The **in**e ciency of Reuters foreign exchange

quotes

Mart**in** Martens a,* , Paul Kofman b

a Department of Account**in**g and F**in**ance, Lancaster University, Lancaster, LA1 4YX, UK

b School of Bank**in**g and F**in**ance, The University of New South Wales, Sydney, NSW 2052, Australia

Abstract

Received 18 April 1997; accepted 27 December 1997

Reuters foreign exchange (FXFX) page is the world wide predom**in**ant **in**formation

source to foreign exchange traders. In this study we compare the **in**dicative spot exchange

rate quotes from Reuters with their match**in**g futures exchange rates from the

Chicago Mercantile Exchange. We ®nd that the **in**dicative quotes on Reuters FXFX

page are **in**e cient and could be improved by **in**corporat**in**g **in**formation from the futures

market. This casts doubt on the way banks determ**in**e these quotes, as well as

on the **in**formational content of these quotes as an **in**dicator of the current exchange

rate. Ó 1998 Elsevier Science B.V.

JEL classi®cation: G14; G15

Keywords: Exchange rates; Futures; E ciency

1. Introduction

Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

The spot foreign exchange market is a 24 hours electronic market with brokers

and traders around the world. Brokers display quotes to their customers.

*

Correspond**in**g author. Tel.: +44 1524 593623; fax: +44 1524 847321; e-mail: m.martens@lancaster.ac.uk.

0378-4266/98/$19.00 Ó 1998 Elsevier Science B.V. All rights reserved.

PII S 0 3 7 8 - 4 2 6 6 ( 9 8 ) 0 0 0 0 4 - 1

348 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

These quotes are the best bid and ask price provided by a limited number of

banks regularly contacted by the broker. S**in**ce there are many brokers each

contact**in**g their own circle of banks to obta**in** quotes and hav**in**g their own customers,

the natural question arises whether this market is **in**formationally e -

cient.

To date, no data sets have been available allow**in**g for a direct test of the ef-

®ciency of the spot market **in** foreign exchange. Goodhart et al. (1996, 1997)

study 7 hours of the Reuters-2000 electronic trad**in**g system, which at the time

of sampl**in**g was still a relatively small broker **in** the spot market. Lyons (1995)

studies one week of all transactions of a New York broker.

Obviously, any data set on quotes from brokers will only re¯ect a part of the

spot market. In fact, the only **in**formation source available to all traders around

the world consists of **in**dicative quotes, as provided by Reuters foreign exchange

(FXFX) page, and those provided by its competitors Knight Ridder and Telerate.

As such these quotes play an important role **in** the spot market, **in**dicat**in**g

the current foreign exchange rate. Though the quotes are only `**in**dicative', studies

us**in**g the quotes claim banks have reputation considerations and will most

likely trade aga**in**st their quotes if called with**in** a short time after appearance

on the Reuters FXFX page. This assumption is crucial for studies like De Jong

et al. (1995) who study triangular arbitrage, Bollerslev and Domowitz (1993),

and Dacorogna et al. (1993) who study the trad**in**g **in**tensity and volatility patterns

**in** the spot market, and Bollerslev and Melv**in** (1994) who study the relationship

between the spreads and volatility. Similarly, Olsen and Associates

who use these quotes to forecast the foreign exchange rate, started a boom **in** empirical

research by releas**in**g 1 year of Reuters quotes **in** 1994.

In this study we further **in**vestigate the assumption that one can actually

trade aga**in**st the Reuters quotes. We compare these spot exchange rate quotes

with their match**in**g futures exchange rates traded at the Chicago Mercantile

Exchange (CME). The futures market is a highly liquid market, but **in** value

terms relatively small as compared to the spot market. Nevertheless, we ®nd

that the futures market is lead**in**g the `quoted' spot market for up to 3 m**in**utes.

The results of a simple trad**in**g strategy show that pro®ts can be made from the

futures lead, unless trad**in**g aga**in**st the Reuters quotes is not (always) possible.

This could (partly) expla**in** our results, which we therefore **in**terpret conditional

on the possibility of trad**in**g aga**in**st the Reuters quotes:

(i) If one can trade aga**in**st the Reuters quotes, then our results show that

ga**in**s can be made and hence the spot market is **in**e cient.

(ii) If one cannot (always) trade aga**in**st the Reuters quotes, our results can

be (partly) expla**in**ed by that fact. However, this implies that studies which

made the assumption that one can trade aga**in**st Reuters quotes were **in**correct

to do so. Their results will then have to be taken with care.

In both cases banks display**in**g quotes on Reuters FXFX page can improve

upon these quotes by pay**in**g more attention to the futures market. The futures

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 349

price provides a more adequate re¯ection of the (true) current spot exchange

rate than the Reuters quotes.

The rema**in****in**g part of this study is organised as follows. Section 2 discusses

**in** further detail the function**in**g of the spot and futures markets. In Section 3

the data set is discussed. Section 4 describes the methodology, and Section 5

elaborates upon the results. Section 6 focuses on the e€ect of prescheduled

news announcements and high volatility periods. In Section 7 the pro®tability

of a simple trad**in**g strategy is tested. F**in**ally, Section 8 will conclude.

2. Microstructure of foreign exchange markets

The major di€erence between the futures and the spot market **in** foreign exchange

is the trad**in**g system. While the futures contracts at the CME are traded

**in** an open outcry (OOC) market, the spot market is an electronic market

with brokers and traders around the world. In addition to brokers sett**in**g

quotes, market participants can also o€er or obta**in** quotes via Reuters, Telerate

or Knight Ridder.

We will use Reuters FXFX data for the spot rates. These data consist of,

ma**in**ly **in**dicative, bid and ask quotes. Transaction prices are not available.

Each trader can immediately submit quotes to Reuters FXFX page. In addition

to Reuters FXFX page, traders have a screen display**in**g a very small

spread often of a magnitude of only 1 tick (i.e., one hundredth of percentage

po**in**t). This spread re¯ects the current best bid and ask provided by a broker.

This broker just compares the available bids and asks of a number of banks

(usually four or ®ve) by call**in**g them at regular time **in**tervals. In a normal market

situation the spreads on Reuters screen will **in**clude the best bid and ask

price. 1 Often banks are will**in**g to trade only on one side of the bid±ask spread

and they try to do so by sett**in**g a bid±ask hitt**in**g the currently best bid or ask

and mov**in**g the other side away. 2

Results **in** Goodhart et al. (1996) suggest that the nature of the `**in**dicative'

spreads on Reuters FXFX page is di€erent from the `®rm' spreads provided by

brokers (derived from Reuters electronic brok**in**g system, D2000-2). However,

1 Most banks put quotes on the Reuters screen themselves. In addition, there are several brokers,

each with their own limited circle of banks from which they obta**in** their quotes. As a result Reuters

conta**in**s more updated **in**formation than the broker uses. The m**in**imum spread, however, is 5 ticks

on Reuters screen, while it can reduce to 1 tick for a broker us**in**g the best bid and ask.

2 For example, if for the DM/$ spot rate the current spread set by the broker is 1.6022±1.6023, a

bank will**in**g to sell US dollars could either do so by hitt**in**g the current best bid of 1.6022 or by

sett**in**g a quote of, e.g., 1.6018±1.6023. In the latter case the quote on Reuters screen (1.6018±

1.6023) will be skewed to the left. Similarly a bank will**in**g to buy US Dollars could set a quote of

1.6022±1.6032, skew**in**g the spread to the right.

350 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

an unresolved issue is the **in**formational role of the `**in**dicative' quotes as a re-

¯ection of the entire spot market which is available to all traders. Our results

show that not only the nature of these **in**dicative spreads is di€erent, but also

that the quoted prices are **in**e cient. This does not necessarily imply pro®table

trad**in**g opportunities. In a high-volatility situation, for example around news

announcements, Reuters FXFX page might lag the current developments.

Traders ®rst trade and only then update Reuters screen by sett**in**g new quotes.

In that case the best bid and ask of the broker might be outside the spreads

given on Reuters FXFX page. It will then also be impossible to trade aga**in**st

the bids and asks given on Reuters screen, simply because they are outdated

and therefore no longer valid. In all other circumstances studies us**in**g Reuters

FXFX quotes claim that reputation considerations will ensure that banks will

trade at their quotes if requested with**in** reasonable time after the appearance

on Reuters.

In this study we compare the Reuters quotes for the DeutscheMark/US Dollar

(DM/$) exchange rate with the DM/$ futures contract traded on the CME. Dur**in**g

our sample period most trad**in**g was still conducted by telephone and with

many di€erent brokers hav**in**g a reasonable market share. Reuters FXFX page

was therefore still the ma**in** source of publicly available **in**formation, while the **in**dividual

broker's quotes were only known to the limited circle of his or her clients.

3. Data

The data set consists of **in**traday Reuters quotations of the DM/$ exchange

rate from the Olsen and Associates data set, and of futures prices of the DM/$

exchange rate for the September 1993 contract from the CME. The sample period

covers June, July and August 1993. We choose to analyse the DM/$ exchange

rate s**in**ce it is the most liquid exchange rate **in** terms of number of

contracts (futures market) and number of bid±ask quotes (spot market).

The futures data conta**in** the transaction price, the date and the time truncated

to the m**in**ute (e.g. 8:37 0 45 00 will be shown as 8:37). The Reuters quotations

conta**in** the date, a time stamp to the nearest second, the bid and ask price,

the code for the bank, and the code for the country. The data set is an almost

complete record of spot DM/$ quotations shown on Reuters FXFX page. Suspect

quotations were ®ltered out us**in**g the methods of Dacorogna et al. (1993).

Whereas Reuters FXFX data cover the entire day (24 hours), the futures data

only cover the 7:20 a.m.±14:00 p.m. Chicago Standard Time (CST) period.

In total we use 65 common trad**in**g **in**tervals (i.e. days), dur**in**g the trad**in**g

hours of the CME. In this period we have about 3.2 quotations per m**in**ute

for the futures market, and about 4.0 observations per m**in**ute for the spot market.

The distribution of the number of observations over the trad**in**g hours of

the CME is given **in** Fig. 1. The decrease **in** the number of spot quotes that

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 351

Fig. 1. Total number of Reuters spot quotes and futures transaction prices for the DM/$ exchange

rate for each m**in**ute dur**in**g the trad**in**g hours of the Chicago Mercantile Exchange, 1 June±31

August 1993.

starts around 10:00 a.m. (CST) can be ascribed to the withdrawal of the European

traders from the market. To allow for a fair comparison between the futures

and the spot market, we con®ne the ma**in** part of our analysis to the 7:20±

10:00 a.m. CST w**in**dow.

We construct 1-m**in** prices and returns to compare the futures exchange

rates with the quotes on Reuters FXFX page. For the futures transaction prices

the last available price **in** each m**in**ute is used, 3 and whenever there was no

trade **in** a certa**in** m**in**ute, the price **in** the previous m**in**ute is used. For the spot

market the bid±asks are often skewed to one side, and this may alternate between

the bid- and ask-side. This `skew**in**g' results **in** negative autocorrelation

(Goodhart and Figliuoli, 1991; Bollerslev and Domowitz, 1993) when us**in**g the

bid±ask midpo**in**ts to generate spot returns. We propose, therefore, to extract

spot prices from the Reuters data **in** two di€erent ways. First, we will use the

last available quote **in** each m**in**ute. From this bid±ask quote the midpo**in**t is

used as the price (from now on we call this panel A):

3 As noted before, the time stamp for the futures prices is truncated to the m**in**ute. As a result,

e.g. the last observation with time label 0731 will be used to re¯ect the price at 0731 0 59 00 .

352 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Table 1

Autocorrelation **in** the DM/$ spot and futures exchange rate returns

Spot Futures

Panel A Panel B

c )0.000347 )0.000292 )0.000246

Rt 1 )0.187 a )0.0516 a )0.0540 a

Rt 2 0.00244 0.0448 a 0.0442 a

Rt 3 0.0324 a 0.0339 a 0.0220 b

Rt 4 0.0359 a 0.0249 b 0.0275 a

Rt 5 0.0250 b 0.0215 b 0.0409 a

Rt 6 )0.0259 a

Rt 7 )0.0243 b

The results are obta**in**ed from an AR(p) process for the DM/$ spot and futures exchange rate

returns. The sample period is June±August 1993, with for every day 1-m**in** observations from 7:20±

10:00 a.m. CST. This results **in** 10,335 returns. Panel A uses the midpo**in**t of the last spot quote each

m**in**ute, Panel B uses also the previous two spot quotes (if with**in** 15 seconds) to ®rst determ**in**e the

best bid and ask and then calculate the midpo**in**t.

a Denotes signi®cance at 1% level.

b Denotes signi®cance at 5% level.

st ˆ …st;bid ‡ st;ask†=2 …ln st;bid ‡ ln st;ask†=2; …1†

where the log spot rate st is expressed **in** US dollars per DeutscheMark, like the

futures price. Second, we will also use the two preceed**in**g quotes, if with**in**

15 seconds of the last available quote of the m**in**ute, and calculate the best

bid and ask (from now on we call this panel B). Thus, we try to imitate what

happens **in** practice, i.e., the broker search**in**g for the currently best available

bid and ask. 4 This latter approach will (partly) correct for the spread be**in**g

usually skewed to one side. This can be observed **in** Table 1. The AR(1) coef-

®cient is )0.0516 for Panel B as opposed to )0.187 for Panel A. The negative

®rst order autocorrelation **in** the futures transaction prices can be attributed to

the bid±ask bounce (Roll, 1984).

4. Methodology

Hav**in**g discussed the univariate data series, we can now proceed with their

jo**in**t analysis based on the covered **in**terest rate parity (CIRP). For the necessary

US and German **in**terest rates we obta**in**ed daily Eurocurrency rates from

Datastream. We refra**in** from us**in**g **in**traday **in**terest rates. First, they are not

readily available. Second, foreign exchange transactions are not settled with**in**

4 Obviously we cannot imitate exactly the broker(s), s**in**ce the Reuters screen conta**in**s actually

more spreads than the ones used by a broker. Furthermore, we cannot observe from our data

whether a quote is still valid.

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 353

the trad**in**g day but at the end of the trad**in**g day when the ®nal position **in** foreign

currency is deposited at a bank o€er**in**g the best rate. 5 Thus, the daily

rates turn out to be the realised rates which had to be estimated by the traders

dur**in**g the day. For both the Eurodollar and the Euromark we have the midquotes

(the bid- and ask-quotes are symmetric around the mid-quotes) for the

1-week, 1-month, 3-months and 6-months **in**terest rate. From these data we

construct midpo**in**t series for the time-to-maturity of the futures contract us**in**g

a standard polynomial (of order 6) **in**terpolation. 6 The result**in**g series are rt;mid

for the Eurodollar rate, and r f

t;mid for the Euromark rate.

To evaluate the CIRP, Brenner and Kroner (1995) relate the cost-of-carry

asset pric**in**g model to the existence of co**in**tegration between the spot and forward

(futures) prices. They illustrate that co**in**tegration depends on the time-series

properties of the cost-of-carry. S**in**ce the **in**terest rate di€erential is likely to

be stationary, the forward price and spot price **in** the FX markets should be

co**in**tegrated with vector (1 )1). Under certa**in** assumptions given **in** Brenner

and Kroner, a mark**in**g-to-market adjustment term, re¯ect**in**g the di€erence between

futures and forward contracts, while be**in**g non-stochastic will have no

e€ect on the co**in**tegration relation. 7 For an extensive summary of the literature

on co**in**tegrat**in**g vectors for foreign exchange markets we refer to Table 2

**in** Brenner and Kroner.

In our approach we de®ne the theoretical (log) futures price by

ft ln Ft ˆ …rd;mid r f

d;mid †…T d† ‡ st ; …2†

where T is the maturity date of the futures contract, and t is the current time on

day d. Hence for all prices with**in** day d we make the same **in**terest rate adjustment

because the actual transactions **in** the spot market take place at the end of the

trad**in**g day. This expression is based upon the CIRP, and it should therefore **in**clude

an error term equal to the di€erence between the forward and futures rate

(see footnote 7). When us**in**g returns from m**in**ute to m**in**ute, this error term can

be neglected. Furthermore, omitt**in**g overnight returns, a return **in** the theoretical

futures price as de®ned by Eq. (2) will be equal to the spot return.

The mispric**in**g error is then de®ned as

5

Banks keep a record of all transactions dur**in**g the day of their currency traders. Only at the end

of the day all transactions are actually settled. The ®nal position **in** each currency has then to be

deposited at the best available rates.

6

See for example Chambers et al. (1984), p. 236. It is assumed that the term structure of **in**terest

rates may be expressed as a simple polynomial of time.

7

More speci®cally, Brenner and Kroner derive for the (log) futures price

ft ˆ …rt r f

t †…T t† ‡ st ‡ Qt;T ;

where Qt;T is a non-stochastic mark**in**g-to-market adjustment term. This term will depend on the

**in**terest rate expectations of traders, which we cannot measure.

354 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Zt ˆ ft ft ; …3†

where ft is the market observed futures price. If this mispric**in**g variable is stationary

(while the observed and theoretical futures prices are non-stationary),

the prices will be co**in**tegrated with a vector close to (1 )1). To facilitate the

**in**terpretation we will use this exact vector (1 )1). In Section 5 we formally test

for co**in**tegration.

Engle and Granger (1987) show that if prices are co**in**tegrated, the returns

follow an error correction model. In this model the current price changes depend

on how far the system was out of long-run equilibrium **in** the previous

period. The traditional solution of ®rst di€erenc**in**g the data imposes too many

unit roots **in** the system, bias**in**g parameter estimates and **in**ference. Instead, we

will estimate the follow**in**g Vector Error Correction Model (VECM):

DXt ˆ l ‡ XK

kˆ1

CkDXt k ‡ ab 0 Xt 1 ‡ et …4†

with Xt ˆ (ft f t ) 0 , b is restricted to (1 )1) 0 (thus b 0 > Xt 1 equals zt 1), l and a

are (2 ´ 1) vectors of parameters, Ck are (2 ´ 2) matrices of parameters, et is

a (2 ´ 1) error vector with mean zero and variance±covariance matrix X, and

K is the lag-length which will be determ**in**ed us**in**g the Schwarz (1978) criterion.

Estimation of the model **in** Eq. (4) allows us to calculate impulse-response

functions, and to determ**in**e the **in**formation share of both the spot and futures

market by us**in**g the measure de®ned **in** Hasbrouck (1995), p. 1183. The VECM

has a common trends representation (e.g. Johansen, 1991)

Xt ˆ X0 ‡ C Xt

iˆ1

ei ‡ C…L†et ; …5†

where X0 is a constant (2 ´ 1) vector, and C(L) a matrix polynomial **in** the lag

operator. C is the impact matrix which represents the long-run impact of a disturbance

on each of the two prices. The impact matrix is related to Eq. (4) by

the expression

C ˆ b ?…a 0

? Wb ?† 1 a 0

? ; …6†

where a? (b?) is a vector orthogonal to the vector a (b), and W is given by

W ˆ I XK

kˆ1

Ck ‡ Kab 0 ; …7†

where I is the (2 ´ 2) identity matrix. By construction, C will have two identical

rows, say c. If the price **in**novations between the spot and the futures market

are correlated, X will not be diagonal. Let F be the Cholesky factorisation of

X (F the lower triangular matrix such that X ˆ FF 0 ), then the market share

of the **in**novation variance attributable to market j (j ˆ 1,2 for the futures

and spot market, respectively) is equal to

Sj ˆ …‰cF Šj †2

cXc0 : …8†

The outcome depends on the stack**in**g order of the prices **in** the vector Xt. The

**in**formation share is maximised on the ®rst price **in** the vector. Therefore the

**in**formation share will alternatively be calculated by putt**in**g the spot price (theoretical

futures price) ®rst **in** the vector Xt. Then Eq. (8) will provide both a

lower and upper bound for the **in**formation share of each market.

One disadvantage of the VECM model is the multicoll**in**earity problem between

the explanatory variables, the lagged futures and spot returns, obscur**in**g

the length of the lead±lag relation, despite penalis**in**g the speci®cation of too

many lags accord**in**g to the Schwarz criterion. This multicoll**in**earity e€ect is

quite strong here due to negative autocorrelation **in** both return series and

the positive impact of one market on the other market. This results **in** opposite

signs of the parameters of the futures returns on the one hand and the parameters

of the spot returns on the other hand. For this reason we will also calculate

cross-correlations between the observed and theoretical futures returns.

F**in**ally, to address the impact of high volatility on the **in**tertemporal relations

set out above, we split our data set **in**to two parts: high and low volatility.

S**in**ce the futures market will turn out to be the most frequently updated market,

we will employ the follow**in**g ad hoc rule us**in**g the absolute futures returns

as a proxy for the volatility:

1 X

N

n‡N

jDf1j > 1 X

T

T

1 X

jDftj ‡ P

t 1

T

1 X

…jDftj

T

T

jDftj† 2

v

u

t : …9†

tˆn‡1

tˆ1

Thus, we attribute each N-m**in**ute **in**terval to the high volatility panel if the

mean volatility dur**in**g these N m**in**utes is above the mean volatility of the total

sample plus P percent of the standard deviation of the volatility of the total

sample. For the majority of cross-correlations both the spot and the futures return

will lie with**in** the same N-m**in**ute **in**terval. Volatility cluster**in**g is then taken

**in**to account as well by assign**in**g **in**tervals to the high or low volatility

panel **in**stead of s**in**gle m**in**utes.

5. Results

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 355

In this section we will ®rst test for co**in**tegration between the market observed

futures prices and theoretical (spot-**in**duced) futures prices based on

the CIRP. Next, we will estimate the VECM speci®ed **in** Eq. (4). From this

we will calculate impulse±response functions and the **in**formation share of both

the futures and spot market. In Section 5.2 we **in**vestigate simple cross-correlations

between the spot and futures returns to determ**in**e the lead±lag structure

between the two markets.

tˆ1

iˆ1

356 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Table 2

Augmented Dickey Fuller tests and co**in**tegration

Panel A Panel B Critical

Futures

price

Theoretical

futures price

5.1. Co**in**tegration and error correction

Futures

price

Theoretical

futures price

value

Levels )2.39 )2.37 )2.39 )2.36 )2.86

Di€erences )37.9 )38.2 )37.9 )37.6 )2.86

Co**in**tegration a )22.7 )22.7 )22.7 )22.7 )3.30

Vector 0.997 1.00 0.997 1.00

Mispric**in**g error b )22.1 )22.0 )2.86

Stationarity and co**in**tegration tests for the DM/$ spot and futures prices. The sample period is

June±August 1993, with for every day 1-m**in** observations from 7:20±10:00 a.m. CST. Panel A uses

the midpo**in**t of the last spot quote each m**in**ute, Panel B uses also the previous two spot quotes (if

with**in** 15 seconds) to ®rst determ**in**e the best bid and ask and then calculate the midpo**in**t. Theoretical

futures prices are calculated us**in**g Eq. (2). For the stationarity tests the follow**in**g equation

is estimated us**in**g OLS:

Pt Pt 1 ˆ h0 ‡ h1 Pt 1 ‡ XL

/ i …Pt i Pt i 1† ‡ et: …i†

iˆ1

For both the levels and the ®rst di€erences, the t-values of h1 are reported. Critical values are

provided **in** the last column. The null hypothesis of non-stationarity is rejected if the t-value of h1

exceeds the critical value.

a

P1t ˆ c ‡ pP2t ‡ zt is estimated, ®rst with the futures price as the dependent variable (column `futures

price'), second with the theoretical futures price as the dependent variable (column `theoretical

futures price'). For the result**in**g error term, Eq. (i) is estimated. The t-value of h1 is reported here.

b For the mispric**in**g error (di€erence between futures and theoretical futures price) Eq. (i) is esti-

mated. The t-value of h1 is reported here.

Table 2 provides the results of the test for co**in**tegration. For both panel A

and panel B the (theoretical) futures prices are non-stationary (row 1, labelled

`levels'), while the returns are stationary (row 2, labelled `di€erences'). Hence

both the theoretical futures price and the market observed futures price have

one unit root, which is the ®rst condition for co**in**tegration.

The estimated co**in**tegration vector (row 4) is close to the expected vector

(1)1), and the result**in**g residual is stationary as can be seen from row 3.

F**in**ally, the mispric**in**g error as de®ned **in** Eq. (2) is stationary. To facilitate **in**terpretation

we will use this mispric**in**g error.

The results of the VECM model for both panel A and B are provided **in**

Table 3. The mispric**in**g error of the previous period, zt 1, only has a signi®cant

impact on spot price changes. Given the estimated coe cients (e.g. **in** Panel A it

is 0.215 for the spot equation and )0.0287 for the futures equation), the e€ect of

the previous mispric**in**g error is clearly stronger on the current spot price change.

S**in**ce the results for Panel A and B are similar, we only report the impulse

response functions result**in**g from the estimated VECM for Panel B. The im-

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 357

Table 3

Vector error correction model for DM/$ spot and futures exchange rate returns

Panel A Panel B

Dst Dft Dst Dft

Dft 1 0.456 a )0.0636 a 0.403 a )0.0669 a

Dft 2 0.501 a 0.0498 a 0.507 a 0.0437 a

Dft 3 0.420 a 0.0119 0.401 a )0.000281

Dft 4 0.343 a 0.0151 0.322 a 0.00653

Dft 5 0.292 a 0.0342 0.283 a 0.0294

Dft 6 0.229 a )0.0334 0.224 a )0.0312

Dft 7 0.185 a )0.0356 b 0.189 a )0.0272

Dft 8 0.154 a )0.0151 0.151 a )0.00460

Dft 9 0.136 a 0.00320 0.134 a 0.00990

Dft 10 0.0955 a )0.0229 0.0932 a )0.0130

Dft 11 0.0451 a )0.0398 a 0.0454 a )0.0344 a

Dst 1 )0.708 a 0.0574 a )0.611 a 0.0812 a

Dst 2 )0.404 a 0.0242 )0.374 a 0.0280

Dst 3 )0.345 a 0.00359 )0.321 a 0.0180

Dst 4 )0.285 a 0.00576 )0.274 a 0.00830

Dst 5 )0.228 a 0.0100 )0.222 a 0.00172

Dst 6 )0.193 a 0.00976 )0.181 a 0.00215

Dst 7 )0.168 a 0.00903 )0.175 a )0.00897

Dst 8 )0.116 a 0.00842 )0.115 a )0.00366

Dst 9 )0.0894 a 0.00619 )0.0820 a )0.00936

Dst 10 )0.0435 a )0.00864 )0.0354 a )0.00268

Dst 11 )0.0146 )0.00263 )0.00273 )0.00588

zt 1 0.215 a )0.0287 0.170 a )0.0293

l )0.00308 a )0.000026 )0.00243 a )0.000022

Adj R2 0.449 0.0137 0.467 0.0143

VECM for the DM/$ spot and futures returns, given **in** Eq. (4). The sample period is June±August

1993, with for every day 1-m**in** observations from 7:20±10:00 a.m. CST. Panel A uses the midpo**in**t

of the last spot quote each m**in**ute, Panel B uses also the previous two spot quotes (if with**in**

15 seconds) to ®rst determ**in**e the best bid and ask and then calculate the midpo**in**t. Standard errors

are usually around 0.01, while White errors are similar to the standard errors.

a Denotes signi®cance at 1% level.

b Denotes signi®cance at 5% level.

pulse response functions illustrate what happens to the system if there is a one

standard deviation shock **in** either the spot or the futures market. The relevant

impulse±response functions are given **in** Fig. 2. A shock **in** the futures market

has clearly a much larger e€ect on the subsequent returns **in** the spot market

than vice versa, i.e. the e€ect of a shock **in** the spot market on the futures returns.

The upper and lower bounds of the **in**formation share of each market are

calculated accord**in**g to expression (8). For Panel A this implies an **in**formation

share of 89.8±98.7% (Panel B: 88.1±98.6%) for the futures market, and 1.27±

10.2% for the spot market. Once aga**in**, the futures market is lead**in**g the quotes

358 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Fig. 2. Impulse response functions derived from the VECM results **in** Table 3. The graph shows the

response of the futures returns to a shock **in** the spot returns (labelled `futures returns') and the response

of the spot returns to a shock **in** the futures returns (labelled `spot returns').

Table 4

Cross-correlations between the DM/$ spot and futures exchange rate returns

Full sample June July August

corr(Dfe t 4 ,Dse t ) 0.00364 [0.016] 0.0228 [0.033] 0.00425 [0.021] )0.0271 [0.022]

corr(Dfe t 3 ,Dse t ) 0.0764 a [0.016] 0.0631 b [0.031] 0.0905 a [0.025] 0.0809 a [0.022]

corr(Dfe t 2 ,Dse t ) 0.396 a [0.022] 0.398 a [0.028] 0.598 a [0.049] 0.159 a [0.025]

corr(Dfe t 1 ,Dse t ) 0.311 a [0.032] 0.515 a [0.036] 0.0800 [0.046] 0.263 a [0.027]

corr(Dfe t ,Dse t ) 0.159 a [0.019] 0.101 a [0.036] )0.0144 [0.017] 0.451 a [0.026]

corr(Dfe t ,Dse t 1 ) 0.0424 a [0.016] 0.0709 b [0.028] 0.00293 [0.021] 0.0438 [0.025]

corr(Dfe t ,Dse t 2 ) 0.00833 [0.014] 0.0213 [0.026] )0.00969 [0.019] 0.00894 [0.021]

Dse t and Dfe t are the prewhitened DM/$ spot and futures returns, respectively, us**in**g an AR(p) ®lter.

The sample period is June±August 1993, with for every day 1-m**in** observations from 7:20±

10:00 a.m. CST. For the spot returns we employed Panel B. Panel B uses, **in** addition to the last

quote **in** each m**in**ute, also the previous two quotes (if with**in** 15 seconds) to ®rst determ**in**e the best

bid and ask and then calculate the midpo**in**t. Heteroscedasticity and autocorrelation consistent

(HAC) errors **in**side brackets.

a Denotes signi®cance at 1% level.

b Denotes signi®cance at 5% level.

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 359

on Reuters FXFX page and new **in**formation is **in**corporated much faster **in**to

the futures prices than **in**to the spot quotes.

5.2. Cross-correlations

Before calculat**in**g the cross-correlations, we ®rst prewhiten the time series

us**in**g an AR(p) process follow**in**g Pierce and Haugh (1977). 8 The results for

Panel B are given **in** the ®rst column of Table 4 (the results for Panel A are similar;

apparently, the direction of the skew**in**g of the spot spreads is close to random

and, therefore, does not a€ect the results, and the ®lter**in**g procedures

remove the di€erent autocorrelation patterns).

These results show that the futures market leads the spot quotes on Reuters

FXFX page signi®cantly up to 3 m**in**, while there is only a small signi®cant 1m**in**

lead the other way around. One possible explanation is that updat**in**g

Reuters screen takes some time, another explanation is that one cannot actually

trade aga**in**st these quotes and as a result **in**su cient e€ort is taken to make

them e cient. Previous studies us**in**g Reuters quotes, however, claim that

banks have reputation considerations, and for our sample period Reuters

was the ma**in** **in**formation source available to all traders.

The results for the subsamples June, July and August **in** columns 2±4 **in**

Table 4 show that the general conclusions hold. The futures market is more ef-

®cient than the Reuters spot quotes.

6. The e€ect of high volatility periods

In this section we split the sample **in**to two parts: one where volatility is relatively

high and one where volatility is at its normal level. In cases of high volatility

or prescheduled news announcements, traders prefer ®rst to trade and

only then update their Reuters quotes. However, traders will then also need

to closely follow the current developments **in** the market.

6.1. Prescheduled news announcements

Eder**in**gton and Lee (1993, 1995) **in**vestigate the volatility pattern surround**in**g

news announcements for several futures markets. One of them is the DM/$

futures contract traded at the CME. In the period 7:30±7:31 a.m. CST there is a

peak **in** the futures volatility, co**in**cid**in**g exactly with US macro-economic an-

8 For example for the ®rst column **in** Table 4 we use the estimated AR(p) processes from Table 1.

We also experimented with time-vary**in**g AR(p) ®lters. This gives similar results as the ones

provided here.

360 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Fig. 3. Average volatility spot (based on Reuters quotes) and futures exchange rates for the ®rst

40 m**in** of trad**in**g **in** Chicago, 1 June±31 August 1993.

nouncements like GNP and employment rates. Us**in**g the absolute values of the

futures and spot returns, the average taken over all trad**in**g days for each trad**in**g

m**in**ute results **in** Fig. 3 (only the ®rst 40 m**in** of CME trad**in**g are **in**cluded).

As expected, we observe **in** the period 7:30±7:31 a peak **in** the futures returns

volatility. The peak **in** the spot returns volatility based on Reuters quotes occurs 1

m**in** later. So, on average (the volatility **in**) the spot returns are lagg**in**g by 1 m**in** **in**

the case of prescheduled news announcements. The fact that there is only a 1 m**in**

lag is somewhat surpris**in**g given the 3 m**in** lead we found earlier. It seems that the

Reuters FXFX page is actually updated quite fast consider**in**g the fact that traders

®rst trade and only then update their quotes. Some traders may even temporarily

withdraw from the market to wait until the volatile period has passed.

To study the e€ect of prescheduled news announcements **in** greater detail,

we analysed two occasions where the news announcement resulted **in** a major

shock **in** the DM/$ exchange rate. On Friday, 4 June 1993, the announcement

**in**cluded an **in**crease **in** US jobs for the month May with 209,000 (while the expectation

was 155,000), and the unemployment rate had decreased slightly

(while predicted to be stable). Accord**in**g to the news reports this apparently

resulted **in** a fear for **in**creased US **in**¯ation and an **in**crease **in** the US **in**terest

rate, strengthened by the strong economic quarter compared to the ®rst quarter

of 1993. In just a couple of m**in**utes after the announcement the US dollar ap-

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 361

preciated by 1 cent versus the Deutsche Mark. Our second news event took

place on Friday, 2 July 1993, when the US dollar depreciated after an **in**crease

**in** non-agricultural employment of 13,000 **in**stead of the expected 130,000.

S**in**ce the futures prices are labelled up to the m**in**ute only, we divide the futures

prices uniformly over each m**in**ute at equal time **in**tervals (e.g. two futures

observations **in** m**in**ute 7:33 a.m. will become 7:33:20 and 7:33:40 a.m.). The

spot prices are multiplied by the cost-of-carry. This results **in** Fig. 4 where

we also **in**clude the spot spread.

On 4 June the futures market immediately reacted to the positive news **in** the

same m**in**ute as the news was released, 1 m**in** later followed by the spot quotes.

Yet, quotes were still appear**in**g on the Reuters FXFX page between 7:30 and

7:31 a.m. CST. Hence, the time-lag did not occur due to traders ®rst trad**in**g

and only then post**in**g new quotes. Also, it is surpris**in**g to see that the bid±

ask spread only **in**creases 1 m**in** after the news release. One would expect

spreads to **in**crease before the news release. Second July gives a similar picture.

The futures market is aga**in** the ®rst to react. In this case, however, it is obvious

that the futures market overreacted, s**in**ce even before the spot rate starts to decrease,

the futures price moves up aga**in**. Once aga**in** there were spot quotes immediately

after the release and the spread only **in**creased 2 m**in** after the release.

6.2. High volatility periods

To **in**vestigate the e€ect of high volatility more formally, we divide our data

accord**in**g to the rule given **in** Eq. (9). We experimented with several values for

the length of the **in**tervals, N (5, 10 and 20 m**in**), and the percentage of the standard

deviation, P (20% and 40%). The results are similar. We therefore only

give results for **in**tervals of 5 m**in** (N ˆ 5) and P equal to 20%, **in** Table 5.

The spill-overs between the futures and the spot markets are signi®cantly

stronger when volatility is high. This applies to both spill-over directions.

The signi®cant 1 m**in** lead of the Reuters spot quotes actually disappears **in**

the low volatility panel, while it is larger **in** magnitude **in** the high volatility

panel. One explanation is that **in** the case of high volatility related to news,

one market might react faster, immediately followed by the other market.

When there is no directly related news, the markets might follow each other,

but this e€ect will be noticeably smaller. 9

9 Similar results are found when we split up the sample accord**in**g to the time of the day, i.e. 7:20±

10:00 a.m. and 11:00 a.m.±14:00 p.m. CST. For the morn**in**g period we ®nd a 1-m**in** signi®cant lead

of the spot quotes **in** Table 4, while there is no spot lead left **in** the afternoon. The futures lead

extends to 5 m**in** for the afternoon period. From Fig. 1 it can be seen that trad**in**g activity decreases

once the European markets are closed. The fact that there is no signi®cant spot lead **in** the

afternoon period, can be attributed to the grow**in**g relative importance of the futures market once

the European traders retreat from the spot market.

362 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Fig. 4. Prescheduled news announcements.

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 363

Table 5

Cross-correlations between the DM/$ spot and futures exchange rate returns **in** high and low volatility

periods

Panel I: Low volatility Panel II: High volatility

corr(Dfe t 4 ,Dse t ) )0.0361 [0.014] 0.0349 [0.027]

corr(Dfe t 3 ,Dse t ) 0.0218 [0.013] 0.117 a [0.026]

corr(Dfe t 2 ,Dse t ) 0.296 a [0.016] 0.469 a [0.034]

corr(Dfe t 1 ,Dse t ) 0.244 a [0.015] 0.359 a [0.052]

corr(Dfe t ,Dse t ) 0.107 a [0.014] 0.193 a [0.030]

corr(Dfe t ,Dse t 1 ) 0.00117 [0.013] 0.0688 a [0.024]

corr(Dfe t ,Dse t 2 ) )0.0213 [0.012] 0.0274 [0.020]

Dse t and Dfe t are the prewhitened DM/$ spot and futures returns, respectively, us**in**g an AR(p) ®lter.

The sample period is June±August 1993, with for every day 1-m**in** observations from 7:20±

10:00 a.m. CST. The data are split up accord**in**g to the rule **in** Eq. (9), with P ˆ 0.20 and N ˆ 5. This

results **in** 2935 observations **in** the high volatility panel and 7400 observations **in** the low volatility

panel. For the spot returns we employed Panel B. Panel B uses, **in** addition to the last quote **in** each

m**in**ute, also the previous two quotes (if with**in** 15 seconds) to ®rst determ**in**e the best bid and ask

and then calculate the midpo**in**t. Heteroscedasticity and autocorrelation consistent (HAC) errors

**in**side brackets.

a Denotes signi®cance at 1% level.

b Denotes signi®cance at 5% level.

7. A simple trad**in**g strategy

Hav**in**g established a statistically signi®cant lead of the futures market over

the spot quotes, it is **in**terest**in**g to **in**vestigate its economic signi®cance. Of

course the underly**in**g test would be more reliable if we would have quotes from

brokers at which we could certa**in**ly trade. On the other hand, Reuters FXFX

page quotes usually **in**clude the broker's quotes, and thus the underly**in**g strategy

overvalues the trad**in**g costs. The spread of the broker can reduce to 1 tick,

while the m**in**imal spread on Reuters FXFX page is 5 ticks. For our sample period

**in** many cases the spread is 10 ticks or even 15 ticks. Especially when the

spread is skewed to one side, the test will overestimate the costs as compared to

reality.

In our test we employ the follow**in**g simple trad**in**g strategy:

M**in**ute t Observe whether jDFtj P f

M**in**ute t ‡ 1 Buy at St‡1;ask if DFt P f and St‡1;ask St‡1;bid 6 s

…case 1†

Sell at St‡1;bid if DFt 6 f and St‡1;ask St‡1;bid 6 s

…case 2†

M**in**ute t ‡ 3 Sell at St‡3;bid …case 1† Profit: St‡3;bid St‡1;ask

Buy at St‡3;ask …case 2† Profit: St‡1;bid St‡3;ask:

…10†

364 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

Thus, if it is observed at t that the absolute futures return exceeds a certa**in**

threshold f, then we buy/sell **in** the spot market at the ®rst observation **in**

m**in**ute t + 1 appear**in**g on Reuters screen if the spread is not too high,

i.e., less than a threshold s. The position is liquidated by sell**in**g/buy**in**g **in**

the spot market at the ®rst observation **in** m**in**ute t + 3, regardless of the

spread.

Apply**in**g this strategy to the total sample of three months for the 7:20±

10:00 a.m. CST w**in**dow results **in** Table 6. The ®rst number **in** columns 2±4

**in**dicates the total pro®t **in** DeutscheMarks per US dollar. Each time the strategy

is applied, it is either ``w**in**n**in**g'' or ``los**in**g''. The ®rst number **in**side brackets

denotes the number of times the strategy was w**in**n**in**g, the second number

denotes the number of times the strategy was los**in**g.

The results show that, despite the huge losses **in**duced by the overestimated

spot spreads, substantial ga**in**s could have been made (assum**in**g one can

always trade aga**in**st the Reuters quotes immediately after appearance). For

example, **in** the case of s equal to 0.0010 (10 ticks) and buy**in**g (sell**in**g)

when the futures return is at least 5 ticks (is below )5 ticks), the above strategy

would have earned 591 ticks **in** the spot market (w**in**n**in**g 70 times, los**in**g 34

times of the 104 times we apply the strategy). If the transaction size is 5 million

US dollar each time, then 1 tick is worth 500 Deutsche Marks. Thus,

591 ticks amounts to 295,500 Deutsche Marks. The standard error **in**side parentheses

show that this result is signi®cantly di€erent from zero. This also applies

to the majority of other entries **in** Table 6.

Table 6

Pro®ts from a simple strategy **in** the DM/$ exchange rate

|DFt| P f Spread 6 5 ticks Spread 6 10 ticks Spread 6 15 ticks

0.0001 )0.0915 [53;209] (0.0127) )0.7897 [647;1920] (0.0404) )1.6003 [845;3019] (0.0571)

0.0002 )0.0084 [26;58] (0.0080) )0.0831 [399;686] (0.0283) )0.3422 [612;1249] (0.0396)

0.0003 0.0099 [12;11] (0.0058) 0.0905 [195;162] (0.0214) 0.0660 [321;346] (0.0293)

0.0004 0.0067 [5;4] (0.0050) 0.0658 [85;42] (0.0174) 0.1084 [152;96] (0.0232)

0.0005 0.0055 [3;4] (0.0048) 0.0591 [70;34] (0.0168) 0.1010 [131;77] (0.0222)

0.0006 0.0059 [2;2] (0.0039) 0.0420 [31;11] (0.0116) 0.0910 [68;26] (0.0187)

0.0007 )0.0003 [0;2] (0.0002) 0.0285 [21;5] (0.0092) 0.0657 [40;15] (0.0166)

0.0008 0.0000 [0;0] ()) 0.0260 [10;0] (0.0089) 0.0484 [20;8] (0.0148)

0.0009 0.0000 [0;0] ()) 0.0251 [9;0] (0.0088) 0.0489 [19;7] (0.0147)

0.0010 0.0000 [0;0] ()) 0.0199 [7;0] (0.0079) 0.0422 [15;6] (0.0140)

Cumulative returns from the trad**in**g strategy **in** Eq. (10). A spot position **in** DM/$ is started based

on the ®rst observation **in** the m**in**ute after a futures **in**crease (decrease) and held for 2 m**in**.

Transaction costs are **in**curred by us**in**g the spot bid and ask quotes. Inside brackets the number of

times the strategy won and the number of times the strategy lost, respectively. Inside parentheses

the standard errors of the returns.

8. Conclusion

M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366 365

This study compares the DM/$ futures prices **in** Chicago with Reuters foreign

exchange page display**in**g spot exchange rate quotes of many di€erent

banks. Even though Reuters' FXFX page is ma**in**ly **in**dicative, reputation considerations

might **in**duce banks to trade at their quotes when asked to with**in**

reasonable time after the appearance on the screen. Also, broker's quotes are

usually with**in** the Reuter's quotes. Interest**in**gly, we ®nd that the futures market

is lead**in**g the quotes on Reuters FXFX page up to 3 m**in**. There is only a

small lead the other way around. This **in**formational lead is supported by the

**in**formation share as proposed by Hasbrouck (1995) show**in**g that the **in**formation

share of the futures market exceeds 89%.

In the case of prescheduled news announcements the futures lead is reduced

to approximately 1 m**in**. Spot traders might then ®rst trade and only later update

quotes on Reuters FXFX page. However, a few examples show that Reuters

FXFX page still conta**in**s new quotes with spreads of at most 10 ticks

immediately after the news release.

Not only does this question the assumption that one can trade aga**in**st the

quotes on Reuters screen, it also suggests an alarm**in**g **in**e ciency as an **in**formational

tool. Our results suggest that it deserves further attention to **in**vestigate

whether spot traders should more closely watch the futures market. 10

Especially banks putt**in**g quotes on the Reuters FXFX page should take current

developments **in** the futures market (if open) **in**to consideration.

Acknowledgements

The authors would like to thank Yuan-chen Chang, Michel Dacorogna,

Theo Nijman, Antoon Pelsser, Piet Sercu, Ton Vorst, Siegfried Trautmann,

Casper de Vries, two anonymous referees, participants of the 13th International

Conference of the French F**in**ance Association **in** Geneva (1996), and participants

of the 23rd European F**in**ance Association meet**in**g **in** Oslo (1996) for

useful comments. We are also grateful to the ABN-AMRO bank for allow**in**g

us to visit their deal**in**g-room **in** Amsterdam and speak with some of their trad-

10 Nowadays most trad**in**g occurs through the brokers, and Reuters claims that its electronic

brok**in**g system D2000 has a still grow**in**g market share. In the F**in**ancial Times (30 June 1997) it

was recently reported that over the ®rst quarter of 1997 Reuters had a daily average of 21,000

currency deals. Its ma**in** rival, EBS, had an average of 24,000 currency deals. Therefore, for future

research it is **in**terest**in**g to obta**in** data from both these brokerage systems (up to now they seem

hard to get for a reasonable period of time) and compare them with each other and with the futures

market **in** Chicago.

366 M. Martens, P. Kofman / Journal of Bank**in**g & F**in**ance 22 (1998) 347±366

ers. The Erasmus Center for F**in**ancial Research is gratefully acknowledged for

®nancial support. All rema**in****in**g errors are our own responsibility.

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