52
`
`Mark D. Flood
`
`Mark D. Flood is an economist at the Federal Reserve Bank of
`St. Louis. David H. Kelly provided research assistance.
`
`Microstructure Theory and
`the Foreign Exchange Market
`
`GROWING BODY OF theoretical literature,
`known as the study of securities market micro-
`structure, deals with the behavior of participants
`in securities markets and with the effects of in-
`formation and institutional rules on the economic
`performance of those markets. These institu-
`tional factors may arise from technology, tradi-
`tion or regulation. Microstructure and its impact
`are important, because of the vast amounts of
`wealth which pass through securities markets —
`including the foreign exchange market —
`every day.
`
`Microstructure is of interest to students of the
`foreign exchange market: microstructural analy-
`ses of other markets have yielded insight into
`traders’ behavior and the effect of various insti-
`tutional arrangements. Conversely, the foreign
`
`exchange market is also of special interest to
`students of microstructure, because it combines
`two very different arrangements for matching
`buyers and sellers — bank dealers trade with
`one another both directly and through foreign
`exchange brokers.1
`
`Standard models of exchange-rate determina-
`tion concentrate on relatively long-run aspects,
`such as purchasing power parity. While micro-
`structure theory cannot address these issues
`directly, it can illuminate a more narrowly fo-
`cused array of institutional concerns, such as
`price information, the matching of buyers and
`sellers, and optimal dealer pricing policies. De-
`spite the substantial literature on microstructure,
`little attention has been paid to the particular
`microstructure of the foreign exchange market.2
`
`‘Similar arrangements exist for other securities—for exam-
`ple, the federal funds market and the secondary market
`for Treasury securities—but these too have been relatively
`neglected in the literature.
`2The shaded insert on the opposite page provides a context
`in which the microstructural approach can be compared
`with more traditional approaches to market efficiency.
`Following some early articles by Demsetz (1968), Tinic
`(1972) and Tinic and West (1972), Garman (1976) per-
`formed the crucial task of defining market microstructure
`as an independent area of the literature, thus focusing the
`debate. Since then, market microstructure has burgeoned,
`led by Cohen, Maier, Schwartz and Whitcomb (1978a,
`1978b, 1981, 1983), Amihud and Mendelson (1980, 1986,
`1988), Stoll (1978, 1985, 1989) and Ho and Stoll (1980,
`1981). See also Beja and Hakansson (1977), Cohen,
`Hawawini, Maier, Schwartz and Whitcomb (1980), Cohen,
`Maier, Ness, Okuda, Schwartz and Whitcomb (1977), Ami-
`hud, Ho, and Schwartz (1985), Schreiber and Schwartz
`(1986), Schwartz (1988) and Cohen and Schwartz (1989).
`
`FEDERAL RESERVE BANK OF St LOUIS
`
`Cohen, Maier, Schwartz and Whitcomb (1979, 1986) and
`Stoll (1985) have surveyed the microstructure literature.
`In addition to the early note by Allen (1977), very recently
`there have appeared some microstructural studies of the
`foreign exchange market: Bossaerts and Hillion (1991),
`Lyons (1991), Rai (1991) and Flood (1991). There is also
`an empirical
`literature measuring the determinants of the
`bid-ask spread in the foreign exchange market. See Black
`(1989), Wei (1991) and Glassman (1987) as well as the
`references therein. Because the focus of this article is on
`microstructure theory, such empirical studies receive little
`attention here.
`Finally, although a consideration of the results of laborato-
`ry experiments would expand the scope of this paper to
`unwieldy dimensions, their role in establishing the sensitiv-
`ity of market behavior to institutional factors must at least
`be acknowledged; see Plott (1982, 1991) for an in-
`troduction.
`
`GAIN CAPITAL - EXHIBIT 1021
`
`

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`NOVEMBER/DECEMBER 1991
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`

`

`54
`
`Figure 1
`Spot Market Volume by
`Transactor (4/89)
`customer
`(5.1%)
`
`(55.0%)
`‘Interbank Brokered
`(39.9%)
`
`change rates or simply to complete their own
`international transactions. Market-makers may
`trade for their own account — that is, they may
`maintain a long or short position in a foreign
`currency — and require significant capitalization
`for that purpose. Brokers do not contact cus-
`tomers and do not deal on their own account;
`instead, they profit by charging a fee for the
`service of bringing market-makers together.
`The mechanics of trading differ substantially
`between brokered transactions and direct deals.
`In the direct market, banks contact each other.
`The bank receiving a call acts as a market-maker
`for the currency in question, providing a two-
`way quote (bid and ask) for the bank placing
`the call. A direct deal might go as follows:
`“Mongobank with a dollar-mark
`Mongobank:
`please?”
`(Mongobank requests a spot market quote
`for U.S. dollars (USD) against German marks
`(DEM).)
`
`has roughly doubled every three years for the past
`decade.
`5Federal Reserve Bank of New York (l989a) lists 162
`market-making institutions (148 are commercial banks) and
`14 brokers; an earlier study, Federal Reserve Bank of New
`York (1980),
`lists 90 market-making banks and 11 brokers.
`
`This paper examines the extant literature on
`market microstructure to determine how it
`might be applied to the foreign exchange
`market.
`
`The paper begins with a brief description of
`the foreign exchange market. Aspects of the
`literature concerned with institutional details
`are addressed second, noting how such details
`can affect the performance of the market. Next,
`the literature dealing with behavioral details, es-
`pecially the communication and interpretation
`of price information, is considered. Finally, the
`interaction of institutional and behavioral fac-
`tors, notably the bid-ask spread, is discussed.
`
`INSTITUTIONAL BASICS OF THE
`FOREIGN EXCHANGE MARKET
`
`The foreign exchange market is the interna-
`tional market in which buyers and sellers of
`currencies “meet.”3 It is largely decentralized:
`the participants (classified as market-makers,
`brokers and customers) are physically separated
`from one another; they communicate via tele-
`phone, telex and computer network. Trading
`volume is large, estimated at $128.9 billion for
`the U.S. market in April 1989. Most of this trad-
`ing was between bank market-makers.~
`
`The market is dominated by the market-makers
`at commercial and investment banks, who trade
`currencies with each other both directly and
`through foreign exchange brokers (see figure IL”
`Market-makers, as the name suggests, “make a
`market” in one or more currencies by providing
`bid and ask prices upon demand. A broker ar-
`ranges trades by keeping a “book” of market-
`maker’s limit orders — that is, orders to buy (al-
`ternatively,
`to sell) a specified quantity of for-
`eign currency at a specified price — from which
`he quotes the best bid and ask orders upon re-
`quest. The best bid and ask quotes on a broker’s
`book are together called the broker’s “inside
`spread.” The other participants in the market
`are the customers of the market-making banks,
`who generally use the market to complete
`transactions in international trade, and central
`banks, who may enter the market to move ex-
`3For more thorough descriptions of the workings of the for-
`eign exchange market, see Burnham (1991), Chrystal
`(1984), Kubarych (1983) and Riehl and Rodriguez (1983).
`4See Federal Reserve Bank of New York (1989a) and Bank
`for International Settlements (815) (1990). Extending this
`figure over 251 trading days per year, this implies a trad-
`ing volume of roughly $32 trillion for all of 1989. Volume
`
`FEDERAL RESERVE BANK OF St LOUIS
`
`

`

`55
`
`Loans ‘n Things: “20-30”
`(Loans n’ Things will buy dollars at 2.1020
`DEM/USD and sell dollars at 2.1030 DEM/USD
`—the 2.10 part of the quote is understood.)
`
`Mongohank:
`“Two mine.”
`(Mongobank buys $2,000,000 for DEM
`4,206,000 at 2.1030 DEMIUSD, for payment
`two business days later. The quantity traded
`is usually one of a handful of “customary
`amounts.”)
`
`Loans ‘n Things: “My marks to Loans ‘n
`Things Frankfurt.”
`(Loans n’ Things requests that payment of
`marks be made to their account at their
`Frankfurt branch. Payment will likely be
`made via SWIFT.)e
`
`Mongohank:
`
`‘(My dollars to Mongobank New
`York.”
`(Mongobank requests that payment of dol-
`lars be made to them in New York. Payment
`will most likely be made via CHIPS.)7
`Spot transactions are made for “value date”
`(payment date) two business days later to allow
`settlement arrangements to be made with cor-
`respondents or branches in other time zones.
`This period is extended when a holiday inter-
`venes in one of the countries involved. Payment
`occurs in a currency’s home country.
`
`The other method of interbank trading is
`brokered transactions. Brokers collect limit
`orders from bank market-makers. A limit order
`is an offer to buy (alternatively to sell) a speci-
`fied quantity at a specified price. I,imit orders
`remain with the broker until withdrawn by the
`market- maker -
`
`The advantages of brokered trading include
`the rapid dissemination of orders to other
`market-makers, anonymity in quoting, and the
`freedom not to quote to other market-makers
`on a reciprocal basis, which can be required in
`the direct market. Anonymity allows the quoting
`bank to conceal its identity and thus its inten-
`tions; it also requires that the broker know who
`is an acceptable counterparty for whom. Limit
`
`eThe Society for Worldwide Interbank Financial Telecommu-
`nication (SWIFT) is an electronic message network.
`In this
`it conveys a standardized payment order to a Ger-
`case,
`man branch or correspondent bank, which,
`in turn, effects
`the payment as a local
`interbank transfer in Frankfurt.
`~TheClearing House for Interbank Payments System
`(CHIPS) is a private interbank payments system in New
`York City.
`
`orders are also provided in part as a courtesy
`to the brokers as part of an ongoing business
`relationship that makes the market more liquid.
`Because his limit order is often a market-maker’s
`first indication of general price shift, Brooks
`likens the posting of an order with a broker “to
`sticking out the chin so as to be acquainted
`with the moment that the fight starts.”8 Schwartz
`points out that posting a limit order extends a
`free option to other traders.~
`
`A market-maker who calls a broker for a quote
`gets the broker’s inside spread, along with the
`quantities of the limit orders. A typical call to a
`broker might proceed as follows:
`
`“What is sterling, please?”
`Mongoank:
`(Mongobank requests the spot quote for
`U.S. dollars against British pounds (GBP).)
`
`“1 deal 40-42, one by two.”
`Fonnieister:
`(Fonmeister Brokerage has quotes to buy
`£1,000,000 at 1.7440 USD/GBP, and to sell
`£2,000,000 at 1.7442 USD/GBP)
`
`“I sell one at 40, to whom?”
`Mongobank;
`(Mongobank hits the bid for the quantity
`stated. Mongobank could have requested a
`different amount, which would have re-
`quired additional confirmation from the bid-
`ding bank.)
`
`Fonmeisten [A pause while the deal is reported
`to and confirmed by Loans ‘n
`Things] “Loans ‘n Things London.”
`(Fonmeister confirms the deal and reports the
`counterparty to Mongobank. Payment ar-
`rangements will be made and confirmed
`separately by the respective back offices. The
`broker’s back office will also confirm the
`trade with the banks.)
`
`Value dates and payment arrangements are the
`same as in the direct dealing case. In addition to
`the payment to the counterparty bank, the banks
`involved share the broket-age fee. These fees are
`negotiable in the United States. They are also
`quite low: roughly $20 per million dollars trans-
`acted.’°
`
`tSee Brooks (1985), p. 25.
`9See Schwartz (1988), p. 239.
`‘°SeeBurnham (1991), p. 141, note 16, and Kubarych
`(1983), p. 14.
`
`NOVFMRFR/OFCFMRPR 1001
`
`1
`
`IIIIIIIIIIIIIIIII S
`
`

`

`56
`
`Figure 2
`Market-Maker Volume by
`Type (4/89)
`
`c— swap
`(23.4%)
`
`Futures and Options
`
`(5.2%)
`
`Outright Forward
`(4.6%)
`
`yen. Such a swap might be used to hedge an out-
`right purchase of six-month yen from a bank cus-
`tomer.’1 In effect, the swapping bank is
`borrowing yen for the six months of the outright
`deal. The foreign exchange market-maker swaps
`in yen — rather than simply borrow yen on a
`time deposit — because banks maintain separate
`foreign exchange and money market accounts for
`administrative reasons. Swapping is generally the
`preferred means of forward dealing (see figures 2
`and 3).
`
`In practice, the vast majority of foreign ex-
`change transactions involve the U.S. dollar and
`some other currency. The magnitude of U.S. for-
`eign trade and investment flows implies that, for
`almost any other currency, the bilateral dollar ex-
`change markets will have the largest volume.
`Consequently, the dollar markets are the most li-
`quid. The possibility of triangular arbitrage en-
`forces the law of one price for the cross rates.
`The upshot is that liquidity considerations out-
`weigh transaction costs. A German wanting
`
`The final category of participants in the for-
`eign exchange market is the corporate cus-
`tomers of the market-making banks. Customers
`deal only with the market-makers. They never go
`through brokers, who cannot adequately monitor
`their creditworthiness. Typically, a customer
`transacts with a bank with which it already has a
`well-established relationship, so that corporate
`creditwor-thiness is not a concern for the bank’s
`foreign exchange desk, and trustworthiness is not
`an issue for the customer. The mechanics of cus-
`tomer trading are similar to those of direct deal-
`ing between market-makers. A customer requests
`a quote, and the bank makes a two-way market;
`the customer then decides to buy, sell or pass.
`The chief difference between this and an inter-
`bank relationship is that
`the customer is not ex-
`pected ever to reciprocate by making a market.
`
`Participants in the foreign exchange market also
`deal for future value dates. Such dealing com-
`poses the forward markets. Active forward mar-
`kets exist for a few heavily traded currencies and
`for several time intervals corresponding to active-
`ly dealt maturities in the money market. Markets
`can also be requested and made for other ma-
`turities, however. Since the foreign exchange
`market is unregulated, standard contract speci-
`fications are matters of tradition and con-
`venience, and they can be modified by the
`transacting agents.
`
`Forward transactions generally occur in two
`different ways: outright and swap. An outright
`forward transaction is what the name implies, a
`contract for an exchange of currencies at some
`future value date. “Outrights” generally occur
`only between market-making banks and their
`commercial clients. The interbank market for out-
`rights is very small, because outright trading im-
`plies an exchange rate risk until maturity of the
`contract. When outrights are concluded for a
`commercial client, they are usually hedged im-
`mediately by swapping the forward position to
`spot. This removes the exchange rate risk and
`leaves only interest rate risk.
`
`A swap is simply a combination of two simul-
`taneous trades: an outright forward contract and
`an opposing spot deal. For example, a bank might
`“swap in” six-month yen by simultaneously buying
`spot yen and selling six-month forward
`
`“Hedging an outright purchase of currency with an oppos-
`ing swap deal still
`leaves an open spot purchase of the
`currency. This can be easily covered in the spot market.
`
`FEDERAL RESERVE BANK OF St LOUIS
`
`

`

`57
`
`Figure 3
`Broker Volume by
`Type (4/89)
`
`swap
`(39.4%)
`
`Options
`(3.5%)
`
`pounds, for example, will typically convert
`marks to dollars and then dollars to pounds,
`rather than trading marks for pounds directly.
`Though this is especially true in the American
`market, it holds for foreign markets as well.
`
`CLASSIFYING MARKETS
`The microstructure literature is by nature
`market-specific, and much of it concerns U. S.
`equity markets. This specificity has the advan-
`tage of realism, but it makes the immediate ap-
`plicability of some microstructural models to the
`foreign exchange market questionable. The first
`task is to define some basic microstructural con-
`cepts, identifying where the foreign exchange
`market fits into the context they provide. Such
`a taxonomy is important, because one of the
`fundamental lessons of the microstructure lit-
`
`12A similar situation obtains on the New York Stock Ex-
`change, where specialists act as either brokers or market-
`makers, depending on the level of activity in the market.
`135ee Wolinsky (1990), p. 1. He goes onto analyze theoreti-
`cally the difference in the price discovery process between
`centralized and decentralized markets. Schwartz (1988),
`pp. 426-35, refers to centralization as “spatial consoli-
`dation.”
`
`erature is that institutional differences can af-
`fect the efficiency of pricing and allocation.
`
`As described above, the foreign exchange
`market combines two disparate auction struc-
`tures for the same commodity: the interbank
`direct market and the brokered market. Defying
`a naive application of institutional Darwinism,
`whereby only the fitter of the two systems
`would survive, these trading methods appear to
`coexist comfortably.” The direct market can be
`classified as a decentralized, continuous, open-
`bid, double-auction market. The brokered mar-
`ket is a quasi-centralized, continuous,
`limit-book,
`single-auction market. The meanings of these
`classifications are explained below.
`
`Centralization
`
`In a centralized market, “trades are carried
`out at publicly announced prices and all traders
`have access to the same trading opportunities.”
`In a decentralized market, in contrast, “prices
`are quoted and transactions are concluded in
`private meetings among agents.”” A New York
`Stock Exchange’s (NYSE) specialist system is a
`centralized market; the interbank direct market
`for foreign exchange is a decentralized one.
`
`The distinction between centralized and de-
`centralized markets might seem to provide a
`neat dichotomy of possible market structures.
`The multiplicity of brokers in the foreign ex-
`change market violates this simple taxonomy,
`however. Each foreign exchange broker accum-
`ulates a subset of market-makers’ limit orders.
`This network of “brokerage nodes” is as dif-
`ferent from a fully centralized system as it is
`from a fully decentralized one. This arrange-
`ment is labeled here as “quasi-centralized.”
`
`Most microstructural studies have confined
`themselves to centralized markets, especially the
`NYSE’s specialist system and the National Associ-
`ation of Securities Dealers Automated Quotation
`(NASDAQ) System on the over-the-counter (OTC)
`market.” Although there are a number of im-
`portant decentralized markets, including the in-
`terbank direct foreign exchange market, rela-
`
`‘4For models of specialist systems, see Demsetz (1968), Tin-
`ic (1972), Garman (1976), Bradfield (1979), Amihud and
`Mendelson (1980), Conroy and Winkler (1981), Glosten
`and Milgrom (1985) and Sirri (1989). For studies of the
`OTC market, see Tinic and West (1972), Benston and
`Hagerman (1974), Ho and Macris (1985) and Stoll (1989).
`
`~ nn-,
`
`I
`
`IIIIIIIII1 IIIIII
`
`I
`
`

`

`58
`
`tively few studies have focused on the impact
`of decentralization.
`
`There is some evidence that differences in
`the degree of centralization between various
`markets cause differences in market perfor-
`mance. Garbade, in studying the largely decen-
`tralized ‘!‘reasury securities market, concludes
`that because brokerage tends to centralize
`trading and price information,
`it “uses time
`more efficiently,”” eliminates the most important
`arbitrages,” and benefits dealers by ensuring that
`orders are executed according to price priority.”
`
`The efficiency gains of centralized price infor-
`mation may imply economies of scale and, thus,
`a natural monopoly for brokers in securities
`markets. This is entirely consistent with the text-
`book presentation of the relativel greater opera-
`tional efficiency of centralized markets.” Thus,
`the fact that a number of brokers service the
`foreign exchange market seems to represent a
`discrepancy between theory and reality. Brokers
`do communicate among themselves, however, to
`eliminate the possibility of arbitrage between
`limit order books. While this helps explain the
`multiplicity of brokers, it does not fully resolve
`the issue of decentralization in the interbank
`direct market.
`Temporal Consolidation
`
`The distinction between a continuous market
`and a call market involves what Schwartz refers
`to as the degree of “temporal consolidation.””
`In a call market, trading occurs at pre-appointed
`times (the “calls”), with arriving transaction ord-
`ers detained until the next call for execution. In
`continuous markets, like the foreign exchange
`market, trading occurs at
`its own pace, and
`transaction orders are processed as they arrive.
`A 1-ange of intermediate arrangements falls he-
`t~veenthese two extremes.
`
`“See Garbade (1978). p. 497.
`“The textbook argument counts trips to market. Briefly, if
`there are N traders, then a total of N trips to a central
`marketplace are required for each to haggle with everyone
`else;
`to pair them bilaterally requires a total of N(N-I)!2
`trips.
`If trips are costly, then centralization is more ef-
`ficient.
`“See Schwartz (1988), pp. 435-47. Garman (1976), pp. 257’
`58, also describes continuous and call markets; he refers
`to these as asynchronous and synchronous markets,
`respectively.
`“See Hahn (1984), Negishi (1962), Beja and Hakansson
`(1977), as well as the references therein.
`“A continuous market cannot be viewed as a continuum of
`infinitesimally lived call markets. Clearing supply and de-
`
`FEDERAL RESERVE BANK OF St LOUIS
`
`Most rnicroeconorriic models assume call mar-
`kets. In a Walrasian thtonnemerir model, for cx-
`ample, an auctioneer calls out a series of prices
`and receives buy and sell orders at each price.
`When a price is found for which the quantities
`supplied and demanded are equal, all transactions
`are consummated at that price. Interestingly
`enough, Walras based this price discovery
`model on the mechanics of the Paris Bourse.
`
`Temporal consolidation can affect the perfor-
`mance of a market. Theoretical work indicates
`how continuous trading can alter- allocations,
`the process of price discovery and even the ulti-
`mate equilibrium price.” The basic thrust of
`these arguments is that, with continuous ttading,
`earlier transactions satisfy some consumer’s and
`producers, causing shifts in supply and detnand
`that affect prices for later transactions. As a
`result, the Pareto-efficiency characteristic of
`Walrasian equilibria does not necessarily obtain
`in continuous markets.”
`
`the periodic batching of
`On the other hand,
`orders that occurs in a call market also has dis-
`advantages. The difference in time between ord-
`er placement and execution can impose real
`costs on investors. A recurring argument in the
`literature is the willingness of investor-s to pat’
`more — a liquidity premium — for the ability to
`trade immediately. Similarly, periodic calls delay
`any information conveyed by prices until the
`time of the call, introducing price uncet-taintv in
`the period between the calls.
`
`In sum, a trade-off exists between the alloca-
`tional efficiency of the nearly ‘Nalrasian call
`market system and the informational efficiency
`and immediacy of the continuous market sys-
`tem.20 it is not clear whether the microstruc-
`ture of the foreign exchange market represents
`a globally optimal balance of these relative ad-
`
`mand in each such call market would require an infinite
`trading volume over the course of a day. Cohen and
`Schwartz (1989) recommend an electronic order-routing
`system for the stock exchanges. to facilitate the placement
`and revision of orders, This would encourage additional
`trading volume, making more frequent calls feasible.
`“See Stoll (1985), p. 72, and especially Schwartz (1988),
`pp. 442-53, for a more thorough exposition of the pros and
`cons of temporal consolidation. Intermediate arrangements
`are also possible. For example, Schwartz argues that
`many of the problems caused by infrequent batching in a
`call market might be overcome by expanding access to
`the market with computer technology, whereby the in-
`creased number of traders would allow for more frequent
`calls.
`
`

`

`59
`
`vantages. A persistent deviation from optimality
`might be explained, for example, by arguing
`that
`the allocational benefits of a call market
`system are a public good.
`
`Communication of Prices
`
`The terms “open-bid” and “limit-book” refer to
`ways in which price information is communi-
`cated. In an open-bid market — the open outcry
`system on the futures exchanges, for example
`— offers to buy or sell at a specified price are
`announced to all agents in the market. At the
`opposite extreme, in a sealed-bid market, orders
`are known only to the entity placing the order
`and perhaps to a disinterested auctioneer.
`
`Direct trading in foreign exchange approxi-
`mates the standard open-bid structure. The
`salient difference between the foreign exchange
`market and the standard arrangement is the
`bilateral pairing of participants in the foreign
`exchange market. In principle, any participant
`can contact a market-maker at any time for a
`price quote. The bilateral nature of such con-
`tacts and the time consumed by each contact
`together imply, however, that all participants
`cannot be simultaneously informed of the cur-
`rent quotes of a market-maker. This practical
`constraint on the dissemination of price infor-
`mation is significant:
`it introduces the possibility
`of genuine arbitrage, that is, of finding two
`market-makers whose current bid-ask spreads
`do not overlap.
`
`The limit order book, which is used by both
`foreign exchange brokers and stock exchange
`specialists, is another intermediate form of price
`communication. Although it would be possible
`in principle for foreign exchange brokerage
`books to be fully open for public inspection, in
`practice only certain orders — namely, the best
`bid and ask on each book — are revealed to
`market-makers, while the others remain con-
`cealed. As in the direct market, market-makers
`must contact brokers bilaterally to get these “in-
`side spreads.” Knowledge of the concealed limit
`orders would be of speculative value to market-
`makers, because an imbalanced book suggests
`that large future price movements are more
`likely in one direction than the other.
`
`More generally, price communication is inti-
`mately related to the role of market-makers as
`
`providers of “predictable immediacy.” Market
`participants are willing to pay a liquidity pre-
`mium, usually embedded in a market-maker’s
`spread, for the reduction in search costs im-
`plied by constant access to a counterparty. The
`costs of “finding” the other side of a transaction
`can be further broken down into the liquidity
`concession, the cost of communicating the in-
`formation and the cost of waiting for potential
`counterparties to respond.22 Other things equal,
`an efficient system of price communication is
`one that minimizes such transaction costs. While
`the communication of price information is a
`central function of securities markets, the fact
`that the systems of price communication in the
`foreign exchange market are not fully central-
`ized suggests that these systems do not represent
`a cost-minimizing arrangement.
`
`Structure of Prices
`
`The terms “double-auction” and “single-auction”
`refer to the nature of the prices quoted. In a
`double-auction market, certain participants pro-
`vide prices on both sides of the market, that is,
`both bid and ask prices. Participants providing
`double-auction quotes upon demand are known
`as market-makers, and they must have sufficient
`capitalization to back up their quotes. In a single-
`auction market, prices are specified either’ to
`buy or to sell, but not both. In the foreign ex-
`change market, market-makers provide double-
`auction prices, while brokers try to aggregate
`single-auction quotes into two-way (inside)
`spreads. A broker’s book may occasionally be
`empty on one or both sides. Rather than make
`a market in such cases, the broker provides,
`respectively, a single-auction quote or none at all.
`
`Thus, whether double or single-auction prices
`are quoted depends largely on whether the
`agent quoting prices is providing market-making
`services or simply attempting to acquire (or sell)
`the commodity. This issue is related to the
`degree of centralization in the market. The
`absence of market-makers in a single-auction
`market, together with the presence of search
`costs, results in a tendency toward centraliza-
`tion of price information, thus facilitating the
`search for a counterparty. Inversely, decentrali-
`zation of price information leads to a tendency
`
`2lThi5 term is due to Demsetz (1968), p. 35. Tinic (1972),
`p. 79, calls in “liquidity services.”
`
`“See Logue (1975), p. 118.
`
`IIIIIIIIIIIIIIIII a
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`60
`
`toward double-auction prices, again to facilitate
`the search for a counterparty.”
`
`MODELING TRADERS’ BEHAVIOR
`
`The microstructure liter’ature extends well be-
`yond a simple description of market institutions.
`Modeling the behavior of market participants is
`central
`to almost all discussions of micro-
`structure. Although numerous approaches to
`such modeling have been taken, two common
`concerns are of special interest. These are the
`treatment of price information by market par-
`ticipants, and determination of the bid-ask spread.
`The latter raises the interrelated issues of inven-
`tory and quantity transacted.
`
`Price Expectations
`
`Modeling the interpretation of price informa-
`tion is a crucial step in constrtcting microstruc-
`tural models of price discovery.” Many diverse
`approaches have been taken in such modeling.
`An almost universal simplification is to model
`securities markets in partial equilibrium, so that
`prices are not determined endogeneously in the
`traditional general equilibrium sense. This allows
`the modeler to focus on the microstructure’s
`finer details. Another common simplification is
`to assume that agents ignore the impact of their
`own behavior on the market.”
`
`Rather than explicitly model such forces as
`general equilibrium or recursive beliefs, models
`posit probability distributions that produce the
`prices of orders in the market. Modelers have
`included randomness at one or both of two lev-
`els, depending on their focus. First, order
`prices can be generated by objective distribu-
`tions, that is, by stochastic processes exogenous
`
`“Note that the converse does not appear to hold. That is,
`centralization does not tend to eliminate double-auction
`quoting. For example, the NASDAO system on the OTC
`stock market centralizes price information while still sup-
`porting numerous market-makers for every stock.
`“Notably, the term “price” is generally too inexact in a
`microstructurat context. One must often distinguish at a
`minimum between quoted prices, transaction prices and
`equilibrium prices. Ther