Exchange Rate Economics: Theories and Evidence

Market microstructure approach 341
In this chapter we consider the various aspects of the microstructure literature as
it relates to the foreign exchange market,in the following ways. First,we examine
to what extent expectations are indeed heterogeneous. To this end we focus on a
literature which uses disaggregate exchange rate survey data to gauge the extent
of heterogeneity in the foreign exchange market. We then go on to look at some
of the characteristics of the foreign exchange market and its key players – that is,
we examine the trading mechanisms of the foreign exchange market. Finally,we
examine some of the theoretical work on market microstructure.
14.1 Do foreign exchange market participants have
heterogeneous expectations? Some answers
from the surveydata literature
As we have noted,central to the MMH is the existence of heterogeneity amongst
foreign exchange market participants. If there is no heterogeneity,then the market
microstructural story does not get started. The existence of heterogeneous expectations
in the context of the foreign exchange market has been tested extensively
using a number of different disaggregate survey data bases. The testing methods
tend to follow two basic approaches. The first set of tests involves examining the
exchange rate expectations of agents,in terms of their unbiasedness,orthogonality
and evolution of expectations. Such tests may be regarded as indirect in the sense
that they are not specifically designed to capture heterogeneity. The second set of
tests,which we refer to as ‘direct’ tests,is based on variants of a test due to Ito (1990).
Survey data bases have also been used to calculate measures of dispersion which
are then related to key microsturcture variables such as volume,volatility and the
bid–ask spread.
14.1.1 Indirect tests of heterogeneity
Unbiasedness tests are based on the following kind of equation or some variant
of this which adequately addresses stationarity issues (see Chapter 15 for further
details):
s t+k = α + βs e t+k + ε t+k,(14.1)
where the null hypothesis of unbiasedness is α = 0 and β = 1 and the error
term is random. To test unbiasedness,Ito (1990) uses a survey data base,collected
by the Japanese Centre for International Finance,which consists of the individual
responses (44 in total) of a number of financial and non-financial institutions
on their expectations of the yen–dollar exchange rate,1,3 and 6 months ahead
for the sample May 1985–June 1987. He groups the survey responses into six
industrial classifications: banking,security companies,trading companies,companies
in the export industries,insurance companies and companies in the import
industries. He finds that unbiasedness is rejected for trading companies and insurance
companies at the 1-month horizon,for securities and import companies at