R~it ˆ a0i ‡ bmi R~mt ‡ bki R~kt ‡ bei R~et ‡ ~eit ;

…1†

where the dependent variable, R~it , is the holding period return for the ith bankÕs
stock in a given month t, R~mt the holding period return on an equally weighted
portfolio of common stocks, R~kt a measure of unanticipated changes in the riskfree rate, R~et a measure of unanticipated changes in a weighted-averageexchange rate of the US dollar versus currencies in 10 industrial countries and
~eit is the usual error term. In this framework, bmi measures systematic risk and
the sensitivity of the security to market-wide events, while bki and bei measure
the e€ect of unexpected changes in nominal interest rates and an index of
exchange rates, respectively, on bank stock returns.
Because expected changes in interest rates and exchange rates should already
be incorporated in stock returns, we construct measures of unanticipated
changes for R~kt and R~et which may cause market participants to react and
potentially a€ect stock returns. In particular, we employ the standard ARIMA
procedure to ®t a model for each of the long-term government bond rate and
index of exchange rates using monthly data for 1989±1993. In both cases, an
AR(1) model is appropriate. 3 We then interpret the residuals from these
models as the unanticipated change in the long-term rate and exchange rate,
respectively, and designate the series as R~kt and R~et . Finally, we estimate the
regressions across banks as a series of seemingly unrelated regressions (SUR)
to take advantage of possible contemporaneous correlation among the error
terms. 4
This model yields the following capital market measures of risk for each
sample bank:
1=2
rRi ˆ total return risk for bank i, …Var…R~it ††
1=2
rei ˆ unsystematic risk for bank i, …Var…~eit ††
bmi ˆ systematic risk for bank i
bki ˆ systematic interest rate risk for bank i
bei ˆ systematic foreign-exchange risk for bank i
Di€erences in the systematic risk measures across banks re¯ect di€erences in
the sensitivity of bank stocks to the market return, unanticipated interest rates,
3
We conducted the same tests throughout this research using the three-month treasury bill rate
instead of the long-term government bond rate. The empirical results are virtually identical as that
with the long-term rate, except an AR(3) model provided the best ®t. Thus, we do not report results
using the treasury bill rate. Several researchers have used orthogonalized indices to help control for
correlation among returns. We do not orthogonalize indices because Gilberto (1985), Kane and
Unal (1988) and Kwan (1991) demonstrate that orthogonalization does not mitigate correlation
problems and theory does not impose zero correlations.
4
For a more detailed explanation of the use of SUR, see Kwan (1991).

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1405

and unanticipated-exchange rates, respectively. 5 Di€erences in total return
and unsystematic risk, in turn, re¯ect aggregate and non-diversi®able risk. A
larger (in absolute value) estimated risk measure signi®es a higher degree of
bank risk along the dimension noted.
After obtaining the ®ve risk measures for each bank, we estimate three
cross-sectional regression models for each risk measure. The ®rst is
Risk measure ˆ c0 ‡ c1 …GAP† ‡ c2 …CR† ‡ c3 …CAP† ‡ c4 …LIQ†
‡ c5 …EFF† ‡ c6 …VARINC† ‡ c7 …SIZE† ‡ c8 …CI†
‡ c9 …RE† ‡ c10 …CON† ‡ c11 …AGRI† ‡ c12 …COM†
‡ c13 …FWD† ‡ c14 …OPT† ‡ c15 …SWAP† ‡ ei ;

…2†

where the risk measure is one of rRi , bmi , bki , bei or rei . The ®rst 11 variables
control for accounting measures of bank risk from the balance sheet and income statement, while the last four variables represent measures of foreign
currency contingent claims. The notation for the last four variables refers to a
bankÕs use of commitments to purchase foreign currency (COM), currency
forward contracts (FWD), purchased currency option contracts (OPT) and
currency swaps (SWAP), respectively. Appendix A provides the notation and
an explanation for all variables used in the regressions.
Because we are particularly interested in the relationship between the extent
of a bankÕs derivativesÕ usage and the marketÕs perception of risk, we construct
two di€erent measures of contingent claims. The ®rst is the continuous measure
of a bankÕs derivativesÕ activity by type employed in the initial regression. The
second groups each bank into one of three categories representing high
(HIGH), medium (MED) and low (LOW) levels of contingent claim activity.
To create the categorical variables, each bank in the sample is ranked according to its level of involvement relative to asset size, in each derivative
activity. It is possible for a given bank to rank low in one type of foreign
currency activity and high in another. Using this ratio we divide the sample
into three equal parts. The top one-third of the sample includes banks where
the level of derivative activity is considered to be high, the next one-third includes banks considered to have a medium level of derivative activity, and the
bottom one-third includes banks considered to have a low level of derivative
activity. Dummy variables labeled HIGH (high), MED (medium) and LOW
(low) indicate the level of activity within each type of contingent claim (e.g.,
HIGHCOM, MEDCOM, LOWCOM, etc.). We estimate a second set of

5

Given the evidence in Kane and Unal (1988), we test for non-stationarity in the market return,
interest-rate beta and exchange rate beta. The results from these tests provide no evidence of nonstationarity. These empirical results are available upon request.

1406

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

cross-section regressions using these interactive measures. Finally, we estimate
a third set of regressions that employs dummy variables to identify the activity
of dealer banks. 6 We distinguish between the activity of dealer banks and nondealer banks by employing interactive dummy variables representing dealer
banks and the amount of their activity in each type of contingent claim.
To be included in the sample a bank holding company (BHC) had to meet
the following criteria: (i) the stock was traded on the NYSE or the NASDAQ
continuously during the sample period, 1989±1993 and (ii) call report data had
to be available for the BHC on all variables used in the study. We exclude
banks that merged or failed during the sample period. 7 The data for both
accounting-based and o€-balance sheet variables are obtained from annual call
reports and represent year-end values averaged over the ®ve year sample period
(1989±1993). Stock returns are computed using monthly data obtained from
the NYSE and OTC CRSP monthly tapes. Data for long-term interest rates are
obtained from Ibbotson and Associates and the index of foreign-exchange
value for the US dollar is from the Federal Reserve Bulletin. The returns and
innovations are employed in Eq. (1) to generate estimates for each of the risk
measures which serve as the dependent variables in the second stage regressions. The ®nal sample includes 112 BHC stocks that are actively traded on
either the NYSE or the NASDAQ markets. 8
An analysis of the correlation between the log of total bank assets and each
independent variable reveals the importance of bank size. Speci®cally, most of
the control variables exhibit a reasonably high correlation with asset size, with
some of the largest correlations related to foreign currency contingent claim

6

Dealer banks in the sample include: B.A. Securities, Incorporated (Bank of America); B.T.
Securities Corporation (Bankers Trust); Citicorp Securities, Incorporated (Citibank); J.P. Morgan
Securities, Incorporated (Morgan Guaranty Trust); NationsBanc Capital Markets, Incorporated
(Nations Bank); Chase Securities, Incorporated (Chase Manhattan); C.S. First Boston Corporation
(First Boston Corporation); First Chicago Capital Markets (First National Bank of Chicago);
Continental Bank National Association (Continental Illinois); Chemical Securities, Incorporated
(Chemical Bank); Zions First National Bank (Zions Bank).
7
There is a clear supervisorship bias in this sample as banks must operate in consistent
organizational form over all ®ve years to be included. The implication is that some omitted ®rms
may have experienced substantially di€erent risk exposures such that our estimated risk parameters
do not re¯ect true exposures. The fact that we ®nd no evidence of non-stationarity in bm , bk and be
(footnote 5) suggests that our estimates are robust for the sample banks. We also conduct the same
regression analysis on a year-by-year basis and discuss the results after the pooled analysis. This
mitigates the impact of survivorship bias in the pooled analysis.
8
The time series regression of returns for the ith bank over the sample period yields a single
value for a given risk estimate. Because there are 112 banks in our sample, a total of 112 values for
a given measure of risk are obtained. These measures are then employed in the SUR regressions in
Eq. (2). The accounting-based and o€-balance sheet variables used in Eq. (2) are single values
obtained for each bank by averaging the annual values obtained from the call data report for the
period 1989±1993.

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1407

activity. For example, the correlation between the log of asset size and currency
commitments is 0.496, for options is 0.467, for forward contracts is 0.449, and
for currency swaps is 0.400. In addition, the correlations between bank size and
the variables used to indicate the three levels of derivative involvement for each
type of contingent claim also indicate a strong positive relationship as the
correlation switches from being negative for the low usage group to a large
positive for the high usage group. Thus, the largest banks are much more active
in derivative activity than smaller institutions. These results are consistent with
prior research of James (1987), Kim and Koppenhaver (1993), Gunther and
Siems (1995) and Carter and Sinkey (1998) for banks and Colquitt and Hoyt
(1997) for life insurance companies who ®nd a positive relationship between
®rm size and the use of derivatives.

4. Empirical results
Tables 2±6 present the parameter estimates from Eq. (2) for each of the ®ve
risk measures. There are three sets of regression results in each table. The
overall sample results (®rst regression) use continuous data for each of the
contingent claims measures, COM, FWD, OPT and SWAP. The middle columns denoting the regression with the level of activity dummies reports the
parameter estimates when foreign currency activity is separated into the three
categories described previously. In the third regression we focus on dealer
banks. Speci®cally, we use the Board of Governors of the Federal Reserve
System classi®cation to identify authorized dealer banks, which we designate
via a dichotomous variable (DEALER) that takes a value one for dealer banks
and zero otherwise. We then investigate the impact of derivativesÕ activity at
these ®rms through the use of interactive variables. The set of variables at the
bottom of Tables 2±6, labeled DCOM, DFWD, DSWAP and DOPT, equals
the product of the dummy variable DEALER, indicating whether or not the
bank is an authorized government security dealer, and the respective continuous measure of each contingent claims variable.
The top portion of each table reports the results for the control variables,
while the bottom portion reports results for the foreign-exchange variables.
Consider Table 2 and the results of the regressions for total return risk. Here
the estimated relationships among the control variables are consistent across
all three models. For example, the greater is a bankÕs GAP, indicating a greater
mismatch between rate-sensitive assets and rate-sensitive liabilities, the greater
is total return risk. Higher relative amounts of equity capital are associated
with lesser total return risk. Banks with lower personnel expense and greater
earnings variability exhibit higher total return risk.
Empirical results regarding the relationship between total return risk and
foreign currency contingent claims are similarly robust. The results for the

1408

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

Table 2
Risk of contingent claims ± foreign currency exposure; dependent variable ± total riska
Overall sample

Regression with level
of activity dummies

Regression with dealer
bank dummies

0.343 (4.52)
0.004 (2.28)
0.048 (0.23)
)1.452 ()5.73)
)0.006 ()0.07)
)0.034 ()2.21)
5.045 (2.29)
)0.009 ()3.53)
0.021 (0.34)
)0.061 ()1.09)
0.035 (0.65)
)0.050 ()0.39)

0.138 (2.03)
0.005 (3.27)
0.220 (1.05)
)1.218 ()4.53)
)0.077 ()0.76)
)0.015 ()0.91)
3.728 (1.67)
)0.004 ()2.38)
0.043 (0.67)
)0.0004 ()0.01)
0.063 (1.12)
0.026 (0.19)

0.185 (2.66)
0.005 (3.29)
0.244 (1.12)
)1.195 ()4.45)
)0.085 ()0.82)
0.040 (2.34)
5.984 (2.38)
)0.0006 ()0.31)
)0.011 ()0.16)
)0.059 ()0.92)
0.010 (0.17)
)0.007 ()0.05)

Foreign currency contingent claims
COM
)0.310 ()0.73)
FWD
1.287 (1.11)
OPT
0.071 (2.49)
SWAP
)0.068 ()1.76)
MEDCOM
±
HIGHCOM
±
MEDFWD
±
HIGHFWD
±
MEDSWAP
±
HIGHSWAP
±
MEDOPT
±
HIGHOPT
±
DCOM
±
DFWD
±
DSWAP
±
DOPT
±

±
±
±
±
)0.009 ()1.16)
)0.019 ()2.40)
0.002 (0.31)
)0.0005 ()0.06)
0.007 (0.83)
)0.036 ()2.32)
0.009 (2.30)
)0.005 ()0.45)
±
±
±
±

)0.685 ()1.17)
)0.001 ()0.01)
0.099 (2.86)
)0.091 ()1.44)
±
±
±
±
±
±
±
±
)0.857 ()0.87)
2.563 (0.84)
)2.112 ()2.22)
0.655 (2.24)

Dealer

±

)0.006 ()0.42)

Control variables
Constant
GAP
CR
CAP
LIQ
EFF
VARINC
SIZE
CI
RE
CON
AGRI

F-value
R2

±


7.420
0.537



6.919
0.601

6.050
0.583

a
In this table we report three sets of regressions. The ®rst regression is for the overall sample
(identi®ed as ``overall sample''), the second accounts for di€erences in levels of derivative activity
(identi®ed as ``regression with level of activity dummies''), and the third takes into account the
activities of dealer banks. The overall sample consists of 112 banks and includes 11 dealer banks.
***
Signi®cant at the 1% level for a two-tailed t-test.
**
Signi®cant at the 5% level for a two tailed t-test.
*
Signi®cant at the 10% level for a two tailed t-test.

overall sample using continuous measures of contingent claims indicate that
the level of foreign currency options increases total risk, while the level of
foreign currency swaps lowers total risk. The levels of foreign-exchange com-

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1409

Table 3
Risk of contingent claims ± foreign currency exposure; dependent variable ± market riska

Control variables
Constant
GAP
CR
CAP
LIQ
EFF
VARINC
SIZE
CI
RE
CON
AGRI

Overall sample

Regression with level
of activity dummies

0.644 (0.88)
0.011 (0.89)
)0.639 ()0.32)
)8.009 ()3.27)
)1.072 ()1.15)
)0.105 ()0.71)
67.021 (3.14)
0.052 (2.11)
)0.026 ()0.05)
)0.307 ()0.57)
0.305 (0.58)
)0.407 ()0.32)

1.056 (1.84)
0.020 (1.61)
0.063 (0.03)
)7.091 ()3.12)
)1.403 ()1.66)
0.074 (0.54)
50.592 (2.52)
)0.014 ()0.82)
0.238 (0.44)
0.164 (0.33)
0.721 (1.53)
0.423 (0.36)

Foreign currency contingent claims
COM
)2.455 ()0.61)
FWD
)2.303 ()0.21)
OPT
0.219 (0.80)
SWAP
)0.223 ()0.60)
MEDCOM
±
HIGHCOM
±
MEDFWD
±
HIGHFWD
±
MEDSWAP
±
HIGHSWAP
±
MEDOPT
±
HIGHOPT
±
DCOM
±
DFWD
±
DSWAP
±
DOPT
±

0.012 (0.17)
)0.019 ()2.40)
0.044 (0.75)
)0.001 ()0.02)
0.203 (2.68)
)0.426 ()3.27)
0.112 (1.67)
0.212 (2.37)
±
±
±
±

Dealer

±

F-value
R2

±


4.671
0.421

±
±
±
±

Regression with dealer
bank dummies
1.851 (2.97)
0.013 (1.02)
1.227 (0.63)
)8.091 ()3.38)
)1.146 ()1.23)
)0.088 ()0.58)
69.732 (3.12)
0.0003 (0.02)
)0.325 ()0.53)
)0.773 ()1.36)
)0.055 ()0.10)
)0.973 ()0.77)
)7.169 ()1.37)
)3.524 ()0.27)
0.663 (2.14)
)0.447 ()1.17)
±
±
±
±
±
±
±
±
12.119 (1.38)
30.974 (1.14)
)40.372 ()2.39)
12.568 (2.20)
)0.146 ()1.14)



5.447
0.532

3.955
0.547

a

In this table we report three sets of regressions. The ®rst regression is for the overall sample
(identi®ed as ``overall sample''), the second accounts for di€erences in levels of derivative activity
(identi®ed as ``regression with level of activity dummies''), and the third takes into account the
activities of dealer banks. The overall sample consists of 112 banks and includes 11 dealer banks.
***
Signi®cant at the 1% level for a two-tailed t-test.
**
Signi®cant at the 5% level for a two-tailed t-test.
*
Signi®cant at the 10% level for a two-tailed t-test.

mitments and forward contracts, in contrast, either are not statistically signi®cant or are marginally signi®cant. Measuring contingent claim activity in
categorical terms with the sample broken into thirds suggests that banks using

1410

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

Table 4
Risk of contingent claims ± foreign currency exposure; dependent variable ± interest rate (longterm) riska

Control variables
Constant
GAP
CR
CAP
LIQ
EFF
VARINC
SIZE
CI
RE
CON
AGRI

Regression with level
of activity dummies

)2.588 ()2.35)
0.009 (0.47)
0.363 (0.12)
)14.011 ()3.81)
)1.129 ()0.81)
0.290 (1.29)
2.882 (0.09)
)0.205 (5.54)
)1.273 ()1.42)
)1.535 ()1.90)
)1.644 ()2.09)
)1.696 ()0.90)

0.519 (0.52)
0.004 (0.20)
0.584 (0.19)
)11.585 ()2.95)
)0.402 ()0.27)
0.488 (2.04)
19.001 (0.55)
)0.018 ()0.63)
)1.047 ()1.12)
)1.788 ()2.11)
)1.634 ()2.01)
)2.165 ()1.07)

Foreign currency contingent claims
COM
6.651 (1.09)
FWD
)1.692 ()0.10)
OPT
)0.414 ()1.00)
SWAP
)0.148 ()0.26)
MEDCOM
±
HIGHCOM
±
MEDFWD
±
HIGHFWD
±
MEDSWAP
±
HIGHSWAP
±
MEDOPT
±
HIGHOPT
±
DCOM
±
DFWD
±
DSWAP
±
DOPT
±

0.032 (0.27)
)0.028 ()0.23)
0.164 (1.59)
0.108 (0.91)
0.211 (1.61)
)0.507 ()2.25)
0.231 (1.99)
0.428 (2.77)
±
±
±
±

Dealer

±

F-value
R2
a

Overall sample
sample

±
5.304
0.453

±
±
±
±

Regression with dealer
bank dummies
1.752 (1.59)
)0.024 ()1.02)
3.180 (0.92)
)8.956 ()2.11)
)0.780 ()0.47)
)0.210 ()0.79)
15.667 (0.40)
)0.004 ()0.12)
)1.253 ()1.13)
)2.191 ()2.19)
)1.575 ()1.63)
)2.982 ()1.34)
8.898 (0.96)
9.060 (0.40)
)0.573 ()1.05)
0.188 (0.28)
±
±
±
±
±
±
±
±
)3.312 ()0.21)
19.891 (0.41)
)45.259 ()2.16)
15.640 (2.02)
0.146 (0.64)

5.357
0.487

4.945
0.445

In this table we report three sets of regressions. The ®rst regression is for the overall sample
(identi®ed as ``overall sample''), the second accounts for di€erences in levels of derivative activity
(identi®ed as ``regression with level of activity dummies''), and the third takes into account the
activity of dealer banks. The overall sample consists of 112 banks and includes 11 dealer banks.
***
Signi®cant at the 1% level for a two-tailed t-test.
**
Signi®cant at the 5% level for a two-tailed t-test.
*
Signi®cant at the 10% level for a two-tailed t-test.

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1411

Table 5
Risk of contingent claims ± foreign currency exposure; dependent variable ± foreign currency riska

Control variables
Constant
GAP
CR
CAP
LIQ
EFF
VARINC
SIZE
CI
RE
CON
AGRI

Overall sample

Regression with level
of activity dummies

)0.550 ()0.45)
0.032 (1.22)
1.504 (0.37)
)5.902 ()2.18)
)1.412 ()0.75)
0.036 (0.12)
31.295 (0.70)
)0.016 ()0.45)
1.511 (1.21)
0.879 (0.79)
)2.706 ()2.48)
)4.424 ()1.69)

)1.280 ()1.01)
0.039 (1.82)
1.262 (1.78)
)5.212 ()1.83)
)1.317 ()1.69)
0.239 (0.78)
39.672 (1.55)
0.004 (0.12)
1.764 (1.48)
1.251 (1.15)
)2.897 ()2.78)
)4.157 ()1.60)

Foreign currency contingent claims
COM
6.381 (1.24)
FWD
)3.260 ()0.27)
OPT
0.905 (3.32)
SWAP
)0.141 ()2.98)
MEDCOM
±
HIGHCOM
±
MEDFWD
±
HIGHFWD
±
MEDSWAP
±
HIGHSWAP
±
MEDOPT
±
HIGHOPT
±
DCOM
±
DFWD
±
DSWAP
±
DOPT
±

±
±
±
±
)0.176 ()1.19)
)0.032 ()0.21)
0.186 (1.41)
0.049 (0.32)
)0.090 ()0.53)
)0.485 ()3.68)
0.104 (3.07)
0.258 (1.98)
±
±
±
±

Dealer

±

F-value
R2

±


2.932
0.346

Regression with dealer
bank dummies
)0.106 ()0.09)
0.032 (1.18)
0.213 (0.05)
)5.706 ()2.13)
)1.401 ()1.83)
0.057 (0.19)
32.502 (1.60)
)0.021 ()0.51)
1.147 (0.97)
0.514 (0.51)
)2.424 ()2.41)
)4.863 ()1.96)
)1.685 ()1.79)
)16.546 ()0.59)
0.547 (3.82)
)0.051 ()3.06)
±
±
±
±
±
±
±
±
)8.458 ()0.52)
9.056 (0.18)
)121.88 v
41.853 (2.66)
0.043 (0.24)



2.991
0.389

2.902
0.343

a
In this table we report three sets of regressions. The ®rst regression is for the overall sample
(identi®ed as ``overall sample''), the second accounts for di€erences in levels of derivative activity
(identi®ed as ``regression with level of activity dummies''), and the third takes into account the
activities of dealer banks. The overall sample consists of 112 banks and includes 11 dealer banks.
***
Signi®cant at the 1% level for a two-tailed t-test.
**
Signi®cant at the 5% level for a two-tailed t-test.
*
Signi®cant at the 10% level for a two-tailed t-test.

1412

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

Table 6
Risk of contingent claims ± foreign currency exposure; dependent variable ± unsystematic riska
Overall sample

Regression with level
of activity dummies

Regression with dealer
bank dummies

0.329 (4.52)
0.003 (2.27)
0.057 (0.29)
)1.347 ()5.54)
)0.025 ()0.27)
)0.027 ()1.84)
3.378 (1.60)
)0.012 ()1.53)
0.069 (1.16)
)0.011 ()0.21)
0.069 (1.16)
)0.011 ()0.21)

0.083 (1.26)
0.004 (3.23)
0.186 (0.91)
)1.094 ()4.19)
)0.080 ()0.81)
)0.007 ()0.45)
2.928 (1.26)
)0.0001 ()0.05)
0.069 (1.12)
0.029 (0.52)
0.094 (1.74)
0.043 (0.32)

0.100 (1.39)
0.004 (3.23)
0.312 (1.38)
)1.045 ()3.78)
)0.078 ()0.73)
0.035 (1.97)
4.266 (1.65)
)0.001 ()0.40)
0.042 ( 0.59)
0.008 (0.12)
0.069 (1.97)
0.063 (0.43)

Foreign currency contingent claims
COM
0.087 (1.67)
FWD
1.399 (1.26)
OPT
0.051 (1.89)
SWAP
0.007 (0.20)
MEDCOM
±
HIGHCOM
±
MEDFWD
±
HIGHFWD
±
MEDSWAP
±
HIGHSWAP
±
MEDOPT
±
HIGHOPT
±
DCOM
±
DFWD
±
DSWAP
±
DOPT
±

±
±
±
±
)0.012 ()1.61)
)0.017 ()2.18)
0.0006 (0.09)
0.001 (0.11)
0.0007 (0.09)
0.038 (2.55)
0.012 (1.52)
0.017 (1.64)
±
±
±
±

)0.669 ()1.10)
)0.104 ()0.07)
0.067 (1.87)
)0.009 ()0.21)
±
±
±
±
±
±
±
±
0.557 (0.55)
1.871 (0.60)
0.955 (2.30)
2.679 (1.92)

Dealer

±

Control variables
Constant
GAP
CR
CAP
LIQ
EFF
VARINC
SIZE
CI
RE
CON
AGRI

F-value
R2

±


8.049
0.557

0.0005 (0.03)


6.114
0.613

5.039
0.496

a
In this table we report three sets of regressions. The ®rst regression is for the overall sample
(identi®ed as ``overall sample''), the second accounts for di€erences in levels of derivative activity
(identi®ed as ``regression with level of activity dummies''), and the third takes into account the
activities of dealer banks. The overall sample consists of 112 banks and include 11 dealer banks.
***
Signi®cant at the 1% level for a two-tailed t-test.
**
Signi®cant at the 5% level for a two-tailed t-test.
*
Signi®cant at the 10% level for a two-tailed t-test.

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1413

a medium level of options increase risk, whereas high levels of swaps reduce
bank risk relative to the low usage banks.
The dealer bank results are similar to the results mentioned above. While
options usage increases total return risk at all banks, on average, the coecients on DOPT indicate that currency options held by dealer banks further
increase total return risk. In terms of currency swaps the results indicate that
dealer bank activity signi®cantly reduces total risk relative to other banks.
Forward currency contracts and currency commitments have no di€erential
impact at dealer versus non-dealer banks.
The results for systematic market risk, reported in Table 3, indicate that of
the control variables, only equity capital and earnings volatility have a consistent impact on market risk. The parameter estimates for contingent claims
further suggest that in the overall sample none of the four foreign currency
activities are signi®cantly related to market risk. In contrast, measuring contingence claims activity as a categorical variable provides evidence that medium and high levels of options can increase market risk, whereas similar high
use of commitments and swaps decreases market risk. Note that banks ranked
in the middle in terms of swap use exhibit greater market risk, in contrast to the
impact of higher usage. Finally, currency option activity reported by dealer
banks sharply increases market risk, while swap activity has the opposite e€ect.
Except for the control variables, the results for interest rate risk in Table 4
mimic the results for market risk. The sensitivity measure, bki , is inversely related to a bankÕs equity capital and relative sizes of the real estate and consumer loan portfolios. The results further indicate that none of the continuous
measures of foreign currency activity impact long-term interest rate risk. When
measured as categorical variables, both medium and high levels of options
activity serve to increase risk whereas high levels of swaps activity appear to
reduce interest rate risk. Furthermore, currency option activity reported by
dealer banks increases interest rate risk, while swap activity again decreases
interest rate risk relative to non-dealer banks.
Table 5 presents results related to foreign-exchange risk, which are again
similar to the results for interest rate risk. Given the fact that these risks are
a€ected by many of the same factors, the sensitivities might reasonably be
related to similar ®nancial control variables and positions in foreign currency
contingent claims. The sensitivity measure, bei , varies inversely with a bankÕs
capital to asset ratio and relative holdings of short-term securities. The same
inverse relationship holds for each bankÕs proportionate holdings of consumer
and agriculture loans. Given that there is no separate size e€ect, these measures
may capture the positions of smaller banks that typically have the highest asset
liquidity and capital and relatively large holdings of consumer and agricultural
loans, but just a limited exposure to foreign-exchange risk. Still, in general,
foreign-exchange rate sensitivity increases with options activity and decreases
with the use of swaps. These e€ects increase with the level of usage for options

1414

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

and decreases with high levels of swaps. Dealer bank activity in options, in
turn, is associated with an even greater level of risk while dealer swap activity is
associated with lower risk.
Finally, Table 6 reports the impact of foreign currency claims on unsystematic risk. The results di€er in several ways. First, the results for the continuous claims regression indicate that both currency options and currency
commitments increase unsystematic risk. Second, when the extent of currency
activity is measured in categorical terms, a high level of both these instruments
actually decreases unsystematic risk. Third, for dealer banks, options as well as
swaps consistently increase unsystematic risk relative to non-dealer banks.
4.1. Regression analysis: Year-to-year results
The use of pooled data for 1989±1993 introduces potential survivorship bias
in the sample and masks possible di€erences in the relationships across years
associated with structural changes in the underlying banks and economic environment. To help control for survivorship bias and check robustness, we
estimate the three sets of regressions in (2) on a year-to-year basis. As such, we
run three regressions for each of the ®ve risk measures for each of the ®ve
years, 1989±1993. 9 Not surprisingly, the results in any one year di€er from
those reported in Tables 2±6, but support the basic conclusions. 10 In general,
the control variables continue to a€ect the risk measures in a systematic way
though the magnitude and signi®cance of the estimates vary. In terms of the
year-to-year impacts of di€erent foreign currency contingent claims, banksÕ use
of currency options and swaps generally replicates the results of the pooled
sample. However, commitments to purchase foreign currency are associated
with higher interest rate risk at both dealer and other banks in most years,
while the pooled sample suggests no relationship. Similarly, the use of currency
forwards is occasionally associated with higher market risk and total risk and
lower interest rate risk.

5. Summary and conclusions
This study examines the impact of four di€erent types of contingent foreign
currency claims, options, swaps, forwards, and commitments on various
measures of capital market risk for banks. Bank risk is measured in terms of
total return risk, market risk, interest rate risk, foreign currency risk, and
9

The sample size varies in each year as follows: 135 (1989), 129 (1990), 125 (1991), 119 (1992)
and 112 (1993).
10
The year-by-year estimates are available upon request.

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

1415

unsystematic risk. As suggested by the 1993 Banking Circular 277, we compare
the impact on a sample of dealer banks, as denoted by the Federal Reserve,
with that for non-dealer banks.
Empirical results using pooled data for 1989±1993 and year-to-year data
suggest several patterns in terms of market e€ects. In general, the use of options tends to increase all types of bank risk for all banks. This should be of
concern to all market participants, including bank regulators, as excessive use
of these instruments can result in banks assuming high levels of risk that may
not be prudent. Swaps, in contrast, seem to be used primarily for risk-control
purposes. Further evidence suggests that the use of these instruments by dealer
banks results in increases in unsystematic risk, which may be important to
bank stock investors and to regulators who seek to maintain orderly markets.
Overall, it appears that banks use currency swaps as a hedging tool while
currency options are viewed as playing a more speculative role. According to
tests with the pooled data, the use of forward contracts and currency commitments seems to contribute mildly, at most, to any type of risk. Empirical
tests conducted cross-sectionally year-to-year, however, suggest that the use of
these instruments does a€ect risk, but these impacts vary over time. The evidence reported in this study suggests that while all contingent claim activity
does not increase risk, the OCC is correct in its concern regarding large banksÕ
use of certain derivatives.

Acknowledgements
We would like to thank Leroy Brooks, Drew Winters, Kevin Jacques and
seminar participants at the 1996 Financial Management Association conference for helpful comments.

Appendix A. Variable de®nitions
A. Control variables
GAP
net dollar value of assets less liabilities subject to repricing
within one year divided by earning assets
CR
loan loss provision divided by total loans (TL)
CAP
book value of equity capital divided by total assets (TA)
LIQ
federal funds sold and short-term securities (less pledged
securities) divided by total assets
EFF
salary and bene®ts divided by average assets
VARINC standard deviation of net income/TA
SIZE
log of total assets

1416

M.K. Chaudhry et al. / Journal of Banking & Finance 24 (2000) 1399±1417

B. Loan diversi®cation variables
RE
real estate loans/TL
CI
commercial and industrial loans/TL
CON
consumer loans/TL
AGRI
agricultural loans/TL

C. Foreign currency o€-balance sheet variables
COM
foreign-exchange commitments to purchase divided by total
assets
FWD
forward contracts divided by total assets
OPT
foreign-exchange options divided by total assets
SWAP
foreign-exchange swaps divided by total assets

D. Dummy variables
MEDCOM
medium level currency commitment (middle one-third
sample)
HIGHCOM
high level of currency commitment (top one-third sample)
MEDFWD
medium level of forward contracts (middle one-third
sample)
HIGHFWD
high level of forward contracts (top one-third sample)
MEDSWAP
medium level of foreign-exchange swaps (middle one-third
sample)
HIGHSWAP
high level of foreign-exchange swaps (top one-third
sample)
MEDOPT
medium level of foreign-exchange options (middle onethird sample)
HIGHOPT
high level of foreign-exchange options (top one-third
sample)
DCOM
currency commitments of dealer banks
DFWD
forward contracts exposure of dealer banks
DSWAP
foreign-exchange swaps exposure of dealer banks
DOPT
foreign-exchange options exposure of dealer banks

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