bid-ask spreads in the interbank foreign exchange...
TRANSCRIPT
Journal of Financial Economics 35 (1994) 3177348. North-Holland
Bid-ask spreads in the interbank foreign exchange markets*
Hendrik Bessembinder Arizona SIate University. Tempe, AZ 85287-3906. USA
Received August 1992, final version received October 1993
This study provides evidence on quotations and bid-ask spreads in the wholesale foreign exchange market, and introduces a method to document variation in the placement of quotes relative to asset value. I find that spreads widen with proxies for inventory-carrying costs, including forecasts of price risk and a measure of liquidity costs. Increases in spreads before nontrading periods can also be attributed to inventory costs. The location of currency quotes in relation to value is not constant, and the outcome of hypothesis tests regarding changes in currency value can be sensitive to allowances for variation in quote location.
Key words: Biddask spreads; Inventory costs; Inventory control; Currency markets JEL classification: Gl5; F31
1. Introduction
Capital market researchers have recently sharpened their focus on micro- economic issues, including the roles of market organization, trading volume, and market-maker inventory management in explaining observed asset prices and trading costs. Most studies of market microstructure, both theoretical and empirical, are limited to equity markets. Relatively little analysis focuses on
Correspondence to: Hendrik Bessembinder, Department of Finance, Arizona State University, Tempe AZ 85287-3906, USA.
*Earlier versions of this paper were titled ‘Inventory Costs and BiddAsk Spreads: Evidence from Foreign Exchange Markets’. I thank Corrine Bronfman, Kalok Chan, Richard Lyons, Mike Melvin, Robert Neal, Paul Seguin, and seminar participants at the University of Washington, the University of Colorado, the University of Arizona, Brigham Young University, the University of Wisconsin, and Arizona State University for helpful comments, and Jay Coughenour for research assistance. I particularly wish to acknowledge the substantial improvements in this paper attributable to comments provided by Clifford Smith (the editor) and an anonymous referee.
0304-405X/94/$07.00 0 1994Elsevier Science B.V. All rights reserved
318 H. Bessmbinder. Bid-ask spreads in .foreign exchange markets
what may be the world’s most active market: that for foreign exchange.’ This paper provides evidence on quotations and bid-ask spreads in the wholesale currency markets.
Currency markets provide an interesting alternate arena for developing and testing market microstructure theories because they differ from the equity markets in their organization, in the characteristics of the traded assets, and in the nature of the relevant information flows. In contrast to the centralized, order-driven specialist system used on the New York Stock Exchange (NYSE), for example, the wholesale currency markets are decentralized, quote-driven dealer markets. Moreover, there is no centralized transactions reporting system for currency trades. Many trades between currency dealers are effected through brokers, however, who also serve as information clearing houses. Most equity issues are traded on markets with specified daily openings and closings. Except for weekends and bank holidays, foreign exchange markets remain active around the clock. NYSE specialists tend to specialize in market making; in contrast, currency dealers, who are typically large commercial banks, engage in other business activities that require taking positions in currencies. Whereas equity values depend on both macroeconomic and firm-specific information, currency valuation depends primarily on macroeconomic information, which may imply a reduced potential for market-maker losses to better-informed traders. However, central banks periodically intervene in foreign exchange markets with the intent of altering transactions prices, providing currency market makers with a problem (or opportunity) not typically faced by equity market makers.
In equity markets, specialists’ net equity positions are typically regarded as inventory, and currency is regarded as the numeraire. In currency markets, however, it remains an open question which currency should be regarded as inventory and which (if either) should be regarded as the numeraire. In addition, equity prices are always quoted in currency per equity share. Terms of quotation in currency markets, however, are a matter of convention, which varies across currencies. The distributional properties of important variables such as bid-ask spreads are not invariant to the quoting convention. Finally, unlike the equity markets, currency markets do not impose a prespecified minimum tick. Market makers can state quotes as finely as desired; this allows for analysis of fully endogenous asset prices and transaction costs.2
‘A recent estimate placed average daily foreign exchange trading at $650 billion. By comparison, the NYSE’s largest volume day (October 19, 1987) saw $21 billion in trading. These figures appeared in the Wall Street Journal, March 1, 1990, page Cl.
‘On the NYSE, for example, the finest price that can be quoted for stocks over one dollar per share is one-eighth of a dollar. Hasbrouck (1991) notes that discreteness induced by minimum-tick rules may explain his finding that inventory-control theories do not explain equity quotes. Similarly, Jang and Venkatesh (1991) assert that minimum-tick rules explain their finding that NYSE quote revisions do not conform to theoretical predictions for most of the observations in their sample.
H. Bessembinder, Bid-ask spreads in foreign exchange markets 319
This paper contributes to the understanding of foreign exchange market microstructure in three ways. First, it provides descriptive data on quoted biddask spreads in the foreign exchange markets. Despite the absence of con- straints imposed by minimum-tick rules, spreads quoted by market makers are shown to cluster on a few values. Because of variation in exchange rates, spreads stated in nonconventional terms (after each quote is inverted) cluster substan- tially less. I also evaluate the effect of clustering and quoting conventions on inference regarding market microstructure hypotheses.
Second, I provide empirical evidence on the determinants of time-series variation in currency market spreads. Previous research reports that bid-ask spreads in currency markets widen (i) with recent volatility [Glassman (1987) and Boothe (1987)], (ii) with measures of trading volume [Glassman (1987)], and (iii) on Fridays [Glassman (1987) and Bossaerts and Hillion (1991)]. Here, 1 show that spreads also widen with forecasts of inventory price risk, with a measure of liquidity costs, and, consistent with prior research, before weekend and holiday nontrading intervals. I find, however, that the increase in spreads before weekends and holidays can be fully explained by increased sensitivity of spreads to risk and liquidity costs over nontrading intervals. This analysis also supports the conclusion that the expected and unexpected components of trading volume have heterogeneous effects on bid-ask spreads.
Third, I introduce a simple procedure for documenting variation in the placement of bid and ask quotes in relation to underlying asset value. Since market makers can induce changes in inventory by varying quotes in relation to value, this procedure can be used to test inventory-control theories. Market makers in this sample react to increases in dollar-denominated interest rates and the approach of weekend nontrading by reducing foreign currency quotes in relation to value. This behavior is consistent with efforts to reduce foreign currency positions in favor of dollar positions at those times. I also find that the outcome of hypothesis tests regarding changes in currency value can be affected by allowing for time variation in the placement of quotes in relation to value.
2. Foreign exchange market structure and quoting conventions
2.1. The foreign exchange markets
The primary foreign exchange market makers are banks located in money centers, including London, Zurich, New York, Tokyo, and Hong Kong. They operate as dealers, trading with each other as well as with nonbank customers. Banks can indicate their willingness to trade currencies by entering ‘indicative’ bid and ask quotes on electronic systems provided by vendors such as Reuters and Telerate. Actual transactions are completed by direct private
320 H. Bessemhinder, Bid-ask spreads in .foreign c~xchongr markets
communication3 In their description of quote activity in the wholesale foreign exchange market, Goodhart and Demos (1990) note that the market operates on a 24-hour basis on weekdays, and closes (in the sense that very few or no quotes are entered on the electronic systems) only on weekends and some holidays.
Detailed data on transactions in this market are elusive, since the banks involved need not report their private dealings. Periodic surveys by the Federal Reserve Bank of New York, however, provide some descriptive information about the New York market. For example, during March 1986 the mean reported transaction size is $3.6 million. Approximately 60% of the transactions are spot, which are typically settled two business days later. Swap transactions, each of which is a package of a spot transaction and a forward transaction, make up 30% of the total, and outright forward transactions make up the remaining 1O%.4 Over 85% of the transactions involve two banks, trading either directly or through a broker.
2.2. Quotations in the foreign exchange markets
The convention in the foreign exchange market is to quote most major currencies against the U.S. dollar in ‘European terms’, where prices are the quantity of the foreign currency to be exchanged for each dollar. An exception is the British pound, which is typically quoted in ‘American terms’; prices are the quantity of U.S. dollars per pound.
The database used in this study is a set of daily spot and six-month forward currency quotations, as of the close of London trading, from January 1979 to December 1992. Bid and ask quotes for the British pound, Swiss franc, German mark, and Japanese yen against the U.S. dollar are provided by Data Resources, Inc. (DRI), which obtains the data from Reuters. The prices are quoted by a ‘representative’, but unidentified, bank for large transactions. The data as provided by DRI have been converted to American terms.
Table 1 provides summary information on typical bid-ask spread quotes in the wholesale foreign exchange markets. Each figure reports the percentage, by currency, of the observed spreads that take (or, because of the noise created at inversion, are rounded to) the indicated value. Each spread is calculated both in American terms - by subtracting the bid reported by DRI from the ask - and in European terms - by subtracting the inverse of the ask reported by DRI from the inverse of the bid.
3Trading technology in the foreign exchange markets was recently altered by the introduction of the Reuters 2000 Dealing system, which allows banks to complete transactions electronically [see Lyons (1993b) for a description]. This system was not available during the sample period used for this study.
“The swap transactions described here differ from currency swaps as described, for example, by Smith, Smithson, and Wakeman (1986), which can be viewed as a package of forward contracts.
H. Bessembinder, Bid-ask spreads in foreign exchange markets 321
322 H. Bessrmhinder, Bid-ask spreads in ,foreign exchange markets
Most notable of the results in table 1 is the tendency for quoted spreads to cluster on a few observations when stated in conventional terms (American for the pound, European for the mark, yen, and franc). The observed spread takes the value of 10 for 53% of the quotes (averaged across the four currencies), and the values of 5, 15, or 20 for 23% of the quotes.5 In equity markets, the minimum-tick rule forces spreads to take one of a few observations. Currency market spreads, in contrast, cluster despite the absence of predetermined con- straints. Because of variation in exchange-rate levels, spreads stated in noncon- ventional terms (European for the pound. American for the mark, yen, and franc) display substantially less clustering.
The observed clustering presents two issues for researchers. The first is why unconstrained prices cluster endogenously.” The second is how sensitive infer- ence about microstructure hypotheses is to the use of highly clustered conven- tional quotes versus less clustered nonconventional quotes.
3. Research design and data characteristics
In this analysis. I examine time variation in currency bid&ask spreads, focusing on the potential role of inventory carrying costs. I then introduce a procedure for documenting variation in the placement of quotes in relation to value and provide evidence that market makers vary quote placement as a function of observable variables. Finally, 1 assess the sensitivity of estimated coefficients and statistical inference to the quoting convention.
3. I. Detertttinan ts of‘ bid-ask spreads
Demsetz (1968) characterizes the bid-ask spread as the cost of obtaining ‘immediacy’, the right to transact without significant delay. Microstructure theory implies that bid-ask spreads must cover three costs incurred by providers of immediacy: order-processing costs, asymmetric-information costs, and inven- tory carrying costs. [See Stall (1989) for a synthesis.] Here. I investigate whether inventory-cost proxies can significantly explain time-series variation in currency spreads.
Money center banks engage in numerous business activities, including loans to business customers, borrowing and lending in the Euromarkets, and market
‘Units are dollars, 10.000 for the pound. yen: 100 for the Japanese yen. francs, 10.000 for the Swiss franc, and marks. 10.000 for the German mark.
“Harris (1991) notes that transaction prvxs for common stocks cluster on quarters. indicating endogenous clustering beyond that required by the minimum one-eighth price move.
H. Bessembinder. Bid-ask spreads in foreign exchange markers 323
making in derivatives such as options, that require taking positions in foreign currencies. Since these currency positions are taken for reasons other than market making, the definition of a bank’s market-making inventory and the identification of inventory carrying costs pertinent to providing immediacy in the spot currency markets are complicated.
In standing ready to trade at quoted bid and ask prices, a market-making bank commits to being able to deliver either currency at settlement two business days after the transaction. Therefore, the degree of liquidity distinguishes cur- rency positions taken for market making. In practice, market-making banks settle foreign currency transactions using currency positions maintained in ‘nostro’ accounts with correspondent banks or branches in each country whose currency is dealt [see Tygier (1988)].
A bank can promise to provide immediacy to its customers either by holding a liquid inventory of currencies, or by demanding liquidity from other market participants. Holding a currency inventory imposes opportunity costs and the risk of changes in inventory value. Opportunity costs arise because the interest rates that can be earned on the highly liquid inventories required to make a spot market are typically less than rates that can be earned on less liquid deposits. The alternative to maintaining liquid currency inventories is to settle the net obligations resulting from imbalances in customer-generated buy-and-sell or- ders by making additional transactions (i.e., by demanding immediacy) in the open market. For these open-market transactions, however, the bank must purchase at another banks ask price or sell at another bank’s bid price, effectively paying the bid-ask spread on its settling transactions. Earning a spread on transactions associated with order imbalances requires that the bank be a net supplier of liquidity to other traders.
For several reasons, the costs of carrying currency inventories are likely to increase as the weekend approaches. First, the opportunity-cost component increases over weekends because inventories are held for more days. Second, the risk of changes in inventory value may increase over the weekend. Third, the foreign exchange market is illiquid over the weekend.
3.3. Mean spreads and exchange-rate movements
Table 2 presents descriptive statistics on mean exchange-rate movements and mean bid-ask spreads. It also reports differences between means on days near weekends and bank holidays and means on other days, making it possible to determine how much exchange-rate movements and spreads differ around weekend and holiday nontrading intervals. Panel A presents mean daily per- centage changes in currency exchange rates, where each exchange rate is defined as the midpoint of bid and ask quotes stated in American terms. Panel A also presents means of absolute values of percentage changes in exchange-rate midpoints to provide summary information about currency market risk.
Tabl
e 2
Mea
” bi
d-as
k sp
read
s,
exch
ange
-rat
e ch
ange
s,
and
shif
ts
in m
eans
ar
ound
no
ntra
dlng
in
terv
als
(dai
ly
data
. Ja
nuar
y 19
79
to
Dece
mbe
r 19
92,
N =
3544
). ~_
__
Pan
el
A:
Erc
hmqe
ra
te
mow
men
ts
Full
sam
ple
Diffe
renc
e fro
m
mid
wee
k D
iffe
renc
e:
Dav
be
fore
ho
lidav
s vs
. ot
her
davs
b
Mon
day
Frid
ay
Lon
don
only
N
ew
Yor
k on
ly
Tok
yo
only
L
ondo
n an
d N
ew
Yor
k A
ll th
ree
C.V
.”
_ ~
~
r-st
at
~~
-
____
~
~
-1
MC
I"
t-st
at
Mea
” r-
stat
M
C?“
” t-
stat
M
ea”
Per
cent
ch
ange
in
sp
ot
exch
ange
-rat
e m
idpo
int
- 0.
0564
-
I .79
-0.1
830
~ 1.
28
0.03
29
0.33
-0
.053
1 -0
.065
5 -
1.92
-0
.232
0 -
1.51
-0
.017
9 -0
.17
-0.0
700
-0.0
481
~ 1.
69
-0.0
497
-0.3
9 -0
.090
1 1.
01
-0.0
174
-0.0
701
- 2.
23
-0.1
902
-1.3
4 -0
.002
3 -0
.02
-0.1
310
Abs
olut
e va
lue of
perr
ent
chan
ge
in
spot
a-
chan
ge-r
are
mid
poin
t
0.02
31
1.08
-0
.007
1 -0
.07
-0.0
249
-0.3
7 0.
0396
0.
0384
1.
72
0.01
63
0.16
-0
.016
6 -0
.24
0.07
28
0.02
61
I .34
-0
.064
4 -0
.73
0.05
13
0.85
0.
0211
0.
0360
1.
71
0.07
37
078
-0.0
567
-0.8
6 0.
0882
t-st
at
ME
I”
Me”
” M
ea”
1-st
at M
‘S””
t-
stat
Bri
tish
poun
d -
0.00
87
85.7
-0
.036
8 -
1.14
Sw
iss
fran
c 0.
0019
29
4.4
~ 0.
0354
-
1.01
Ja
pane
se
ye”
0.01
26
52.7
~
0.03
99
- 1.
37
Ger
man
m
ark
0.00
34
224.
3 -0
.053
4 -
1.66
-0.7
0 0.
0363
0.
35
0.36
62
1.75
-
0.85
-0
.034
8 -0
.31
0.21
68
0.96
-0
.25
- 0.
0428
-
0.45
0.
3181
I .6
8 -
1.73
0.
0040
0.
04
0.23
80
1.14
Bri
tish
poun
d 0.
5306
0.
934
0.09
18
4.17
S
wis
s fr
anc
0.59
07
0.87
6 0.
0893
3.
89
Japa
nese
ye
n 0.
4779
0.
936
0.08
89
4.47
G
erm
an
mar
k 0.
5371
0.
903
0.11
16
5 19
0.76
-0
.033
7 -
0.47
-
0.06
25
- 0.
44
1.34
-0
.118
9 -
1.59
0.
0093
0.
06
0.45
0.
0158
0.
24
0.05
73
0.44
1.
74
-0.0
719
- 1.
03
-0.0
617
-0.4
4 -
Pan
el
B
Pcw
en~
e hi
d-as
k sp
read
s
Full
sam
ple
Dit
Ter
ence
fr
om
mid
wee
k ~_
___
~~
DitT
eren
ce:
Day
be
fore
ho
liday
s vs
. ot
her
days
b
Lon
don
and
Lon
don
only
N
ew
Yor
k on
ly
Tok
yo
only
N
ew
Yor
k
Mea
” f-
stat
M
CI”
t-
stat
M
ea”
t-st
at
MC
I”
t-st
at
MK
I”
Mon
day
Frid
ay
~~
C.V
.”
MC
I”
t-st
at
MC
I”
t-st
at
All
thre
e
Me”
” r-
stat
Spo
t sp
read
s’
Bri
tish
poun
d 0.
0618
0.
496
0.00
10
0.76
0.
0063
4.
86
0.00
39
0.65
0.
0019
0.
46
0.00
36
1.12
0.
0318
7.
16
0.05
05
5.71
Sw
iss
franc
0.
0798
0.
692
o.ca
l7
0.30
0.
0183
8.
14
0.00
36
0.34
-0
.002
6 -0
.36
0.00
75
1.33
0.
0707
9.
13
0.11
14
7.20
Ja
pane
se
yen
0.06
37
0.53
8 -0
.ooo
5 -0
.30
0.01
04
7.03
0.
0075
1.
11
0.00
48
1.02
0.
0012
0.
33
0.01
83
3.67
0.
0938
9.
57
Ger
man
m
ark
0.05
24
0.60
4 o.
ooo4
0.
27
0.00
77
5.76
0.
0036
0.
58
0.00
12
0.29
0.
0010
0.
28
0.02
72
5.91
0.
0527
5.
76
Bri
tish
poun
d 0.
0942
Sw
iss
fran
c 0.
1458
Japa
nese
ye
n 0.
1069
G
erm
an
mar
k 0.
0868
Six-
mon
th
forw
ard
spre
ad?
0.39
7 0.
0020
1.
23
0.00
73
4.63
o.
co33
0.
45
0.00
10
0.20
0.
0047
1.
19
0.03
53
6.51
0.
0587
5.
44
0.47
8 0.
0006
0.
21
0.01
91
6.44
0.
0023
0.
16
-0.0
023
-0.2
4 0.
0092
1.
25
0.08
82
8.77
0.
1372
6.
83
0.64
1 -0
.001
0 -0
.47
0.01
14
5.29
0.
0045
0.
46
0.00
22
0.34
0.
0004
0.
08
0.02
77
3.81
0.
1164
8.
10
0.42
0 0.
0012
0.
77
0.00
85
5.55
0.
0020
0.
28
o.oo
o9
0.19
0.
0038
0.
99
0.03
10
5.87
0.
0626
5.
96
Pane
l C’
Ab
solu
te
spot
bid
-ask
sp
read
s
Full
sam
ple
Dif
fere
nce
from
m
idw
eek
Dif
fere
nce:
D
ay
befo
re
holid
ays
vs.
othe
r da
ysb
-~~_
_~
- ~
~~
_~~
Lon
don
and
Mon
day
Frid
ay
Lon
don
only
N
ew
Yor
k on
ly
Tok
yo
only
N
ew
Yor
k A
ll th
ree
~ .
_~
Mea
n C
.V.”
M
Cd”
f-
stat
M
ean
1-st
at
Mea
n t-
stat
M
ean
I-st
at
Mea
n f-
stat
M
ean
t-st
at
Mea
n f-
stat
Bri
tish
poun
d’
10.4
72
0.51
3 0.
133
0.56
1.
301
5.64
0.
7631
0.
72
0.38
72
0.53
0.
4084
0.
72
5.51
81
7.12
Sw
iss
fran
c’
10.3
952
6.74
14
.333
0.
745
~ 0.
064
- 0.
18
3.82
1 8.
37
1.33
13
0.63
~
0.52
22
- 0.
36
1.25
99
1.12
11
.849
1 7.
70
18.6
475
6.07
Japa
nese
ye
ns
11.7
76
0.59
5 -
0.06
3 -
0.21
2.
200
7.31
2.
2039
1.
60
0.93
15
0.98
0.
2875
0.
39
3.43
94
3.38
15
.194
3 7.
54
Ger
man
m
ark’
10
.730
0.
570
0.07
7 0.
29
1.81
1 6.
92
0.77
52
0.65
0.
1076
0.
13
0.45
35
0.71
5.
6376
6.
39
10.1
372
5.77
“Coe
ffic
ient
of
var
iatio
n “L
ondo
n on
ly,
New
Yor
k on
ly,
and
Tok
yo
only
co
lum
ns
repo
rt
diff
eren
ces
in m
eans
on
day
s be
fore
ho
liday
s ob
serv
ed
in t
he i
ndic
ated
ci
ty (
but
not
the
othe
r tw
o) a
nd
mea
ns
on o
ther
da
ys.
The
Lon
don
and
New
Y
ork
colu
mn
repo
rts
shif
ts
in m
eans
pr
ior
to h
olid
ays
obse
rved
m
bot
h in
dica
ted
citie
s.
obse
rved
in
all
thre
e ci
ties.
T
he
‘All
thre
e’ c
olum
n re
port
s sh
ifts
in
mea
ns
prio
r to
hol
iday
s
‘Exc
ess
of s
pot
ask
over
sp
ot
bid
divi
ded
by
the
mid
poin
t of
spo
t bi
d an
d as
k pr
ices
. dE
xces
s of
six
-mon
th-f
orw
ard
ask
over
w
-mon
th-f
orw
ard
bid
divi
ded
by
the
mid
poin
t of
for
war
d bi
d an
d as
k pr
ices
. ‘D
olla
rs
x 10
m4.
‘C
urre
ncy
units
x
10-4
. gY
en
x lo
-?
326 H. Bessembinder, Bid-ask spreads in foreign rxchunge markrts
Mean exchange-rate movements are close to zero in all four markets. Abso- lute values of percentage changes in currency values average near 0.5% per day in each market. Notably, in each market, price volatility is significantly higher on Mondays (measured from Friday close to Monday close) than on other days, a finding that may help explain shifts in bid-ask spreads around weekends.’
Panel B of table 2 provides descriptive statistics on percentage spot and forward bid-ask spreads (each defined as the ask price less the bid price divided by the mean of ask and bid). Percentage currency spreads are relatively small. Mean spot spreads range from 0.052% for the German mark to 0.080% for the Swiss franc. Although small, these estimates potentially overstate the average percentage cost of wholesale currency transactions: The bid and ask prices quoted by a representative bank may not reflect the highest bid or lowest ask available in the market, and some transactions completed in private commu- nication occur inside the market maker’s indicative quotes. Mean forward currency spreads are larger than spot spreads, but still small. They range from 0.087% for the German mark to 0.146% for the Swiss franc.
By comparison, Stoll(1989) reports that spreads on over-the-counter equities range from 1.2% for the largest decile of firms to 6.9% for the smallest decile, and Amihud and Mendelson (1986) report spreads on portfolios of NYSE equities ranging from 0.5% to 3.2%. That bid--ask spreads are smaller in currency markets than in markets for individual equities probably reflects economies of scale resulting from large currency trading volumes, smaller return variances, and a smaller likelihood of market-maker losses due to asymmetric information.
Consistent with results reported by Glassman (1987), percentage spreads in this sample are significantly higher on Fridays than on other days. Panel C of table 2 reports mean absolute (rather than percentage) spot spreads quoted in conventional terms. European spreads are also significantly higher on Fridays. This indicates that the observed increase on Fridays derives from widening of quoted spreads rather than from the behavior of the exchange rate itself.
Weekends and bank holidays share increased risk and decreased liquidity. If the increase in spreads preceding weekends reflects increased costs due to these characteristics, spreads should also rise before bank holidays. Holidays ob- served in the several cities that are centers for currency trading do not always coincide, however. 1 investigate bank holidays in London, New York, and Tokyo, and differentiate holidays observed in only one center from holidays observed in two or all three centers.8 The columns of table 2 labeled ‘London
‘Currency volatility is also higher across bank holidays (measured from the pre-holiday close to the post-holiday close) than on other days. The increase in absolute returns averages 27% across the four currencies.
“New York holidays are identified as days for which no equity returns are listed on the CRSP tapes. London and Tokyo holidays are identified from publications geared to business visitors. These holidays are verified by checking that equity return databases (also obtained from DRI) for London and Tokyo do not report prices on the holidays.
H. Bessembinder, Bid-ask spreads in foreign exchange markets 327
only’, ‘New York only’, and ‘Tokyo only’ report differences between mean spreads observed the last day before holidays celebrated in the indicated city, but not the other two, and mean spreads on all other days. Spreads do not increase by a significant margin before any of the single-country holidays.
The column of table 2 labeled ‘London and New York’ reports increases, in relation to all other days, in mean spreads observed the last day before holidays celebrated in both New York and London. The column labeled ‘All three’ reports shifts in mean spreads the day before holidays observed in all three cities. (New Year’s Day is the only occurrence in the sample.) These point estimates are uniformly positive and significant, indicating increased spreads before holidays observed in multiple financial centers. The increases are relatively large. Before London and New York holidays, spreads increase by over 50% (averaged across the four currencies). Before holidays observed in all three cities, spreads more than double on average. These findings are consistent with the reasoning that holidays observed simultaneously in multiple financial centers are associated with higher spreads due to decreased liquidity, while holidays observed in only a single financial center do not degrade liquidity significantly. It is puzzling, however, that increases in spreads before these holidays are substantially larger than increases before weekends.
Table 2 also reports coefficients of variation (ratios of standard deviation to mean) for the overall sample. Despite the frequency with which a few spreads are quoted, as documented in table 1, spreads display nontrivial variability, with coefficients of variation for spot spreads ranging from about 0.50 to about 0.75. Coefficients of variation do not differ markedly for absolute versus percentage spreads.
4. The time-series behavior of currency bid-ask spreads
In this section I report results of regressing time series of currency spreads on inventory-cost and trading-volume proxies. Results are reported for percentage spot spreads and, to verify robustness, absolute spot spreads quoted in Euro- pean terms. The same analyses are conducted for absolute spot spreads quoted in American terms and for six-month forward spreads. Results (which are not reported) are fully consistent with those reported here.
4.1. Inventory-cost proxies
To evaluate whether spreads for wholesale foreign exchange transactions depend on inventory costs, I use three proxies for inventory carrying costs: forecasts of price risk, interest-rate-based measures of liquidity costs, and a non- trading indicator. To assess whether spreads vary with trading volume, I include measures of expected and unexpected trading activity.
328 H. Bessembinder. Bid-ask spreads in ,foreign exchange markets
One component of inventory carrying costs arises from uncertainty in underly- ing asset value. Glassman (1987) and Boothe (1987) report that spreads rise with recent volatility. Here, I exploit the well-documented regularity that financial market volatility is autocorrelated to construct a forecast of price volatility, and I assess whether spreads vary with this forecast. This reflects the reasoning that market makers base bid and ask prices on their assessments of volatility over upcoming periods. Baillie and Bollerslev (1989) report that the conditional hetero- skedasticity in daily spot exchange rates is well represented by a GARCH(l,l) specification. Conditional volatility is estimated for this study using a GARCH(l,l) specification that also includes holiday and weekend indicator variables in the variance equation. The forecast risk variable used in the empirical analysis is the conditional variance from the GARCH specification led by one day.
A measure of the opportunity cost resulting from the requirement to maintain liquid inventories is the difference between the interest earned on highly liquid positions and the interest that could have been earned on similar but less liquid positions. I use Eurodollar (bid) interest rates quoted at the London close to construct two measures of liquidity costs. 9 The first is the rate on one-month Eurodollar deposits minus the rate on overnight Eurodollar deposits. This measure can be viewed as the sum of two components: one that reflects the higher liquidity costs inherent in holding overnight positions and one that reflects intertemporal considerations such as expected future changes in over- night rates. If the second component were zero, the measure would be exact; since it is not, this variable measures true liquidity costs with error.
The second measure of liquidity costs is less restrictive in that its accuracy does not require that the intertemporal component be zero, but requires only that this component be equal across short maturities. I estimate the intertem- poral component as the implied forward interest rate applicable to the second month after the observation date minus the one-month rate on that date.
The final measure of liquidity costs is the first measure (which includes liquidity costs plus the intertemporal component) minus this estimate of the intertemporal component. This final measure is roughly equal to the difference between the slope of the interest-rate term structure over the first month and the slope over the second month. The empirical results reported are based on the second measure of liquidity costs. Results based on the first measure, however, support the same conclusions.
To evaluate the importance of the approach of nontrading intervals in determining currency bid-ask spreads, I include a nontrading indicator variable set equal to one on Fridays and on the last trading day before holidays.” I also
91t might be preferable to use a separate measure of liquidity costs for each currency, but data on overnight Euro deposit rates for currencies other than the dollar are not available.
“For this analysis, I set the indicator equal to one for holidays celebrated in both London and New York. I repeat each analysis using separate Friday and holiday indicators, with conclusions unaltered.
H. Bessembinder. Bid-ask spreads in foreign exchange markets 329
examine whether the effects of interest-rate and risk variables are more pro- nounced before nontrading intervals by including the product of the nontrading indicator and these variables in the analysis.
4.2. Trading volume and spreads
I also evaluate the relation between trading volume and spreads. Glassman (1987) includes measures of trading volume as explanatory variables for cur- rency spreads and obtains positive coefficient estimates. Empirically, trading volumes are highly autocorrelated, implying that volumes can be forecast to a substantial degree. I posit that forecastable volume and deviations of actual volume from the forecast imply differing costs for market makers. The mixture of distributions hypothesis [Tauchen and Pitts (1983)] implies that innovations in trading volume are correlated with the number of information arrivals. Therefore, unforecastable volume is likely to be correlated with risk and with information asymmetry. Expected volume, in contrast, can be considered pre- determined. If there are economies of scale in market making, increased fore- castable volume is likely to be associated with decreased spreads. Easley and O’Hara (1992) formally develop a model that implies spreads decrease with forecastable trading volume.
Lacking a comprehensive database on trading volume in the wholesale foreign exchange market, I follow Glassman (1987) in using trading volumes in CME currency futures as instrumental variables for spot volumes. In markets where both spot and futures trading volumes are observable, the two are highly correlated.” Futures volume data are obtained from the Columbia University Futures Center. I employ an ARIMA(lO,l,O) specification to decompose futures trading volume into forecastable and unexpected components.
Evidence in Glassman indicates that intercepts in regressions of bid-ask spreads on variables such as risk and volume vary by economically and statis- tically significant margins from year to year. This is also true for the current sample. ’ 2 Since the cause of these shifts is unknown, I accommodate them by including indicator variables for each year other than 1985.
“For example, Bessembinder and Seguin (1992) report that the correlation between daily Standard and Poors 500 futures volume and spot NYSE volume is over 0.60. They also provide evidence consistent with the reasoning that expected and unexpected trading volumes convey different information to market participants.
“This raises the question of whether the slope coefficients estimated are stable over time. I also estimate specifications, similar to those reported below, that allow slope coefficients to vary annually or across three subperiods. Results, which are not reported but are available on request, support two conclusions. First, there is some evidence of statistically significant shifts in slope coefficients over time. The hypothesis that slope coefficients on individual explanatory variables are constant over time can be rejected at the 0.10. level in approximately one-third ofall cases examined. Second, these shifts do not lead to significant qualifications of the conclusions drawn here. In particular, signs of estimated slope coefficients rarely change across subperiods.
330 H. Bessembinder. Bid-ask spreads in ,foreign exchange markets
4.3. Estimation and inference
I obtain coefficient estimates using generalized method of moments (GMM). For the specifications reported in the tables, the set of instruments is identical to the set of regressors, resulting in coefficient estimates that are identical to those obtained by ordinary least squares estimation. To obtain standard error esti- mates and to test the hypotheses, however, 1 employ the covariance matrix specified by Newey and West (1987a), which allows for the presence of condi- tional heteroskedasticity and autocorrelation.
I test joint hypotheses using a Wald statistic described by Newey and West (1987b). Let k denote the number of parameters estimated for each of n equa- tions, B denote the nk x 1 vector of coefficient estimates, and R denote the appropriate 4 x nk restriction matrix for a test of RB = 0, where 0 is a 4 x 1 vector of zeros. The Wald statistic is computed as Q = (RB)‘(RWR’-‘RB, where W is the nk x nk parameter estimate covariance matrix described by Newey and West (1987a).i3 This test statistic follows an asymptotic chi-square distribution with q degrees of freedom.
4.4. Evidence on time-series variation in currency bid-ask spreads
Tables 3 and 4 present the results of GMM regressions of percentage spot spreads and absolute spot spreads quoted in European terms on the variables discussed above. To allow comparison of coefficient estimates across currencies, each spread quoted in European terms is divided by its own time- series mean.
4.4.1. Inventory costs and time-series variation in spreads
Point estimates reported in tables 3 and 4 are generally consistent with the implication that currency bid-ask spreads widen with inventory carrying costs. The estimated coefficient for the effect of forecast risk on currency bid-ask spreads, reported in panel A of table 3, is positive and significant for all four currency markets. Consistent with greater risk increasing invent- ory carrying costs, end-of-day spreads are positively related to the anticip- ated riskiness of holding a position in the currency over the next trading day.14
r3For the reported results I use eight lags to compute the Newey-West matrix, which corresponds to the fourth root of the sample size [see Newey and West (1987a)]. Sensitivity tests over the range 5 to 20 lags indicate little variation in estimated standard errors.
“%ince banks may deal in more than one currency, the risk of a currency portfolio might be a more appropriate measure than univariate risk series. As a sensitivity test, I estimate regressions like those reported in tables 3 and 4 using the risk on currency portfolios, with varying weights, in place of single-currency risk. Results are little altered from those reported.
H. Bessembinder. B&ask spreads in foreign exchange markets 331
The results are also consistent with currency bid-ask spreads varying posi- tively with the opportunity costs of maintaining a liquid inventory. The esti- mated coefficient on the interest-rate-based proxy for the opportunity cost of liquidity is positive for each currency, and the hypothesis that this coefficient equals zero for all four currencies is readily rejected.
4.4.2. Trading volume and spreads
Coefficient estimates on the forecastable and unexpected components of futures trading volume, used as a proxy for trading volume in the interbank foreign exchange market, support the conclusion that forecastable and unex- pected trading volumes have heterogeneous effects on bid-ask spreads. For each of the four currencies, the coefficient estimate on unexpected trading volume exceeds the coefficient estimate on forecastable volume. A Wald test rejects the hypothesis that the two volume coefficients are equal to each other for the system of four currencies. Consistent with the model of Easley and O’Hara (1992) the estimated coefficient on expected trading volume is negative for each currency, implying decreased bid-ask spreads when forecastable volume in- creases. A Wald test of the hypothesis that these coefficient estimates jointly equal zero is rejected (p-value < 0.001) when European quotes are used, but not (p-value = 0.235) when percentage quotes are used. In contrast, each point estimate for the effect of unforecastable volume on bid-ask spreads is positive, although these estimates do not differ significantly from zero.
4.4.3. Explaining the increase in Friday and holiday spreads
The specifications reported in tables 3 and 4 include a nontrading indicator variable; the coefficient estimates shifts in the regression intercept before week- ends and holidays. If the increases in bid-ask spreads on Fridays and holidays (as documented in table 2) result wholly from changes in the other explanatory variables (such as forecast risk, which increases on Fridays and before holidays) that are included in the time-series regression, coefficients on the nontrading indicator variable should not differ significantly from zero. The actual coefficient estimates on the nontrading indicator reported in panel A of tables 3 and 4 are positive and statistically significant for each of the four currencies, implying that the other variables in the regression do not fully explain increases in spreads before nontrading days.
To explore the possibility that the remaining increase in Friday and holiday spreads reflects increased sensitivity to risk or liquidity costs as the nontrading interval approaches, I include in each regression products of the nontrading indicator variable and the inventory-cost proxies. The coefficients on these interaction variables estimate the differential effect of inventory costs on spreads for Fridays and holidays in relation to other days. These regressions also include
Tab
le
3
Est
imat
ed
effe
cts
of i
nven
tory
-cos
t an
d tr
adin
g-ac
tivity
pr
oxie
s on
cu
rren
cy
bid-
ask
spre
ads
mea
sure
d in
per
cent
age
term
s.
The
de
pend
ent
vari
able
is
(a
sk,
- hi
d,)/
mid
,, w
here
m
id,
is t
he b
id-a
sk
mid
poin
t an
d ea
ch
quot
e is
sta
ted
in A
mer
ican
te
rms.
Jo
int
hypo
thes
es
are
test
ed
usin
g th
e W
ald
test
des
crib
ed
by
New
ey
and
Wes
t (1
987b
).
Bri
tish
poun
d
~__
~
__~
~
Swis
s fr
anc
Japa
nese
ye
n
Inve
nror
y co
st
prox
ies
FRIH
OL”
Fo
reca
st
risk
d LI
QP
RE
M’
Tra
ding
vo
lum
es’
Exp
ecte
d U
nexp
ecte
d
Tes
t?
x2 [
p-va
lue]
Yea
rly
indi
cato
rs
Inte
rcep
t 19
79
1980
19
81
1982
19
83
1984
19
86
1987
19
88
1989
19
90
1991
19
92
0.00
5 3.
41
0.01
5 5.
32
0.00
7 5.
01
0.00
7 5.
59
53.2
6 P
.ow
0.
024
4.67
0.
033
5.68
0.
032
6.26
0.
016
6.49
73
.12
ww
0.
036
1.40
0.
111
2.59
0.
063
2.48
0.
060
1.97
14
.17
[0.0
07]
- 0.
035
0.01
6
3.86
- 1.
41
1.12
[0.0
50]
0.05
4 11
.02
- 0.
027
- 6.
67
- 0.
023
- 6.
22
- 0.
005
- 0.
92
- 0.
002
- 0.
56
0.00
5 1.
43
0.01
2 3.
74
- 0.
007
- 2.
13
- 0.
004
- 1.
20
- 0.
003
- 0.
90
- 0.
003
- 0.
85
- 0.
001
- 0.
19
0.00
3 0.
88
0.00
7 1.
59
Tes
t:’
x2 [
p-va
lue]
48
7.77
W
.~l
Coe
ff
- t-
staP
C
oeff
t-
stat
b C
oeff
t-
stat
b __
___
Pan
el
A:
With
out
Frid
aq’
inte
ract
ion
1:ar
iahl
es
- 0.
039
- 0.
92
0.01
4 0.
56
2.56
[O
.l lo
]
0.07
1 8.
25
- 0.
024
- 2.
78
- 0.
018
- 2.
03
0.00
8 0.
86
- 0.
005
- 0.
81
- 0.
006
- 0.
93
- 0.
017
- 2.
67
- 0.
019
- 1.
63
- 0.
015
- 2.
87
- 0.
012
- 2.
08
- 0.
025
- 2.
84
0.00
5 0.
70
- 0.
005
- 0.
57
- 0.
006
- 1.
09
67.5
7 [O
.OO
o]
- 0.
025
0.00
7 -
1.33
0.
81
5.19
[0
.023
]
0.03
4 13
.58
0.00
8 2.
35
0.02
0 3.
98
0.03
8 10
.39
0.01
3 4.
39
0.01
2 5.
30
0.00
8 2.
78
0.00
5 1.
79
0.00
5 1.
56
0.00
6 1.
72
0.01
0 2.
08
0.03
3 7.
01
0.03
4 9.
49
0.04
7 9.
76
517.
52
Dow
Ger
man
m
ark
Coe
ff
t-st
ath
- 0.
011
- 0.
79
0.01
3 1.
63
1.80
[O
. 179
1
0.03
7 10
.87
- 0.
004
- 1.
03
- 0.
005
- 1.
17
0.00
8 1.
66
- 0.
001
- 0.
25
- 0.
005
- 1.
84
- 0.
005
- 2.
25
- 0.
006
- 2.
39
- 0.
005
- 2.
01
- 0.
003
- 1.
10
- 0.
007
- 2.
21
0.02
3 6.
05
0.01
8 4.
23
0.01
8 4.
17
186.
08
[O.O
OO
]
Cro
ss-e
quat
ion
test
”
x2
[p-v
alue
]
5.39
[0
.250
] 3.
50
co.4
773
12.0
4
337.
26
57.7
8 64
.14
147.
48
30.9
1
51.7
3 60
.12
17.0
1 15
.66
9.17
23
.76
78.1
8 14
4.10
15
2.23
[0.0
17]
P.~
l m
w
ww
D
ow
P.c
w
[@~
I C
O.~
l [0
.002
] [0
.004
] [0
.057
]
P.~
l w
w
CO
.~l
CO
.~l
Pan
el B
: W
ith
Frid
ay
inte
ract
ion
vari
able
s’
Inve
ntor
y-co
st p
roxi
es
FRIH
OL
-
0.00
9 -
2.22
-
0.00
0 -
0.03
-
0.01
5 -
2.10
-
0.00
7 -
2.07
12
.26
[0.0
16]
Fore
cast
ri
sk
0.01
9 3.
81
0.02
9 5.
52
0.02
4 4.
90
0.01
3 5.
46
53.5
8 W
.~l
Fore
cast
ri
sk *
FR
IHO
L 0.
019
2.81
0.
018
1.88
0.
041
4.08
0.
019
4.05
29
.66
Pow
LI
QP
REM
0.
004
0.23
0.
078
2.60
0.
049
2.38
0.
042
1.76
12
.99
co.0
1 l]
LI
QP
REM
*
FRIH
OL
0.09
2 2.
2 1
0.09
4 1.
69
0.03
5 0.
95
0.05
3 1.
47
6.47
C
O.1
671
3
Tes
t:’
x2 [
p-va
lue]
11
.01
[0.0
04]
6.02
[0
.049
] 17
.39
ww
17
.01
ww
31
.70
P.o
ool
g R
egre
ssio
n ad
j. R
2 0.
191
0.13
0 0.
246
0.20
4 9
~-
P
“Tes
t th
at
the
asso
ciat
ed
coef
fici
ent
is z
ero
in a
ll fo
ur
curr
enci
es
or
that
th
e hy
poth
esis
ho
lds
in
all
four
cu
rren
cies
. B
%
-sta
tistic
s ar
e ba
sed
on
the
New
eyyW
est
(198
7a)
hete
rosk
edas
ticity
- an
d au
toco
rrel
atio
n-co
nsis
tent
co
vari
ance
m
atri
x,
usin
g ei
ght
lags
. Y
‘FR
IHO
L is
an
indi
cato
r va
riab
le
equa
l to
on
e on
Fr
iday
s an
d be
fore
ho
liday
s,
and
zero
ot
her
days
. &
“For
ecas
t ri
sk
is t
he
one-
step
-ahe
ad
cond
ition
al
retu
rn
vari
ance
fr
om
a G
AR
CH
(l,l)
sp
ecif
icat
ion.
‘L
IQP
REM
is
an
estim
ated
co
st
of h
oldi
ng
liqui
d in
vent
orie
s,
deri
ved
from
E
urod
olla
r in
tere
st
rate
s.
E
R-
‘Exp
ecte
d an
d un
expe
cted
vo
lum
es
are
fitte
d va
lues
an
d re
sidu
als
from
A
RIM
A
mod
els
fitte
d to
th
e se
ries
of
CM
E
futu
res
trad
ing
volu
mes
in
uni
ts
of
10,0
00
cont
ract
s.
+$
BT
est
that
co
effi
cien
t on
ex
pect
ed
volu
me
equa
ls
the
coef
fici
ent
on
unex
pect
ed
volu
me.
g
hTes
t th
at
the
thir
teen
ye
arly
in
dica
tor
coef
fici
ents
jo
intly
eq
ual
zero
. 3’
‘R
egre
ssio
ns
repo
rted
on
pa
nel
B a
lso
incl
ude
trad
ing
volu
mes
an
d ye
arly
in
dica
tors
; es
timat
ed
coef
fici
ents
ar
e no
t re
port
ed.
‘2
‘Tes
t th
at
coef
fici
ents
on
Fo
reca
st
risk
* F
RZ
HO
L an
d L
IQPR
EM
+
FRIH
OL
jo
intly
eq
ual
zero
. : 3’
Tab
le
4
Est
imat
ed
effe
cts
of
inve
ntor
y-co
st
and
trad
ing
volu
me
prox
ies
on
abso
lute
cu
rren
cy
bid-
ask
spre
ads
stat
ed
in
Eur
opea
n (d
olla
rs
per
unit
fore
ign
curr
ency
) te
rms.
T
he d
epen
dent
va
riab
le
is a
sk,
- bi
d,.
To
faci
litat
e co
mpa
riso
ns
of c
oeff
icie
nts
each
sp
read
ha
s be
en
divi
ded
by i
ts o
wn
time
seri
es
mea
n.
Join
t hy
poth
eses
ar
e te
sted
us
ing
the
Wal
d te
st
desc
ribe
d by
N
ewey
an
d W
est
(198
7b).
Inve
ntor
y-co
st
prox
ies
FRIH
OL’
Fo
reca
st
risk
d LI
QP
RE
M’
Tra
ding
vo
lum
es’
Exp
ecte
d U
nexp
ecte
d
Tes
t?
1’
[p-v
alue
]
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rly
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cato
rs
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rcep
t 19
79
1980
19
81
1982
19
83
1984
19
86
1987
19
88
1989
19
90
1991
19
92
Tes
t:”
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p-va
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tish
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d Sw
iss
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c Ja
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man
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ss-e
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a
[p-v
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el
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Wit
h F
rida
y in
tera
ctio
n va
riab
les’
Inve
ntor
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st
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ies
FR
IHO
L
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sk
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t ris
k *
FR
IHO
L
LIQ
PR
EM
L
IQP
RE
M
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RIH
OL
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t:’
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ion
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9 C
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“Tes
t th
at
the
asso
ciat
ed
coef
fici
ent
is z
ero
in
all
four
cu
rren
cies
or
th
at
the
hypo
thes
is
hold
s in
all
four
cu
rren
cies
‘t
-sta
tistic
s ar
e ba
sed
on
the
New
ey-W
est
(198
7a)
hete
rosk
edas
ticity
- an
d au
toco
rrel
atio
n-co
nsis
tent
co
vari
ance
m
atri
x,
usin
g ei
ght
lags
. .z
‘FR
IHO
L
is a
n in
dica
tor
vari
able
eq
ual
to
one
on
Frid
ays
and
befo
re
holid
ays,
an
d ze
ro
othe
r da
ys.
B
dFor
ecas
t ri
sk
is t
he
one-
step
-ahe
ad
cond
ition
al
retu
rn
vari
ance
fr
om
a G
AR
CH
(1
,l)
spec
ific
atio
n.
F
‘LIQ
PR
EM
is
an
estim
ated
co
st
of h
oldi
ng
liqui
d in
vent
orie
s,
deri
ved
from
E
urod
olla
r in
tere
st
rate
s.
e
‘Exp
ecte
d an
d un
expe
cted
vo
lum
es
are
fitte
d va
lues
an
d re
sidu
als
from
A
RIM
A
mod
els
fitte
d to
th
e se
ries
of
CM
E
futu
res
trad
ing
volu
mes
in
uni
ts
fi
of
10,O
CQ
cont
ract
s,
s 2 gT
est
that
co
effi
cien
t on
ex
pect
ed
volu
me
equa
ls
the
coef
fici
ent
on
unex
pect
ed
volu
me.
hT
est
that
th
e th
irte
en
year
ly
indi
cato
r co
effi
cien
ts
join
tly
equa
l ze
ro.
‘Reg
ress
ions
re
port
ed
on
pane
l B
als
o in
clud
e tr
adin
g vo
lum
es
and
year
ly
indi
cato
rs;
estim
ated
co
effi
cien
ts
are
not
repo
rted
. ‘T
est
that
co
effi
cien
ts
on
For
ecas
t ri
sk *
FR
IHO
L
and
LIQ
PR
EM
*
FR
IHO
L
join
tly
equa
l ze
ro.
336 H. Bessembinder, Bid-ask spreads in ,foreign exchange markets
the volume and yearly indicator variables. The associated coefficient estimates are essentially unaltered by the inclusion of the Friday interaction variables and are not reported.
Results of estimating the time-series regressions when including these interac- tion variables are reported in panel B of tables 3 and 4. The coefficient estimate on the nontrading indicator variable is negative for all four currencies. Since the regression intercept is lower before nontrading days than on other days, these results indicate that the increase in Friday and holiday spreads is fully explained by the other variables in this specification.
The right column of panel B reports results of a Wald test of the hypothesis that all eight coefficients (two interaction terms for each of the four currencies) that estimate shifts in regression slopes on Fridays and holidays jointly equal zero. The p-value on this joint hypothesis is less than 0.001, implying that the slope coefficients relating bid-ask spreads to inventory costs change by a statis- tically significant margin before nontrading intervals. All eight of the individual coefficient estimates are positive, indicating that spreads are more sensitive to inventory-cost proxies on Fridays and holidays. The positive coefficient esti- mates on the product of the nontrading indicator and forecast risk imply that risk is more costly to market makers when combined with the lack of liquidity over the weekends and holidays. Positive coefficients on the product of the Friday indicator and the liquidity-cost proxy indicate that spreads are more sensitive to liquidity costs before nontrading intervals, which probably reflects increased opportunity costs due to longer holding periods.
To summarize, the evidence presented here indicates that currency spreads widen with proxies for inventory carrying costs, and that increased inventory carrying costs can fully explain the previously documented regularity that currency spreads are higher on Fridays than on other days. The significant coefficient estimates on inventory-cost measures obtained here contrast with the lack of evidence of inven- tory-cost effects obtained in studies conducted in equity markets.15
Notably, coefficient estimates and inference are quite consistent across results reported in table 3 for percentage spreads and in table 4 for absolute European spreads. Despite the tendency for quotes stated in conventional terms to cluster, as documented in table 1, inference with respect to the hypotheses tested here is largely insensitive to the clustering.
5. The placement of quotes in relation to currency value
The bid and ask prices quoted by market makers need not be symmetric around the underlying value of the asset. Since variation in quote placement is
“George Kaul and Nimalendran (1991, p. 649) find ‘no evidence for the existence of an inventory > 3 cost component’ (of the spread). Madhavan and Smidt (1991) find only weak evidence that specialist inventories affect quotes.
H. Bessembinder. Bid-ask spreads in foreign exchange markets 337
a standard inventory-control mechanism, the ability to test for variation in the placement of quotes in relation to value is useful for testing inventory-control theories. In addition, market makers may try to alter inventory around events that affect value. If so, avoiding bias in estimates of value changes potentially requires the accommodation of shifts in quote location. In this section I develop a simple procedure for estimating the location of bid and ask quotes in relation to underlying value. Unlike the procedure for estimating quote location intro- duced by Bossaerts and Hillion (1991), this method does not require simulta- neous observation of spot and forward quotes.
I implement the estimation procedure using currency quotes provided by the representative bank. However, without a detailed specification of desired shifts in market-maker inventories, the results are perhaps best viewed as illustrative rather than as definitive evidence of market-maker quotation strategies.
5.1. A method for documenting variation in quote placement
Let a, denote a time t location parameter, defined in relation to the ask quote, At, bid quote, B,, and unobservable value, V,, by
Vt = atAt + (1 - LX,)& . (1)
The change in the underlying asset value can be stated as
V t+1 - vr=Pt+Et+l> (2)
where pLt is the expectation at time t of the change in value over the next period
and stfl is the unexpected change. Letting S, = A, - B, denote the time t bid-ask spread, (1) and (2) can be combined to give
B ffl - B, = ,aLt + @,+I[ - St+,1 + aA + &,+I.
Eq. (3) is general, but its parameters are time-varying and cannot be estimated unless additional structure is imposed. A simple structure is obtained by assum- ing that the parameters of (3) do not vary over time: pt = pO and CI, = CI,,. With this structure imposed, (3) reduces to
B 1+1 - 4 = PO + a& - S,+ 11 + gt+ 1
Under these assumptions, the location parameter a0 can be estimated as the slope coefficient obtained in a simple regression of the change in bid price on (the opposite of) the contemporaneous change in the bid-ask spread. To
338 H. Bessembinder. Rid-ask spreads in foreign exchange markets
illustrate, suppose that the underlying value always equals the bid-ask mid- point. In this case, half of a change in the spread typically occurs by change in the bid (and half in the ask), resulting in a slope coefficient in (4) equal to one-half. If underlying value were always equal to the ask (o! = l), then, all else being equal, all changes in the spread would occur by adjustments in the bid, resulting in a slope coefficient in (4) equal to one.
Although specification (4) is useful for gaining intuition regarding this estima- tion procedure, its practical usefulness is limited because it constrains the measure of interest, x,, to be constant. I6 A less restrictive specification is obtained by the assumption that pt and a, are linear functions of observable variables: p, = p. + plX, and c(, = a0 + c(iZ,.17 Here, X, and Z, are (vectors of) observable variables that are hypothesized to affect the expected change in asset value and the placement of quotes in relation to value. With this less restrictive structure imposed, (3) can be restated as
B t+1 - 4 = PO + ~lXt+ aoCS, - St+ 11
+ ~lC-G% - zt+ 1s,+ 11 + Et+ 1 .
The parameters of (5) can be estimated by standard regression techniques. Positive estimates of ri imply that quotes are being reduced in relation to value when Z, rises, and vice versa.
5.2. Application to currency quotes
For this study, I use two variables to allow for time variation in expected changes in currency value, and four variables to allow for possible time variation in the placement of quotes in relation to currency value. Substantial evidence [surveyed by Froot and Thaler (1990)] indicates that interest-rate differentials forecast subsequent exchange-rate changes. Accordingly, I include in X, the excess of 30-day Eurodollar interest rates over 30-day local currency Euro rates (INTDIF,). To allow for weekend effects in currency values of the type documented in other asset markets, I include a Monday indicator variable
(MON,). Individual banks seeking to alter their net position in a particular currency
can do so either as a demander or as a supplier of immediacy. One method of
16The many studies that document forecastability in asset returns [see Fama (1991) for a review] suggest that p, also varies over time. If so, this variation should also be accommodated in the estimation.
“Of course, any nonlinear function can be imposed as well. 1 use linear functions for simplicity and because specification tests (described below) do not reject the simple structure for the current sample.
H. Bessembinder, Bid-ask spreads in .foreign exchange markets 339
decreasing a currency position is to decrease quotes in relation to value to increase the likelihood of customer purchases and decrease the likelihood of customer sales. Altering positions by shading quotes allows the bank to con- tinue earning a spread on transactions. Alternatively, the bank can simply sell at another market maker’s bid price, but it then implicitly pays rather than receives the spread. If banks in aggregate seek to alter currency holdings, quotes must be shaded. The model presented by Lyons (1993a, p. 13) implies that a component of each period’s currency trade is effected by nonmarket-maker customers who are induced via prices to ‘absorb the inventory imbalance of market makers as a whole’.
If market makers use quote changes to induce position changes, then ~1, will increase when market-maker positions exceed desired levels (as quotes are decreased to encourage net sales), and vice versa. But, the interpretation of coefficient estimates depends on the quoting convention. When quotes are stated in American terms, an increase in a, implies a reduction in dollar quotes in relation to the dollar value of the foreign currency. If effected for position change, the increase implies that the market maker seeks to reduce foreign currency holdings in favor of dollar holdings. When quotes are stated in European terms, the interpretation of an increase in LX, is reversed. To determine whether results are robust to the quoting convention, I estimate (5) using quotes stated in both American and European terms. To allow comparison of coefficients across currencies and quoting conventions, I divide each bid quote and each spread by the time-series mean bid quote for that currency.
Lyons (1993b) suggests that market makers’ desired currency holdings depend on relative interest rates. I include in the set Z, the change since the preceding day in the 30-day Eurodollar deposit rate (AUSZNT,) and the change since the preceding day in the local currency Euro interest rate (ALOCZNT,). Bossaerts and Hillion (1991) suggest that quotes may be asymmet- ric before weekends because central banks are more likely to intervene over weekends. Alternatively, banks may seek to alter their positions before weekends or holidays if they have a preferred currency for weathering periods of increased risk and decreased liquidity. I also include in the set Z, a Friday indicator (FM,) and a preholiday indicator (HOL,). The system of equations I estimate is
B 1+1 - Bt = ~2 + @,+I[ - &+,I + G, + ~t+l, (6)
pt = p. + p~INTDIFf + p2MON,,
a, = a, + a,FRI, + a,HOL, + a3AUSINT, + ci,ALOCINT,.
340 H. Bessembinder, Bid-ask spreads in foreign e.xchange markets
5.3. Evidence of variation in the placement qf currency quotes
I estimate system (6) by GMM. Results are reported in panel A of table 5 for spot American quotes and in panel A of table 6 for spot European quotesi Some caution should be exercised in interpreting of the point estimates obtained here. As mentioned above, the quotes used in this study are provided by an unidentified bank, and, in principle, results could differ if another bank’s quotes were used. But, since the quotation of an ask that is less than another bank’s bid or quotation of a bid that is greater than another bank’s ask gives rise to arbitrage opportunities, relatively tight limits control the degree to which quotation strategies can differ across banks.
The right column of table 5 reports Wald statistics for the hypothesis that the placement of quotes in relation to currency value does not vary (tli = ~1~ = ~1~ = LQ = 0) with the four variables used here when quotes are stated in American terms. The hypothesis that LX, is constant is rejected (p-value < 0.001) for each currency. This implies rejection of the hypothesis that the market maker quotes bid and ask prices such that currency value exceeds the bid price by a constant proportion of the bid-ask spread.
Of the four variables in Z,, the change in the U.S. interest rate has the most explanatory power for quote placement. Each point estimate of CI~ is positive and highly significant. This result is consistent with the hypothesis that the bank seeks to reduce foreign currency positions and increase dollar positions when dollar deposit rates rise. In contrast, point estimates for the effect of local currency deposit rates on the placement of quotes are mixed in sign and do not differ significantly from zero. The cross-equation Wald test rejects the hypothe- sis that tx is unchanged on Fridays (p-value = 0.017). Point estimates indicate that quotes are reduced in relation to foreign currency value on Fridays. This is consistent with efforts by the bank to reduce foreign currency holdings in favor of dollar holdings before the weekend nontrading interval. In contrast, there is no evidence of efforts to reduce foreign currency holdings before bank holidays.
The extent to which inference regarding quote placement is sensitive to the quoting convention can be determined by comparing results in panel A of table 5 for American quotes with those in panel A of table 6 for European quotes. Consistency of results implies the reversal of signs on corresponding
“For each currency, 1 use the set of regressors as instruments, which yields an exactly identified system. In estimating (6) or a similar equation, some specification checks are desirable. For example, the failure to accommodate variation adequately in expected changes in value could lead to bias in coefficient estimates due to the correlated omitted-variable problem. Here, I also estimate specifica- tions that include several additional instruments, including a time-trend variable, expected and unexpected futures trading volumes, and additional day-of-week indicators. The resulting test statistic [Hansen (1982)] for the hypothesis that the residuals are uncorrelated with the instruments does not indicate rejection (all p-values > 0.50) for any combination of instruments. Thus, I find no evidence that (6) is misspecified.
H. Bessembinder, Bid-ask spreads in foreign exchange markets 341
coefficients (except for the intercept ao). In large measure, results are robust to the quoting convention. The hypothesis that tl, is constant is again rejected (p-value < 0.001) for each of the four currencies. Each coefficient on the change in the U.S. interest rate is of the appropriate (for consistent inference) sign and, again, highly significant. Coefficient estimates for the placement of quotes on Fridays are of the appropriate sign for consistency of inference but do not differ significantly from zero.
These results support the conclusion that market makers vary the placement of quotes in relation to value as a function of observable variables, particularly the U.S. interest rate, and this conclusion is robust to the quoting convention.” More powerful tests of hypotheses regarding market-maker inventory-manage- ment policies require more detailed specifications of desired shifts in inventory.
5.4. Quote placement and inference regarding asset value
Variation in the quote-placement parameter ~1, may be of consequence for inference regarding changes in asset value. A correlation between CI, and changes in asset value might be expected if market makers seek to alter positions around the time of the event being studied. Lease, Masulis, and Page (1991) observe that transactions prices provide a biased estimate of value in situations where market-maker inventories are altered, because transactions cluster nonrandom- ly at the bid or the ask. They observe that using the bid-ask midpoint may also lead to a biased estimate if quote placement is altered. The procedure introduced here can accommodate variation in quote placement when conducting inference regarding value changes. Results from the present sample of currency quotes illustrate that inference regarding asset value can be altered by accommodating variation in quote placement.
Wald tests reported in the next-to-last column of tables 5 and 6 indicate that the hypothesis that expected currency appreciation is stationary is readily rejected for each currency. Each estimate of ~1~ is statistically significant, indicat- ing that the expected change in currency value varies with the interest rate differential. In contrast to the ‘international Fisher effect’, but consistent with prior evidence [e.g., Froot and Thaler (1990)], these point estimates imply that the currency with the higher interest rate appreciates on average against the currency with the lower interest rate.
“Intuition suggests that a should typically lie in the interval zero to one, although one might imagine scenarios in which a desire for a rapid inventory adjustment (perhaps in the face of differing opinions regarding underlying value) would allow for a to lie below zero or above one. The empirical procedure implemented here does not constrain the estimated values of a. Although the mean c1 estimate lies between zero and one for each currency regardless of the quoting convention, 26% of the daily point estimates lie below zero and 27% lie above one. In part, this reflects the simplicity of the linear specification for a, which was adopted to determine whether OL varies with observable variables. Fitted values of a: could be fine-tuned by exploring more complex functional forms.
Tab
le
5
Tes
ts
for
vari
atio
n in
the
pla
cem
ent
of q
uote
s in
rel
atio
n to
und
erly
ing
curr
ency
va
lue,
an
d fo
r va
riat
ion
in t
he e
xpec
ted
chan
ge
in c
urre
ncy
valu
e,
whe
n qu
otes
ar
e st
ated
in
Am
eric
an
term
s.
The
sa
mpl
e pe
riod
is
Jan
uary
19
79 t
o D
ecem
ber
1992
. T
he
para
met
ers
estim
ated
in
clud
e x,
, w
hich
de
fine
s th
e lo
catio
n of
und
erly
ing
curr
ency
va
lue
(V,)
rela
tive
to
bid
(B,)
and
as
k (A
,) q
uote
s ac
cord
ing
to
V, =
X
,.4, +
(I
-
a,)&
,
and
pr,
whi
ch
is t
he
expe
cted
ch
ange
in
und
erly
ing
curr
ency
va
lue
over
th
e ne
xt
peri
od.
The
se
para
met
ers
are
cons
trai
ned
to
be l
inea
r fu
nctio
ns
of o
bser
vabl
e va
riab
les,
an
d ar
e es
timat
ed
by
appl
ying
ge
nera
lized
m
etho
ds
of m
omen
ts
to
the
syst
em:
B If
, -
B,=
p,+
z,+
,[-S
t+,1
+
%%
+c,
+,,
1, =
p,
+ p
,IN
TD
IF,
+ p
*MO
N,,
r, =
a,
+ r
lFR
I,
+ a
,HO
L,
+ c
x,A
USI
NT
, +
z,A
LO
CIN
T,,
whe
re
B,
deno
tes
curr
ency
bi
d pr
ice,
IN
TD
IF,
is e
xces
s of
one
-mon
th
Eur
odol
lar
rate
s ov
er
loca
l-cu
rren
cy
Eur
o ra
tes,
M
ON
, an
d F
RI,
ar
e M
onda
y an
d Fr
iday
in
dica
tors
, re
spec
tivel
y,
HO
L,
is a
pre
-hol
iday
in
dica
tor,
AU
SIN
T,
is t
he
chan
ge
in
the
one-
mon
th
Eur
odol
lar
depo
sit
rate
, ALOCINT, i
s th
e ch
ange
in
the
on
e-m
onth
lo
cal
Eur
ocur
renc
y de
posi
t ra
te,
and
5, i
s th
eexc
ess
ofas
k ov
er
bid
pric
e at
t.
To
faci
litat
e co
mpa
riso
n of
coe
ffic
ient
es
timat
es,
each
cu
rren
cy
quot
e ha
s be
en
divi
ded
by i
ts o
wn
mea
n bi
d pr
ice.
Jo
int
hypo
thes
es
are
test
ed
usin
g a
Wal
d te
st
[New
ey
and
Wes
t (1
987b
)].
Tes
t st
atis
tics
are
asym
ptot
ical
ly
dist
ribu
ted
x2
with
de
gree
s of
fre
edom
eq
ual
to
the
num
ber
of c
onst
rain
ts.
T-s
tatis
tics
are
repo
rted
in
par
enth
eses
Bri
tish
poun
d
Swis
s fr
anc
Japa
nese
ye
n
Ger
man
m
ark
Cro
ss-e
quat
ion
Tes
t: x2
[p-
valu
e]”
Exp
ecte
d ch
ange
in
cur
renc
y va
lue
n, =
/I
” +
plIN
TD
IF,
+ p
lMO
N,
- 0.
018
( ~ 1
.04)
0.05
0 (2
.28)
0.06
1 (3
.49)
0.04
6 (2
.41)
15.1
1
[0.0
04]
p, x
100
~ 0.
013
- 2.
87)
- 0.
007
~ 1.
94)
- 0.
010
- 3.
09)
~ 0.
005
- 1.
08)
16.1
2
[0.0
03]
- 0.
124
- 2.
64)
- 0.
102
- 2.
23)
- 0.
087
- 2.
00)
- 0.
155
( ~ 3
.29)
I I .4
6
co.0
221
Pan
el
A:
Unc
onst
rain
ed
Loc
atio
n of
quo
tes
vs.
valu
e T
est:
Tes
t: r,
= rz
=
a3
r, =
CQ
, +
r, F
RI
+ r
,HO
L
+ r
,AU
SIN
T
+ r
,AL
OC
INT
P
I =
p2=
0 =
ciq=
o
0.73
6 (1
.31)
0.31
5 (1
.05)
-0.1
51
( -0.
28)
0.12
2 (0
.45)
3.38
10.4
961
1.08
8 (2
.42)
0.68
0 (2
.16)
0.61
I
(1.4
6)
1.63
2 (3
.32)
12.0
1
[O.O
l7]
- 0.
763
( -
1.02
)
-0.1
50
( ~ 0
.40)
- 0.
104
(-0.
12)
~ 0.
524
( - 0
.62)
1.23
[0.8
73]
1.88
2 (5
.62)
1.47
8 (5
.06)
1.17
8 (5
.39)
2.11
8 (5
.11)
50.9
6
[O.O
OO
J
a4
zz
[p-v
alue
]
0.51
2 16
.07
(1.2
7)
[O.O
OO
]
-0.0
72
9.46
(-
0.12
) [0
.009
]
~ I.
120
13.7
7 (-
1.
95)
[O.o
ol]
0.21
3 13
.17
(0.1
3)
[O.O
Ol]
5.64
27
.68
[0.2
27]
[O.O
Ol]
x2 [
p-va
lue]
48.0
2
[O.o
w
39.7
4
wm
41
.04
ww
37
.58
mw
84
.53
[O.O
OQ
]
/Lo
x 10
0 /I
, x
100
Bri
tish
poun
d
Swis
s fr
anc
Japa
nese
ye
n
Ger
man
m
ark
- 0.
036
( - 2
.17)
0.02
9 (1
.34)
0.04
5 (2
.70)
0.01
7
- 0.
011
- 2.
60)
- 0.
006
- 1.
71)
- 0.
009
- 2.
73)
- 0.
004
(0.9
0)
( -
0.83
)
Cro
ss-e
quat
ion
13.1
8 13
.52
Tes
t: x2
[p-
valu
e]”
[O.O
lO]
[0.0
09]
Pan
el B
: rl
=
a2
= r
3 =
x4
= 0
im
pow
d
!-bX
l~
x2 [
p-va
lue]
- 0.
015
0.93
4 7.
13
~ 0.
46)
(1.5
0)
[0.0
28]
- 0.
007
0.65
8 3.
01
- 0.
19)
(2.7
1)
CO
.226
1
- 0.
019
0.06
3 7.
94
- 0.
63)
(0.1
4)
[0.0
19]
- 0.
016
0.26
2 1.
09
( -
0.46
) (0
.76)
[0
.604
]
0.64
9.
15
14.7
0
[0.9
58]
[0.0
57]
[0.0
65]
“Tes
t th
at
the
asso
ciat
ed
coef
fici
ent
is z
ero
in a
ll fo
ur
curr
enci
es
or
that
th
e hy
poth
esis
ho
lds
in a
ll fo
ur
curr
enci
es.
Tab
le
6
Tes
ts
for
vari
atio
n in
the
pla
cem
ent
of q
uote
s in
rel
atio
n to
und
erly
ing
curr
ency
va
lue,
an
d fo
r va
riat
ion
in t
he e
xpec
ted
chan
ge
in c
urre
ncy
valu
e,
whe
n qu
otes
ar
e st
ated
in
Eur
opea
n te
rms.
T
he
sam
ple
peri
od
is J
anua
ry
1979
to
Dec
embe
r 19
92.
The
pa
ram
eter
s es
timat
ed
incl
ude
x,,
whi
ch
defi
nes
the
loca
tion
of u
nder
lyin
g cu
rren
cy
valu
e (V
,) r
elat
ive
to
bid
(B,)
and
ask
(A,)
quo
tes
acco
rdin
g to
V, =
atA
r + (
I -
a,)B
, ,
and
p,,
whi
ch
is t
he
expe
cted
ch
ange
in
und
erly
ing
curr
ency
va
lue
over
th
e ne
xt
peri
od.
The
se
para
met
ers
are
cons
trai
ned
to
be l
inea
r fu
nctio
ns
of o
bser
vabl
e va
riab
les,
an
d ar
e es
timat
ed
by
appl
ying
ge
nera
lized
m
etho
ds
of m
omen
ts
to
the
syst
em:
B,+
,~B
,=~
,+G
I,+
,[-S
,+~
I +
G%
+~
,+I~
~
‘r=
~o+
~(1
1NT
DIF
,+1(
2~O
N,,
a, =
a0
+ r
,FR
I,
+ a
,HO
L,
+ o
l,AU
SIN
T,
+ c
(,ALO
CIN
T,,
whe
re
B, d
enot
es
curr
ency
bi
d pr
ice,
IN
TDIF
, is
exc
ess
of o
ne-m
onth
E
urod
olla
r ra
tes
over
lo
cal-
curr
ency
E
uro
rate
s,
MO
N,
and
FRI,
ar
e M
onda
y an
d Fr
iday
in
dica
tors
, re
spec
tivel
y,
HO
L,
is a
pre
-hol
iday
in
dica
tor,
AU
SIN
T,
is t
he
chan
ge
in
the
one-
mon
th
Eur
odol
lar
depo
sit
rate
, A
LOC
INT,
is
the
ch
ange
in
th
e on
e-m
onth
lo
cal
Eur
ocur
renc
y de
posi
t ra
te,
and
S, i
s th
e ex
cess
of
ask
ov
er
bid
pric
e at
t.
To
faci
litat
e co
mpa
riso
n of
coe
ffic
ient
es
timat
es,
each
cu
rren
cy
quot
e ha
s be
en d
ivid
ed
by i
ts o
wn
mea
n bi
d pr
ice.
Jo
int
hypo
thes
es
are
test
ed
usin
g a
Wal
d te
st
[New
ey
and
Wes
t (1
987b
)].
Tes
t st
atis
tics
are
asym
ptot
ical
ly
dist
ribu
ted
x2
with
de
gree
s of
fre
edom
eq
ual
to
the
num
ber
of c
onst
rain
ts.
T-s
tatis
tics
are
repo
rted
in
par
enth
eses
.
Pan
el A
: U
ncon
stra
ined
Exp
ecte
d ch
ange
in
cur
renc
y va
lue
p, =
fr
o +
pIIN
TDIF
, +
pJM
ON
,
Loc
atio
n of
quo
tes
vs.
valu
e T
est:
Tes
t: a,
= a
1 =
a3
zr =
a0
+ a
I FR
I +
azH
OL
+ a
,AU
SIN
T +
a,A
LOC
INT
Pl
= P
z =
0
=a,=
0
Bri
tish
poun
d
Swis
s Fr
anc
Japa
nese
ye
n
Ger
man
m
ark
Cro
ss-e
quat
ion
Tes
t: x2
[p-
valu
ela
0.02
5
(1.4
4)
- 0.
054
( -
2.91
)
- 0.
068
( -
4.16
)
- 0.
043
( -
2.69
)
24.4
6
ww
PI
x 10
0 P
zXl~
__
_ __
__~~
0.01
2 0.
084
(3.1
3)
(1.6
9)
0.00
7 0.
115
(2.4
6)
(2.5
2)
0.01
2 (3
.29)
0.00
6 (1
.69)
16.3
5
[0.0
03]
0.10
4 (2
.57)
0.13
2 (2
.81)
10.0
6
[0.0
39]
a0
a1
a2
a3
0.06
8 -
0.30
1 0.
835
~ 2.
186
(0.0
7)
( -
0.59
) (1
.18)
(
- 4.
93)
0.32
7 -
0.54
9 0.
509
- 1.
474
(1.1
1)
( -
1.41
) (1
.10)
(
- 4.
85)
1.10
6 ~
0.6
25
- 0.
064
- 1.
302
(2.5
6)
(-
1.70
) (-
0.
10)
( -
5.65
)
- 2.
571
( -
5.73
) 0.
858
(1.8
9)
9.49
[O.O
SO]
- 0.
834
( -
1.47
)
4.46
1.12
2 (1
.31)
2.79
10.3
471
10.5
951
49.4
1
[O.O
OQ
]
u‘l
- 0.
796
( -
1.74
)
0.55
3 (0
.80)
1.05
5 (1
.57)
- 0.
973
( -
0.46
)
5.68
10.2
251
[O.O
Ol]
x2 [
p-va
lue]
13.3
8 33
.65
[O.O
Ol]
C
O.O
QO
l
12.5
3 35
.91
[0.0
02]
ww
15
.51
39.1
9
Pow
P
.ow
10
.76
45.1
5 [O
.OO
S]
[O.O
OO
]
25.2
7 81
.24
v.w
x2 [
p-va
lue]
Pane
l B:
u,
=
a2
= x3
=
CL, =
0
impo
sed
!-bx
l~
PlX
l~
Pc,
Xl~
80
Bri
tish
poun
d 0.
031
0.01
1 0.
039
0.26
1 (1
.99)
(2
.91)
(1
.10)
(0
.32)
Swis
s fr
anc
- 0.
038
0.00
6 0.
046
0.28
5 (
- 2.
08)
(2.1
9)
(1.3
3)
(0.9
7)
Japa
nese
ye
n -
0.04
9 0.
011
0.02
7 0.
800
( -
3.22
) (2
.82)
(0
.85)
(0
.183
)
Ger
man
m
ark
- 0.
023
0.00
5 0.
049
0.82
3 (-
1.
61)
(1.3
1)
(1.4
0)
(1.6
6)
Cro
ss-e
quat
ion
16.5
8 13
.86
2.14
5.
10
Tes
t: ,$
[p
-val
ue]”
[0
.002
] [O
.OO
S]
[0.7
10]
[0.2
77]
_
aTes
t th
at
the
asso
ciat
ed
coef
fici
ent
is z
ero
in
all
four
cu
rren
cies
or
th
at
the
hypo
thes
is
hold
s in
al
l fo
ur
curr
enci
es.
x2 [
p-va
lue]
10.0
8 [0
.006
]
6.31
[0
.042
]
8.27
[0
.016
]
3.58
[O
. 167
1
16.0
4
CO
.042
1
346 H. Bessembinder, Bid-ask spreads in ,foreign exchange markets
Point estimates of ,u~ indicate that foreign currencies depreciate significantly against the dollar on weekends, which might explain the result above that the market-making bank seeks to hold dollars over weekends. Since each quote is divided by its own time-series mean, these coefficients estimate the average percentage depreciation over the weekend. Compared with mean spreads re- ported in table 2, the mean-estimated weekend depreciation varies from one to three times the mean spread. In contrast to this evidence of significant weekend depreciation, the estimates based on biddask midpoints reported in table 2 indi- cate only marginally significant price changes on Mondays.
To determine whether changes in the placement of quotes in relation to value can explain this shift in inference, I again estimate eq. (5), but constrain c(, to be constant. Results are reported in panel B of tables 5 and 6. Given this constraint, point estimates on p2 are substantially reduced in absolute magnitude, and the hypothesis that expected changes in currency value do not differ between Mondays and other days cannot be rejected using either American or European quotes.
This evidence supports the conclusion that there is a ‘Monday effect’ in currency values, but that shifts in the placement of quotes in relation to value around weekends make it difficult to detect. More generally, these findings illustrate that inference regarding changes in asset value can be altered by allowing for variation in quote placement.
6. Conclusions
The microstructure of the foreign exchange market differs in several ways from that of the often-examined equity markets, providing an interesting alter- nate arena for developing and testing microstructure hypotheses. This study documents that, despite the absence of a predetermined minimum tick, currency bid-ask spreads cluster nonrandomly on a few values when quotes are stated in conventional terms. Quotes stated in nonconventional terms cluster less, and inference is largely unaffected by the quoting convention for the hypotheses evaluated here.
This study also provides evidence that currency spreads vary with proxies for inventory carrying costs, including risk forecasts and a measure of liquidity costs. This evidence can be contrasted with that of some recent studies conduc- ted in equity markets [e.g., Hasbrouck (1991), George, Kaul, and Nimalendran (1991) and Madhavan and Smidt (1991)] where inventory costs appear to have little if any effect on market-maker quotes. The previously documented regular- ity of wider currency bid-ask spreads on Fridays is shown here to be explained by increased inventory carrying costs on Fridays, in the form of both increased risk and increased sensitivity of spreads to risk and interest rates.
This study provides some new evidence on interactions between trading volume and spreads. When time series of volume are decomposed into forecastable
H. Bessembinder. B&ask spreads in foreign exchange markets 347
and unexpected components, the effects of the two volume components on spreads are found to differ significantly. Point estimates indicate that spreads decline with the expected component of volume but increase with volume surprises.
I introduce a simple procedure for documenting variation in the placement of quotes in relation to underlying value. The evidence indicates that, consistent with efforts to reduce foreign currency positions in favor of dollar positions, currency market makers reduce quotes in relation to underlying dollar value when dollar-denominated interest rates rise, and, to a lesser extent, on Fridays. This finding of a weekend effect complements results reported by Keim (1989) and Porter (1992). They find that closing transactions in individual equities tend to occur at prices above the midpoint of bid and ask quotes more often on Fridays than on other days, suggesting shifts in market-maker inventories before weekends.
The procedure introduced here to estimate the placement of quotes in relation to asset value can be implemented in any database composed of time-series bid and ask quotes. Allowing for time-series variation in this placement parameter may be useful for testing theories regarding market-maker quotation strategies. In addition, the evidence obtained here illustrates that inference regarding asset value can be altered by allowing for variation in the placement of quotes in relation to value. This implication is potentially important for assessing the valuation consequences of any events that are accompanied by changes in market-maker inventories.
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