Exchange Rate Economics: Theories and Evidence

356 Market microstructure approach
The earlier discussion deals with market maker spreads – the determination
of brokers spreads are usually analysed separately. As we have seen,a brokered
spread is the combination of the best bid and best ask price received by the broker
as separate limit orders. Cohen et al. (1979) model limit orders as if they are generated
by ‘yawl’ distributions,named after their resemblance to a sailing boat.
Such distributions are argued to satisfy heuristics for the incentives of investors
placing limit orders (see also Cohen et al. 1981). However,such models have been
developed for the stock market,where brokerage is seen as a service providing predictable
immediacy. As we noted earlier,in our discussion of market makers,this is
not such an issue in the foreign exchange market since there are a large number of
market makers capable of providing this immediacy. Instead,as Flood (1991) notes,
one key advantage of a bank trading through a broker is that the name of the bank
remains anonymous until a deal is agreed and at that stage only the counterparty
knows the identity of the bank. Such anonymity is valuable because in revealing a
buy–sell position a market maker is potentially at a disadvantage compared to the
situation where he does not need to reveal his position. 5 Additionally,anonymity
can be advantageous to market makers who would not normally contact each other
directly. However,a theoretical model of anonymity has still to be developed and
therefore the determination of the broker bid–ask spreads in the foreign exchange
market is less well understood than that of market maker spreads.
14.4.2 Empirical evidence on the bid–ask spread
As we have seen,an implication of the inventory-carrying cost models is that the
costs in such models arise as a result of market makers having open positions in
currencies and they can be related to price risk,interest rate costs and trading
activity. In terms of price risk,the idea is that as exchange rate volatility increases,
risk-averse traders will increase the bid–ask spread in order to offset the increased
risk of losses. There is a lot of evidence in support of this positive relationship
between the spread and volatility. For example,Fieleke (1975),Overturf (1982)
and Glassman (1987) all show that spreads increase with recent volatility. Using
GARCH-based methods to model exchange rate uncertainty,Glassman (1987),
Boothe (1988) and Bollerslev and Melvin (1994) and Bessembinder (1994) show
that spreads are positively correlated with GARCH-expected volatility. In the
study of Jorion (1996),discussed in Section 14.3,the implied volatility from option
prices is shown to be positively related to the spread and,indeed,it is shown to be
a superior measure of volatility compared to the GARCH models used in other
studies. Using a term structure effect as a proxy for the cost of capital from investing
in short-term investments,Bessembinder (1994) shows that this has little effect on
the spread.
A number of studies have also shown that trading activity is an important determinant
of the spread. For example,Glassman (1997) and Bessembinder (1994)
and Jorion (1996) show that at time when markets are known to be less volatile–
at weekends and holidays – spreads tend to increase. Trading activity can also
be captured by volume and Cornell (1978) has argued that volume should be