MASTER FILES
`ROOM C-525
`
`0440
`
`IMF WORKING PAPER
`
`& 1992 International Monetary Fund
`
`This is a Working Paper and the author would welcome any
`comments on the present text. Citations should refer to a
`Working Paper of the International Monetary Fund, men-
`tioning
`THE
`AUTHOR
`AND
`the
`date
`of
`i s s u a n c e.
`The
`v,••".*•,;
`e x p r e s s e d a r e t h e s e o f t h e a u t h o r a n d d o n o t n e c e s s a r i l y
`represent those of the Fund.
`
`WP/92/76
`
`INTERNATIONAL MONETARY FUND
`
`Research Department
`
`A Taxonomy of Automated Trade Execution Systems
`
`Prepared by Ian Domowitz *
`
`Authorized for Distribution by David Folkerts-Landau
`
`September 1992
`
`Abstract
`
`A taxonomy of existing and planned automated trade execution systems
`in financial markets is provided. Over 50 automated market structures in
`16 countries are analyzed. The classification scheme is organized around
`the principle that such markets consist of an algorithm that performs a
`trade matching function, together with information display and transmission
`mechanisms. Automated market structures are classified by ordered sets of
`trade execution priority rules, trade matching protocols and associated
`degree of automation of price discovery, and transparency, to include
`informational asymmetries between classes of market participants.
`Systematic differences in systems across types of financial instruments,
`geographical market centers, and over time are analyzed.
`
`JEL Classification Numbers:
`D44; G15
`
`* I would like to thank the National Science Foundation, the MidAmerica
`Institute, and the Center for Urban Affairs and Policy Research,
`Northwestern University, for financial support.
`
`©International Monetary Fund. Not for Redistribution
`
`GAIN CAPITAL - EXHIBIT 1019
`
`

`

`- ii -
`
`Contents
`
`Summary
`
`I. Introduction
`
`II. The Extent of Automated Trade Execution
`
`III. Classification by Ordered Sets of Priority Rules
`
`IV. Classification by Degree of Automation of Price Discovery
`
`V. Classification by Information Structure
`
`VI. Concluding Remarks
`
`Text Tables
`
`1. Automated Futures and Options Exchanges
`2. Automated Stock and Bond Exchanges
`3. Proprietary Automated Trading Systems
`4. Classification of Futures/Options Systems by Priority Rules
`5. Classification of Stock/Bond Systems by Priority Rules
`6. Classification of Proprietary Systems by Priority Rules
`7. Classification of Futures/Options Systems by Degree of
`Automation of Price Discovery
`8. Classification of Stock/Bond Systems By Degree of
`Automation of Price Discovery
`9. Classification of Proprietary Systems By Degree of
`Automation of Price Discovery
`10. Screen Transparency: Futures/Options Systems
`11. Screen Transparency: Stock/Bond Systems
`12. Screen Transparency: Proprietary Systems
`13. Public Information: Futures/Options Systems
`14. Public Information: Stock/Bond Systems
`15. Public Information: Proprietary Systems
`
`Figures
`
`1. Globex Main Display
`2. Globex Trading Window Detail
`3. Globex Trading Window Detail
`4. Sycom Main Screen with Trading Window
`5. DTB Main Trading Screen
`6. Cincinnati Stock Exchange Indepth Market Display
`7. Aurora Main Display
`
`Appendix. System Acronyms
`
`References
`
`Page
`
`iii
`
`1
`
`4
`
`10
`
`17
`
`24
`
`33
`
`5
`6
`7
`15
`16
`16
`
`22
`
`23
`
`23
`26
`27
`28
`30
`31
`31
`
`32a
`32b
`32c
`32d
`32e
`32f
`32g
`
`35
`
`37
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- iii -
`
`Summary
`
`Computerized trade execution is the final step in the automation of
`financial trading market operations, whereby traders submit orders through
`computer terminals, and the host computer determines trades, reporting
`results back to traders through their terminals. Over fifty automated trade
`execution systems currently operate worldwide, and at least five
`international organizations are looking into the regulation and
`standardization of the trade execution process.
`
`This paper provides unified technical summary of 53 automated trade
`execution systems, which are differentiated with respect to geographical
`location, date of inception, type of securities traded, and extent of global
`reach and are then described in terms of three classifications.
`
`First, automated systems are classified by an ordered set of trade
`execution priority rules, eleven of which are identified. The priority
`assigned to bids and offers for a security governs the place of the order in
`the queue awaiting execution, and determines the distributional properties
`of transaction prices, conditional on order flow. A comprehensive view of
`the nature of automated systems in sixteen countries is provided, by
`security type and over time.
`
`Second, automated systems are classified according to the degree of
`automation of the price discovery process in order to clarify the diversity
`of trade-matching algorithms observed in existing automated markets. The
`level of price discovery has implications for the type and degree of
`regulatory oversight of automated markets. Trends in the automation of the
`price discovery process by security type, market center, and over time are
`analyzed. It is found not only that the number of automated markets is
`growing over time, but also that the degree of automation of market
`structure within this class is increasing.
`
`Third, systems are classified by information structure. Regulatory
`concerns are focused on the type and amount of information provided to
`different classes of investors and system participants. Informational
`differences influence price volatility and liquidity of the market. All
`systems are classified with respect to the types of Information they offer
`to direct system participants. Asymmetries of information between traders
`working on the system and outside Investors, who do not have direct access
`to the automated market, are explored for a smaller set of markets. The
`paper examines differences in the provision of information by type of
`security, differentiating between futures and options trading and stock
`trading according to the degree to which participants have access to
`electronic order books.
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`This page intentionally left blank
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`I. Introduction
`
`Automation of a market can include computerization of information
`dissemination services, order routing, and clearance and settlement
`procedures. This paper is concerned with a different form of automation,
`that of the technology of trade execution: computerization of the trade
`matching, quantity allocation, and in most cases, price discovery
`mechanisms. The study of automated trade execution systems is a study in
`the design of automated auctions. Any system is basically a communications
`technology for passing messages between traders, combined with a set of
`rules for trade execution that have an impact on trading strategy and
`pricing outcomes. The latter are embodied in the trade matching algorithm.
`The former are manifested in the type of information displayed to system
`participants and in the types of bids, offers, and personal identifiers
`allowed by the system design.
`
`The theoretical and experimental literature on auctions, as well as
`work on the theory of financial market microstructure, indicates that the
`precise form of the trading institution matters a great deal in the analysis
`of agent behavior, the properties of transactions prices, and welfare. 1/
`Despite the extensive proliferation of automated trading markets, little is
`known about their structure. Yet, a substantial amount of transactions data
`from such systems soon will become part of the data banks upon which both
`theoretical observations and empirical work is based.
`
`The purpose of this paper is to provide a taxonomy of existing and
`planned automated trade execution and auction mechanisms in financial
`markets. 2/ The classification system is organized around the principle
`that automated trade execution systems are computerized mathematical
`algorithms that enable trade matching, combined with information display and
`transmission mechanisms. This classification is in three parts, although it
`will be clear that the divisions are not independent when examining any
`particular market.
`
`The first classification concerns priority of trade execution. The
`priority assigned to bids and offers, conditional on the state of the system
`at any given time, governs the place of the order in the queue awaiting
`execution. The distribution of bids and offers in the queue determines the
`
`1/ See, for example, the survey by Friedman (1992).
`2/ In particular, this paper is based on data for specific systems in
`practice, and is not a general normative discussion of possible system
`design. Proposals in the academic literature for elements of automated
`execution mechanism design date from the work of Black (1971), and include
`Peake, Mendelson, and Williams (1979), Amihud and Mendelson (1985), Cohen
`and Schwartz (1989), and Harris (1990).
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 2 -
`
`distributional properties of transactions prices, given the order placement
`strategies of traders. 1/
`
`The next classification scheme is by the degree of automation of the
`price discovery process. Automated trading systems exist which do not
`determine transactions prices endogenously within the system. On the other
`end of the spectrum, it is possible and planned to automate the pricing of
`certain securities requiring a variety of pricing inputs to the extent that
`only one such input is priced based on the trade matching algorithm and
`order flow, while the remainder are calculated by formula. The extent of
`automation of price discovery helps determine the amount of economic
`interest in any given automated market structure. This scheme is structured
`to clarify the diversity of matching algorithms observed in existing
`automated markets.
`
`The final classification is by information structure and transparency.
`Transparency is the extent to which trading information is made available
`after each discrete market event. The degree of transparency in a system
`influences variables such as price volatility and liquidity of the
`market. 2/ Regulatory concerns are focused on the types and amount of
`information provided to investors who are not direct system participants, as
`well as on information provided to traders and to themselves. The levels of
`transparency described in this paper relate directly to information
`displayed to various classes of system users and offer data on asymmetric
`information issues stemming from market design.
`
`Any taxonomy is in the mind of the particular individual designing the
`scheme, and other ways of classifying automated trade execution systems may
`be possible. The divisions selected here are important with respect to
`considerations of pricing and market efficiency. The particular taxonomy
`suggested also is not devoid of policy interest or motivation, especially
`with respect to regulatory issues. The United States General Accounting
`Office (GAO) has stressed the need for system information and technical
`reviews of automated markets that ensure that automated trade execution
`systems do not diminish an exchange's competitiveness and pricing efficiency
`(GAO, 1989). The Commodity Futures Trading Commission (CFTC) is required to
`judge new market mechanisms with respect to the openness and competitiveness
`of open outcry auction on a trading floor, based on CFTC Regulation 1.38.
`The public interest requirement of the 1974 Commodity Exchange Act even
`defines the public interest in terms of reliable price discovery. Similar
`concerns appear in the Security and Exchange Commission's (SEC) approach to
`
`1/ See Domowitz and Wang (1992) for an analysis of the stationary
`distribution of transactions prices in a simple automated system for
`continuous trading. It is shown, for example, that the distribution of
`prices differs greatly from that derived by Mendelson (1982) for the case of
`clearing house auctions.
`2/ See, for example, Madhaven (1992).
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 3 -
`
`the regulation of automated markets. 1/ All three divisions of the
`classification scheme are oriented to provide a basis for any such
`evaluations.
`
`On an international scale, the International Organization of Securities
`Commissions (IOSCO) currently is in the process of investigating regulatory
`issues surrounding the growth of automated systems world-wide. A review of
`automated execution algorithms is explicitly suggested for all regulatory
`jurisdictions in the IOSCO statement of principles for the oversight of
`screen-based trading systems (IOSCO, 1990). The form of the matching
`algorithm, including its priority rules, is held to have implications with
`respect to regulatory jurisdiction across countries, as well as for the
`degree of regulatory oversight required. 2/ One of the ten principles
`focuses explicitly on system transparency. Further concerns over
`transparency in automated trade execution mechanisms recently have been
`enunciated by the SEC. 3/
`
`The remainder of the paper begins in section II with an overview of the
`extent of automated trade execution in financial markets. Over 50 systems
`are listed, spanning financial centers in 16 countries. 4/ There is an
`additional taxonomy inherent in the presentation, with respect to
`geographical location, date of inception, and the extent of global reach for
`any system documented. Systems also are differentiated with respect to the
`type of securities traded, as well as with respect to their ownership.
`
`Section III contains the classification by trade execution priority
`rules. Eleven different rules in existence are isolated, and it is argued
`that all systems can be described by an ordered set of these priorities.
`The classification is applied to all systems listed in section II, providing
`a comprehensive view of the nature of systems on a global basis, by security
`type, and over time.
`
`The classification in terms of the degree of automation of price
`discovery is presented in section IV. Seven levels of such automation are
`described, and all systems are classified by a set of these levels. Each
`such degree of price discovery automation is linked to particular forms of
`
`1/ See, for example, Ruder and Adkins (1990), and the references in
`Domowitz (1990a).
`2/ See also Corcoran and Lawton (1991). Participants in the working
`group drafting the IOSCO statements included the United States, Australia,
`France, Italy, Japan, Switzerland, the United Kingdom, and West Germany.
`3/ See letter from Brandon Becker, Deputy Director, SEC, to Shokichi
`Takagi, Director, Secondary Market Division, Ministry of Finance, Japan,
`dated 29 July, 1991.
`4/ The list is as complete as possible, but some systems known to exist
`are excluded for lack of enough information. These include the Belgian,
`Austrian, and Barcelona exchanges, in particular. It also is possible that
`additional proprietary systems exist, but are unknown to the author.
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 4 -
`
`trade matching algorithms. Trends in the automation of price discovery by
`security type, market center, and over time are analyzed.
`
`Information structure is the topic of section V. A comprehensive set
`of data provided to users of existing systems is given. Systems are
`classified first with respect to information provided to traders directly
`participating in system trading. Differences in information provision by
`type of security receive special attention, with futures and options trading
`differentiated from stock trading by the degree to which participants have
`access to order books. Anonymity with respect to quotes also is
`investigated. Some examples of screen design are offered. Systems then are
`classified by the type of information transmitted to investors outside the
`system, who participate only indirectly through the transmission of orders
`to system traders. A view of the asymmetric information structure between
`traders and outside investors is thereby provided.
`
`A bibliographical note is in order here. Detailed information on
`automated trade execution systems is not widely available. The data
`presented in this paper are gathered from diverse sources, including
`regulatory documents and letters, surveys by the International Organization
`of Securities Commissions, and many exchanges. Citations for each
`individual fact would be unwieldy, at best. A list of such references is
`available upon request.
`
`II. The Extent of Automated Trade Execution
`
`Automation of the trade execution process in financial markets is
`taking place on a large scale. Trading floors, where they exist, are being
`superseded or complemented by automated trade execution systems on a
`worldwide basis. The institutions of open outcry floor trading and
`telephone dealer markets are consistently abandoned in favor of automated
`trade execution in the construction of new markets for both day and off-
`hours trading activity. Considerations of cost, market efficiency, and
`competition between exchanges for order flow, abetted by the advances in
`off-exchange trading, all have contributed to this growth in the utilization
`of technology.
`
`Tables 1 through 3 contain a listing of over 50 automated trade
`execution systems in use or planned over the next couple of years; full
`names of systems and their associated exchanges are given with their
`acronyms in the appendix. Tables 1 and 2 contain information on
`futures/options systems and stock/bond systems, respectively, operating as a
`formal exchange. This means that the market is regulated as an exchange in
`its domestic market, and definitions for such treatment vary from country to
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 5 -
`
`Table 1. Automated Futures and Options Exchanges
`
`System
`(Exchange)
`
`GLOBEX
`(CME)
`
`ATS/2
`(IFOX)
`
`FAST
`(LFOX)
`
`APT
`(LIFFE)
`
`ATS
`(NZFOE)
`
`SYCOM
`(SFE)
`
`FACTS
`(TIFFE)
`
`AUTOM
`(PHLX)
`
`DTB
`(GFOE)
`
`Date
`
`1992
`
`Hours
`
`Night
`
`1989
`
`Day
`
`1990
`
`Day
`
`1989
`
`Night
`
`1985
`
`Night
`
`1989
`
`Night
`
`1989
`
`Day
`
`1990
`
`Day
`
`1990
`
`1990
`
`Day
`
`Day
`
`Members
`(Terminals)
`
`(250)
`
`Number of
`Securities/
`Products
`
`100
`(potential)
`
`N/A
`
`N/A
`
`N/A
`
`37
`
`20
`(30)
`
`262
`
`N/A
`
`69
`
`37
`(135)
`
`4
`
`4
`
`1
`
`11
`
`5
`
`4
`
`37
`
`19
`
`2
`
`Global
`(Country)
`
`Yes
`(USA)
`
`No
`(Ireland)
`
`Yes
`(UK)
`
`No
`(UK)
`
`No
`(New Zealand)
`
`No
`(Australia)
`
`No
`(Japan)
`
`No
`(USA)
`
`Planned
`(Germany)
`
`No
`(Spain)
`
`S-MART
`(MEFF)
`
`MOFEX
`(MOFF)
`
`SOFFEX
`(SOFFE)
`
`CORES-F
`(TSE)
`
`CORES-O
`(TSE)
`
`SFTS
`(OSE)
`
`OTS
`(OSE)
`
`TGE
`(TGE)
`
`RAES
`(CBOE)
`
`AUTO-EX
`(AMEX)
`
`POETS
`(PSE)
`
`SOM
`(SOM)
`
`1990
`
`1988
`
`Day
`
`Day
`
`1988
`
`Day
`
`1989
`
`1988
`
`Day
`
`Day
`
`1989
`
`Day
`
`1988
`
`Day
`
`1985
`
`1985
`
`1991
`
`Day
`
`Day
`
`Day
`
`1985
`
`Day
`
`48
`(43)
`
`48
`(800)
`
`132
`(213)
`
`132
`(274)
`
`108
`(190)
`
`108
`(225)
`
`N/A
`
`N/A
`
`N/A
`
`N/A
`
`N/A
`(50)
`
`2
`
`14
`
`1
`
`1
`
`2
`
`1
`
`6
`
`180
`
`All equity
`options
`
`Listed
`equity
`options
`
`13
`
`No
`(Spain)
`
`No
`(Switzerland)
`
`No
`(Japan)
`
`No
`(Japan)
`
`No
`(Japan)
`
`No
`(Japan)
`
`No
`(Japan)
`
`No
`(USA)
`
`No
`(USA)
`
`No
`(USA)
`
`Yes
`(Sweden)
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 6 -
`
`Table 2. Automated Stock and Bond Exchanges
`
`System
`(Exchange)
`
`SEATS
`(ASX)
`
`CAC
`(Paris)
`
`IBIS
`(FSE)
`
`GTB
`(Milan)
`
`MORRE
`(MF)
`
`SIB
`(SSE) 1/
`
`SAEF
`(LSE)
`
`BEACON
`(BSE)
`
`NSTS
`(CSE)
`
`MAX
`(MSE)
`
`ABS
`(NYSE)
`
`OHT
`(NYSE)
`
`Date
`
`1987
`
`Hours
`
`Day
`
`1986
`
`Day
`
`1991
`
`Day
`
`1991
`
`1990
`
`1991
`
`1989
`
`1987
`
`1985
`
`1981
`
`1976
`
`Day
`
`Day
`
`Day
`
`Day
`
`Day
`
`Day
`
`Day
`
`Day
`
`1991
`
`Night
`
`Members
`(Terminals)
`
`90
`(600)
`
`45
`
`70
`(25)
`
`N/A
`
`20
`
`54
`(319)
`
`N/A
`
`N/A
`
`(54)
`
`N/A
`
`53
`(231)
`
`N/A
`
`Securities
`
`All ASX listed stocks
`
`All stocks
`Most bonds
`
`30 stocks
`29 bonds
`
`Most stocks
`(phased in)
`
`All stocks
`
`116 stocks
`
`LSE listed
`stocks
`
`Stocks traded
`over ITS
`
`425 stocks
`(2,700 capability)
`
`Exchange listed
`stocks
`
`Bonds
`
`NYSE stocks
`
`Global
`(Country)
`
`No
`(Australia)
`
`No
`(France)
`
`No
`(Germany)
`
`No
`(Italy)
`
`No
`(Quebec)
`
`No
`(Spain)
`
`No
`(UK)
`
`Yes
`(USA)
`
`No
`(USA)
`
`No
`(USA)
`
`No
`(USA)
`
`No
`(USA)
`
`SCOREX
`(PSE)
`
`PACE
`(PHLX)
`
`SOES
`(NASD)
`
`CORES
`(TSE)
`
`STS
`(OSE)
`
`CLOB
`(SSE)
`
`CATS
`(TSE)
`
`HKTS
`(SEHK)
`
`ELECTRA
`(CSE)
`
`1969
`
`Day
`
`1976
`
`Day
`
`1985
`
`Day
`
`1982
`
`Day
`
`1991
`
`Day
`
`1987
`
`Day
`
`1977
`
`Day
`
`1993
`
`Day
`
`N/A
`
`N/A
`
`N/A
`(2,405)
`
`124
`(375)
`
`76
`(305)
`
`N/A
`
`75
`(300)
`
`N/A
`
`1987
`
`Day
`
`N/A 2/
`
`MATCHMAKER
`(VSE)
`
`1988
`
`Day
`
`MAX-OTC
`(MSE)
`
`SAX
`(SSM)
`
`OLS
`(NYSE)
`
`1987
`
`Day
`
`1989
`
`Day
`
`1986
`
`Day
`
`N/A
`(200+)
`
`N/A
`
`N/A
`(300)
`
`N/A
`
`Listed stocks
`
`Listed stocks
`
`NASDAQ stocks
`
`1,612 TSE stocks
`
`1,009 OSE stocks
`
`SSE, HK listed
`stocks
`
`850 TSE stocks
`
`SEHK listed
`stocks
`
`2,000 bonds
`275 stocks
`
`1,500 stocks
`
`OTC stocks
`
`Listed stocks,
`bonds
`
`Odd lots for NYSE
`listed stocks
`
`No
`(USA)
`
`No
`(USA)
`
`No
`(USA)
`
`No
`(Japan)
`
`No
`(Japan)
`
`No
`(Singapore)
`
`No
`(Canada)
`
`No
`(Hong Kong)
`
`No
`(Denmark)
`
`No
`(Canada)
`
`No
`(USA)
`
`No
`(Sweden)
`
`No
`(USA)
`
`1/ Spanish stock exchanges: Madrid, Barcelona, Bilbao, Valencia.
`2/ All brokers are allowed terminal-to-host hookups.
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 7 -
`
`Table 3. Proprietary Automated Trading Systems
`
`Date
`
`Terminals
`
`Securities
`
`Global
`(Country)
`
`Yes
`(UK)
`
`No
`(UK)
`
`No
`(UK)
`
`Yes
`(UK)
`
`No
`(US)
`
`No
`(US)
`
`No
`(US)
`
`System
`(Exchange)
`
`INSTINET
`(REUTERS)
`
`BEST
`(KB)
`
`TRADE
`(BZW)
`
`1985
`
`N/A
`
`1986
`
`30
`
`1986
`
`N/A
`
`Stocks
`Bonds
`
`100 +
`UK stocks
`
`100 +
`UK stocks
`
`NORDEX
`(TRANSVIK)
`
`1990
`
`20
`Firms
`
`Scandinavian
`stocks
`
`WAS
`(WASI)
`
`POSIT
`(JEFCO)
`
`DELTA
`(RMJ)
`
`1991
`
`23
`
`1987
`
`N/A
`
`1988
`
`N/A
`
`Stocks
`Bonds
`
`Stock
`Portfolios
`
`Options on
`treasures
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 8 -
`
`country. 1/ Table 3 covers proprietary systems, which enable the trading
`of stocks for the most part, but includes one options system. 2/
`Proprietary systems are not registered as exchanges, although they are
`subject to many of the same trade reporting requirements. Automated systems
`are included in these lists only if the trading protocol explicitly excludes
`person to person interaction for the purpose of trade execution. There is a
`variety of proprietary off-exchange systems, in particular, that act mainly
`as electronic bulletin boards, requiring that trades actually be consummated
`by telephone. 3/
`
`Most of these efforts are very new. Over 25 systems have been
`installed between 1988 and 1991, with several more scheduled to start
`operation between 1991 and 1993. The vast majority of systems date from
`1985 or later. Recent growth is more pronounced in the futures and options
`area. Roughly 81 percent of automated futures/options exchanges have come
`on line since 1988, compared to 40 percent of total stock exchanges. This
`fact is partially explained by the growth in the trading of futures and
`options on a global basis. The number of financial futures and options
`listed on exchanges has grown from 16 in 1978 to 205 in 1988, for example,
`and the number of futures and options exchanges has grown accordingly. 4/
`As such growth stabilized, the number of automated futures/options exchanges
`introduced since 1990 (6) parallels new automated stock and bond systems
`(7), both representing about 28 percent of the total.
`
`Automated markets are classified with respect to the system sponsor
`(exchange or company), date of inception, location, and global reach. A
`total of 16 countries are represented. Hours of operation vary widely, and
`may even differ with respect to individual products traded on a given
`system. The main distinction is between systems which operate during the
`regular trading day and those that operate after-hours, usually
`
`1/ In the United States, for example, an exchange is defined within the
`context of the Securities Exchange Act under Section 3(a)(1). The
`definition is so broad that virtually anything could be considered an
`exchange. Regulatory history has shown, however, that merely having a
`communication technology for bringing together buyers and sellers is
`necessary, but not sufficient, for a securities market to be classified as
`an exchange.
`2/ Delta Government Options ("Delta") is operated by RMJ Securities, a
`registered clearing agency, and RMJ Options, a registered broker-dealer.
`The system trades options on underlying United States Treasury bills, bonds,
`and notes. Participants are primarily large banks and securities firms.
`3/ Twenty systems have been granted the right to operate as non-exchange
`facilities in the United States, for example. Several of these operate as
`such electronic bulletin boards. Others have failed by the time of the
`writing of this paper, including Econ Investment Software, Adler & Co.,
`Security Pacific, Troster Singer, Exchange Services, Transaction Services,
`and B&K Securities. See Becker, Adkins, Fuller, and Angstadt (1991).
`4/ See Chapman (1990), tables 6 and 7.
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 9 -
`
`supplementing a conventional trading floor. Examples of the latter include
`APT, GLOBEX and SYCOM for futures, and OHT for stocks.
`
`The vast majority of automated systems operate during regular trading
`hours. In many cases, the automated system is the main trading system of
`the exchange, i.e., all trades in a financial product are processed through
`the automated execution mechanism. Exceptions generally involve systems
`which are designed to handle only small retail customer orders. Such
`mechanisms use prices for trade matching based on activity in a floor
`trading market that usually is in operation during the same time period.
`These limited execution mechanisms are relatively rare in futures and
`options trading, including RAES, AUTOEX, AUTOM, and POETS. Examples in the
`case of the trading of stocks and bonds are BEACON, MORRE, PACE, SCOREX, and
`SOES. Most execution systems of this type are quite old, dating back as far
`as 1969. The newer generation of automated mechanisms is composed of
`systems that endogenize the price discovery process.
`
`Global reach pertains to whether or not terminals are located outside
`the home country. In most instances, a "no" in the last column of the
`tables implies that there are regulatory restrictions against such an
`operation, but that is not always the case. The IBIS stock trading system
`is under no such legal restriction, for example, but all terminals are
`located in Germany with no immediate plans for expansion into cross-border
`trading.
`
`Computerized exchanges easily lend themselves to the idea of cross-
`border trading. There are no real technological barriers. Despite the
`frequency with which one reads about "globalization of trading," however,
`electronic markets are not spearheading the move into international trading
`activity at present. Only 19 percent of futures/options systems are
`oriented this way, with the DTB system planning such operations. The FAST
`system of the London Futures and Options Exchange specifically advertises
`its international trading operations as a direct way to increase the number
`of market participants and attract liquidity. The GLOBEX system of the
`Chicago Mercantile Exchange will operate in partnership with foreign
`exchanges and offer overseas terminals. Although there is a small sample
`problem here, it appears that the movement towards building systems with
`some global reach is growing, with 29 percent of exchanges built after 1989
`exhibiting cross-border capabilities. In stock trading, only BEACON of the
`Boston Stock Exchange maintains a foreign connection, and it is limited to a
`link with Montreal. The best global reach is provided by INSTINET, which
`has terminals located around the world. Trading in U.S. equities is
`supplemented by dealing in U.K., French, German, Dutch, Swiss, Norwegian,
`Finnish, and Swedish stocks. Many of the problems arising with respect to
`greater cross-border trading activity through automated exchanges concern
`regulatory issues and international regulatory cooperation.
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 10 -
`
`III. Classification by Ordered Sets of Priority Rules
`
`The trade execution function is an algorithm that performs order
`matching according to a set of rules governing the priority of submitted
`bids and offers. The priority rules determine the place of a bid or offer
`in the queue awaiting execution. A match occurs under several
`circumstances, depending on the design of the system. In some systems, a
`match occurs the moment an order rises to the top of the queue, at a price
`possibly determined outside of the automated system. A match may occur in
`other designs when a bid or offer at the top of the queue is accepted
`directly by the touch of a button. In limit order matching systems,
`transactions occur when the orders cross; i.e., when the price of the best
`offer to buy is equal to or greater than that of the best offer to sell.
`This section is devoted to the priority rules; trade matching and price
`discovery is deferred to section IV.
`
`An example of a specific trade execution algorithm may help. The
`following subset of the GLOBEX limit order system trading rules is taken
`from Domowitz (1990b). 1/
`
`1.
`
`Order eligibility. A new order is eligible to be matched with a
`standing order, and a trade will result, whenever the following
`conditions occur:
`
`1.1 One order is a buy order and the other is a sell order.
`1.2 The two orders are for the same contract.
`1.3 The price of the buy order is greater than or equal to the
`price of the sell order.
`
`2.
`
`3.
`
`Trade price. If an order match is possible according to the criteria
`of Rule 1, then the trade will take place at the price of the standing
`order.
`
`Trade quantity. If an order match is possible according to Rule 1,
`then the trade will take place for a quantity equal to the smaller of
`the
`
`3.1 remaining quantity of the new order;
`3.2 remaining quantity of the standing order.
`
`4.
`
`Maximization of total trade size. If there are multiple standing
`orders eligible for matching against a new order, then matching will be
`considered in priority sequence until one of the following conditions
`is attained:
`
`1/ There also are special rules governing the setting of an opening price
`in the GLOBEX system, as well as a facility to directly take an existing bid
`or offer on the limit order book.
`
`©International Monetary Fund. Not for Redistribution
`
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`

`- 11 -
`
`4.1 the new order is completely filled;
`4.2 all eligible standing orders have been considered.
`
`5.
`
`Standing order priority.
`
`5.1 Price: for buy orders, higher price is higher priority; for
`sell orders, lower price is higher priority.
`5.2 Quantity: a standing order for "primary quantity" has a
`higher priority than that for "secondary quantity" if they
`are both at the same price. A standing order for secondary
`quantity has priority over a standing order for primary
`quantity if the supplementary quantity is at a better price.
`A supplementary quantity order may be executed only in
`conjunction with its associated primary quantity.
`5.3 Time: Within the same price and quantity type, older orders
`have higher priority.
`
`The first three rules are a part of most trade execution algorithms.
`The term "standing order" refers to a bid or offer entered previously into
`the system, which has been saved on the electronic order book. The fact
`that the trade takes place at the price of the standing order replicates
`floor trading practice. Variations of rule 4 are not independent of
`priority rules, and are considered below in that context. A possible
`alternative would be to have some kind of sharing rule among all orders at
`the same price, regardless of time of order entry.
`
`There are three priority rules that govern this execution algorithm.
`Best price (5.1) is the chief priority. Following price is time: first in,
`first out. The final priority is one of display. A trader may split a bid
`or offer at the same price into primary and secondary amounts. The primary
`quantity is shown to all system participants. The secondary quantity is not
`displayed. The displayed quantity has precedence over that which is not
`displayed. If a trader's secondary quantity cannot be executed at the same
`time as the primary, the system will cancel the secondary bid or offer, as
`undisplayed orders have zero priority if they stand alone without some
`displayed quantity.
`
`The purpose of this section is to describe the trade execution priority
`rules used in practice. 1/ In principle, all automated trade execution
`systems can be characterized by an ordered list of such rules. The list
`below is not ordered in any particular fashion, however.
`
`1/ Harris (1990) also discusses selected order precedence rules, but more
`from a normative point of view with an eye towards improvements of rules in
`efforts to increase liquidity in the market. The list here is more
`comprehensive, but covers only rules currently used on existing systems.
`
`©International Monetary Fund. Not for Redistribution
`
`

`

`- 12 -
`
`P1. Price
`
`Best price is the highest priority on virtually all systems. Trade
`matching systems which take transactions