WO2000026834A2 - Reseau croise et procede y relatif - Google Patents

Reseau croise et procede y relatif Download PDF

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Publication number
WO2000026834A2
WO2000026834A2 PCT/US1999/025369 US9925369W WO0026834A2 WO 2000026834 A2 WO2000026834 A2 WO 2000026834A2 US 9925369 W US9925369 W US 9925369W WO 0026834 A2 WO0026834 A2 WO 0026834A2
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Prior art keywords
price
orders
order
ofthe
satisfaction
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PCT/US1999/025369
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English (en)
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WO2000026834A3 (fr
Inventor
John T. Rickard
William A. Lupien
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Optimark Technologies, Inc.
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Application filed by Optimark Technologies, Inc. filed Critical Optimark Technologies, Inc.
Priority to EP99971554A priority Critical patent/EP1131764A2/fr
Priority to AU14558/00A priority patent/AU1455800A/en
Publication of WO2000026834A2 publication Critical patent/WO2000026834A2/fr
Publication of WO2000026834A3 publication Critical patent/WO2000026834A3/fr
Priority to GBGB0428305.7A priority patent/GB0428305D0/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Definitions

  • the present invention is directed to an automated crossing network (also known as a matching system) and method, and in particular, to an anonymous and confidential crossing network that matches buy and sell orders by maximizing the mutual satisfaction of traders submitting orders.
  • an automated crossing network also known as a matching system
  • an anonymous and confidential crossing network that matches buy and sell orders by maximizing the mutual satisfaction of traders submitting orders.
  • crossing networks used in connection with the trading of trading instruments are disclosed in U.S. Pat. No. 4,412,287, which discloses an automated stock exchange in which a computer matches buy and sell orders for a variety of stocks; U.S. Pat. 3,573,747. which discloses an anonymous trading system for selling fungible properties between subscribers to the system; U.S. Pat. 3,581,072, which discloses the use of a special purpose digital computer for matching orders and establishing market prices in an auction market for fungible goods; U.S.
  • Pat. 4.674,044 which discloses an automated securities trading system
  • U.S. Pat. 5,136,501 which discloses an anonymous matching system for effectuating trades through automatic matching in which buyers and sellers who are willing to trade with one another based on specified criteria, such as price, quantity and credit, may automatically trade when matching events occur satisfying these criteria
  • U.S. Pat. No. 5.101,353 which discloses an automated system for providing liquidity to securities markets in which orders are entered by the system and executed in real time either internally between system users or externally with stock exchanges and markets.
  • Crossing networks have a number of advantages, including: (a) traders need not search for a contraparty; and (b) anonymity is preserved.
  • Instinet ' s Crossing Network and POSIT Portfolio System for Institutional Trading
  • POSIT Portfolio System for Institutional Trading
  • the Instinet Crossing Network has an equities trading service to match buyers and sellers anonymously at set times. Computers pair buyers with sellers on a time priority basis. Trades are executed at the closing price for exchange-listed issues, and at the midpoint ofthe inside market (best bid and ask) for OTC issues.
  • POSIT for example, enables large investors to trade baskets of stocks among themselves.
  • the orders are sent to a central computer where they are electronically matched with other orders.
  • POSIT crosses are done during the trading day.
  • the prices are obtained from those quoted on the exchanges, a practice known as "parasitic pricing. " ' See “Reshaping the Equity Markets, A Guide for the 1990s” cited above.
  • Instinet owned by Reuters, also operates an electronic block-trading system that facilitates the negotiation of block trades between institutional investors and brokers. Instinet allows parties to trade anonymously, entering bids electronically. Instinet subscribers can respond to an "order" entered into the system either by matching a displayed price or by making a counter bid or offer that is transmitted instantaneously to the contraparty's terminal. The trades that result from these negotiations become public information only when they are executed. This procedure provides an alternative to the direct human-to-human negotiation of orders in the upstairs market or on the trading floors. Instinet provides a limit order book for over-the-counter (OTC) securities and listed securities and also provides inside quotes for exchange listed securities for the seven U.S. exchanges on which stocks can be traded and for NASDAQ listed securities.
  • OTC over-the-counter
  • crossing networks function independently of existing stock exchanges. However, some crossing networks are operated by stock exchanges.
  • the Match Market Exchange (“MMX") is operated by the Chicago Stock Exchange. All matched orders are executed at a random time within a predetermined ten minute window at the market price at such time. The market price is calculated based upon the spread of a particular issue. Rather than matching orders on the basis of time priority, the MMX system uses liquidity fees and liquidity credits to determine the level of priority for order matching. Those users willing to pay the highest liquidity fee have the highest execution priority. See 59 F.R. 5451 (February 4, 1994).
  • Crossing networks that automatically match buy and sell orders often concentrate trading at a single point of time, and can be called a batch process matching system. There is a need, however, for an anonymous crossing network that continuously, and in real-time, satisfies the buying and selling desires of an arbitrary number of market participants.
  • a major problem encountered in the design of crossing networks is that of determining how to match buyers and sellers.
  • Existing approaches to this problem include:
  • Premium strategies (as in the Chicago MMX system), where bids and offers have an associated positive or negative premium, and crossing takes place at the midpoint of market spread or at the minimum necessary premium differential from the midpoint, with priority given in order of premium.
  • the premium-based priority in matching provides the incentive for offering higher premiums.
  • Each ofthe above approaches is a batch process that relies upon ad hoc rules of competition among a relatively small set of discrete orders as being the means of arbitrating the crossing network participants' buy /sell entries.
  • orders to buy or sell can enter the market at any time, and discrete orders in a crossing network often represent only an approximate and partial expression of the order fill that would satisfy the trader.
  • discrete orders in a crossing network often represent only an approximate and partial expression of the order fill that would satisfy the trader.
  • an individual order seldom represents the full desired fill size, and the trader must then employ multiple orders at different prices (and generally in different markets) to achieve his ultimate fill.
  • existing crossing networks allow discrete buy or sell orders to be entered, e.g., "sell 10.000 IBM at 64.”
  • Existing crossing networks do not easily allow traders to enter combinations of orders, such as "sell 10,000 IBM at 64 only if I can buy 20,000 DEC at 32".
  • existing crossing networks do not allow traders to enter combinations of orders, such as "sell 10.000 IBM at 64 or sell 100,000 IBM at 63.”
  • Traders often have trading strategies such as, for example, "buy 3,000 IBM at 33, but if I can buy 5,000. 1 would be prepared to pay 33 and V ⁇ that cannot be handled by existing crossing networks.
  • a crossing network is needed that will guarantee mathematical optimality ofthe matching process, so that each participant is assured that the overall outcome of the process (in terms ofthe price and size of all fills) has maximized the joint satisfaction of all participants.
  • the present invention is directed to a computerized crossing network that allows traders to input as orders a satisfaction density profile and maximum size limit which at once characterizes the trader ' s degree of satisfaction to trade at any and all prices and sizes, up to the aggregate (or size) limit, and that matches orders (as represented by each trader's satisfaction density profile) so that each trader is assured that the overall outcome ofthe process (in terms of average price and size of fill) has maximized the mutual satisfaction of all traders.
  • the satisfaction density profile is a two-dimensional grid or matrix (which could also be represented as a two-dimensional graph or in another two-dimensional format), one dimension being price and the second dimension being size of transaction, that as a whole characterizes the trader ' s degree of satisfaction for a transaction at each (price, size) coordinate.
  • Each element ofthe satisfaction density profile called a satisfaction density value, indicates the trader's degree of satisfaction to trade that size order at that price.
  • each satisfaction density value is a number between zero and one, with zero representing no satisfaction (i.e., will under no circumstances trade that quantity at that price) and one representing total satisfaction.
  • Each trader can input one or more satisfaction density profiles.
  • each satisfaction density profile can be represented and input as a graph of at least two dimensions, such as, for example, as a temperature grid or two dimensional matrix.
  • a trader may input a limit order that may be converted into a satisfaction density profile.
  • the trader once the satisfaction density profile is complete, the trader causes the satisfaction density profile to be transmitted to a central matching controller ("CMC"), which anonymously matches buy and sell orders as discussed below.In this embodiment, the CMC may maintain the characteristics ofthe orders represented by the satisfaction density profiles confidential.
  • CMC central matching controller
  • such characteristics may include the name of a security, a price of a security, a quantity of shares of a security, a preference value for trading a particular security at a certain price and volume, conditions relating to the way in which the buy/sell order for a particular security should be filled or satisfied (e.g., all/none, fill or kill, immediate or cancel, corporate buy back, etc.), and combinations thereof.
  • the present invention can easily handle trades of baskets of securities. For example, in the representative embodiment, if a trader wishes to simultaneously both sell IBM and buy DEC, the trader would create a sell satisfaction density profile representing the IBM part of the transaction and a buy satisfaction density profile representing the DEC part ofthe transaction, and indicate that these profiles are to be linked together. The CMC will then combine these two satisfaction density profiles into one. This combining process can be accomplished, for example, by utilizing a connection matrix and performing matrix manipulation on the two profiles. It will be apparent that other, more complex, combined trades can be accomplished in the same manner.
  • the present invention can be operated as a batch crossing network, where orders are matched at set times.
  • the present invention can be operated as a continuous crossing network by treating each new satisfaction density profile that is entered as a triggering event that causes a new round of computation as described above.
  • One aspect ofthe subject invention is directed to a method for matching orders.
  • the method includes the steps of receiving a plurality of orders, wherein each order has a source and characteristics associated therewith; maintaining the source ofthe plurality of orders anonymous; maintaining the characteristics ofthe plurality of orders confidential; and matching at least some of the orders based on a mutual satisfaction function.
  • the method includes the steps of creating plurality of buy and sell kernels based on buy and sell orders for a security. Each kernel has a price ofthe security at which a trader willing is willing to buy /sell the security, a minimum and maximum volume ofthe security that the trader is willing to buy/sell, and priority characteristics associated therewith.
  • the method also includes the steps of sorting the buy and sell kernel based on the priority characteristics; selecting a buy/sell kernel from the sorted buy and sell kernels; and aggregating sell/buy kernels against the selected buy/sell kernel at the price associated with the kernel.
  • the method may also include the steps of altering the price ofthe selected kernel; aggregating sell/buy kernels against the selected buy/sell kernel at the altered price; and executing a trade ofthe security associated with the kernel at the altered price.
  • Fig. 1 is a block diagram of a representative system operating according to the present invention
  • Fig. 2 is an example satisfaction density profile for a sell order
  • Figs. 3A to 3D are example satisfaction density profiles in contour plot format
  • Fig. 4A and 4B are examples of interface windows, used to set parameters for and enable input of satisfaction density profiles
  • Fig. 5 is a load pattern interface window, used to load parameterized satisfaction density profile templates:
  • Fig. 6A and 6B are examples of screen displays showing an interface window, a load pattern interface window and a satisfaction density profile;
  • Fig. 7 is an example buy satisfaction density profile displayed as a temperature graph
  • Fig. 8 is a description ofthe matching process in flow chart format
  • Figs. 9A to 9C are example mutual satisfaction cross products, represented as contour graphs
  • Fig. 10 depicts a preference profile for use in the exemplar)' embodiment for use with a specific exchange
  • Fig. 11 shows an illustration of explicit price and volume controls in accordance with one aspect ofthe present invention
  • Fig. 12 shows an illustration of implicit price controls generated by the system according to another aspect ofthe present invention:
  • Fig. 13 is an illustration of a preference profile with no implicit price controls according to yet another aspect ofthe present invention.
  • Fig. 14 is an illustration of coordinates with and without standing according to a further aspect ofthe present invention.
  • Fig. 15 is a flow chart representing the sequential steps ofthe matching algorithm of the subject invention.
  • Fig. 16 is a flow chart representing the sequential steps ofthe aggregation stage ofthe matching algorithm of Fig. 15;
  • Fig. 17 is a flow chart representing the sequential steps ofthe negotiation stage ofthe matching algorithm of Fig. 15.
  • the present invention is described below in the context of trading equity securities.
  • the invention is not so limited and can be easily adapted to allow the trading of anything that can be bought or sold, including liquid assets such as futures, derivatives, options, bonds, currencies, commodities, insurance contracts, and the like.
  • the invention may be employed to trade media time, airline tickets, concert tickets, electronic components, or any contract for goods or services.
  • the term instrument is used in its broadest meaning to cover anything that may be bought or sold. Accordingly, where the context permits, the terms "securities", “stock”, and “shares” when used herein includes other instruments that can be traded, such as, for example, futures, derivatives, options, bonds and currencies.
  • the terms “buy “ and "sell” include, where appropriate, put and call, bid and offer, etc.
  • Intended users ofthe representative embodiment system of this invention are typically investors, such as institutional investors (e.g., a pension fund) but may also be individual investors, brokers or others who deal in or trade securities.
  • institutional investors e.g., a pension fund
  • investors may also be individual investors, brokers or others who deal in or trade securities.
  • the term "user”, "trader” or “investor” means that person or entity who wishes to make a trade.
  • a central matching controller (“CMC") 2 matches buy and sell orders transmitted to the CMC from various trader terminals, e.g., 10, 12, 14.
  • the CMC 2 is preferably a supercomputer that can perform matrix calculations at rates of multiple gigaflops, such as. for example with present technology, an IBM SP2 or an Intel PARAGON supercomputer.
  • a storage device 4 is coupled to the CMC 2.
  • the storage device 4 comprises a database for storing buy and sell satisfaction density profiles.
  • buy satisfaction density profiles can be stored in a buy profile database 6 and sell satisfaction density profiles can be stored in a sell profile database 8.
  • Each trader who wished to trade will have access to a trader terminal, such as trader CPU 10, 12. 14.
  • the trader terminals 10, 12, 14 are high powered personal computers or workstations.
  • the trader terminals 10. 12, 14 are coupled to the CMC 2.
  • Trader terminals may be coupled to the CMC 2 over a wide area network (WAN) and/or over the Internet.
  • Each trader terminal includes one or more input output devices 16, 18, 20 that allow for the entry of satisfaction density profiles and the display of output, such as matching trades.
  • a trader may input a buy or sell order as a limit order.
  • software residing within either the CMC 2 or a trader terminal 10, 12. 14 may convert the limit order into a satisfaction density profile.
  • Each order has a source and characteristics associated therewith.
  • the source of an order identifies the person or entity submitting the order (e.g., the name of a trader, a specialist, a market maker, a firm, and combinations thereof).
  • a characteristic of an order is information that relates to the order, for example, a name of a security, a price of a security, a quantity of shares of a security, conditions relating to the order for a security, and combinations thereof.
  • the conditions relating to the order for a security e.g., "Day,” “All or none,” “Fill or kill,” “Immediate or cancel," “Good until first fill,” and “Corporate buy back) are described in more detail below.
  • the CMC 2 maintains the identity ofthe sources of orders anonymous and maintains the characteristics ofthe orders represented by the profiles confidential. Thus, in this embodiment, the sources and characteristics ofthe orders submitted to the CMC 2 are not disclosed to other traders. This reduces the market impact that an order might otherwise have on the price of a security.
  • FIG. 2 there is illustrated an example satisfaction density profile for a sell order.
  • each security that a trader wishes to trade requires the creation of a satisfaction density profile.
  • the satisfaction density profile as shown in Fig. 2 is a two-dimensional grid. Quantity is represented on the vertical axis and price is represented on the horizontal axis. (The ranges and scale of each axis can be set by the trader or automatically set by the present invention.) The satisfaction density levels are described by the numbers shown.
  • the satisfaction density profile characterizes the trader's range of interest in the transaction at each (price, size) combination.
  • the trader is required to enter in one or more places on the satisfaction density profile a satisfaction density value, indicating the trader's willingness to trade that size order at that price.
  • each satisfaction density value is a number between and including zero and one, with zero representing no satisfaction (i.e., will under no circumstances trade that quantity at that price) and one representing total satisfaction.
  • Fig. 2 shows that the trader is fully willing to sell 7,500 at $73, but under no circumstances is willing to sell any quantity at $70.25.
  • the satisfaction density value to sell 2.250 at $72.25 is 0.3, indicating a limited degree of satisfaction.
  • Fig. 2 shows that the trader is more willing to sell 8.250 at $72.75 then 1.500 at $73.25.
  • a boundary is shown, marked B1-B2-B3-B4.
  • the user is able to draw a boundary on the satisfaction density profile.
  • the user can enter satisfaction density values.
  • the satisfaction density values are automatically set to zero.
  • Fig. 3A there is illustrated an example satisfaction density profile for a buy order.
  • the satisfaction density profile as shown in Fig. 3A is a contour plot on a two-dimensional grid. Price is represented on the vertical axis and quantity is represented on the horizontal axis. The satisfaction density levels are described by the contours shown.
  • each satisfaction density value is a number between and including zero and one, with zero representing no satisfaction (i.e., will under no circumstances trade that quantity at that price) and one representing total satisfaction.
  • Fig. 3A shows that the trader would be highly satisfied to buy 1,500 at $20.50, but under no circumstances is willing to buy any quantity at $24.
  • the satisfaction density value for a buy of 3,000 at $20 is 0.6, indicating a more limited degree of satisfaction.
  • Fig. 3 A shows the trader is more willing to buy 2,000 shares at $21 than 4.000 shares at $21.
  • Fig. 3B shows an example satisfaction density profile for a sell transaction in the same format as the contour plot in Fig. 3 A.
  • the satisfaction density profile of Fig. 3B could represent, for example, an agency sell order.
  • Fig. 3C shows a satisfaction density profile for a sell transaction.
  • Fig. 3C illustrates a "soft" limit order.
  • Fig. 3D shows a satisfaction density profile for a buy transaction.
  • FIG. 4A there is illustrated an example interface window 21 that can be used by a trader to set parameters when inputting a satisfaction density profile (see also Fig. 4B).
  • the interface window 21 is displayed on an Input/Output device (e.g.. 16, 18, 20).
  • the interface window 21 in the representative embodiment can be manipulated according to standard graphical user interface (GUI) commands by a user using, for example, a mouse and a keyboard.
  • GUI graphical user interface
  • a Side indicator 22 allows the trader to set the type of transaction, e.g.. buy, sell, sell short etc.
  • a Symbol indicator 24 allows the trader to set the instrument being traded, e.g., for stocks, the ticker symbol; for futures, the futures symbol, etc.
  • a Maximum Quantity indicator 26 allows the trader to set the maximum quantity to be traded. In Fig. 4A, the trader has entered a buy profile to buy a maximum quantity of 50,000 Motorola shares.
  • the trader can also set a Time-in-Force indicator 28 that determines for how long the order will be valid. Examples of valid Time-in-Force settings include "good until canceled", “good until end of day " and for a set period of time.
  • a Surface Description section 30 of the interface window 21 allows the trader to define the dimensions ofthe satisfaction density profile.
  • a Center Price parameter 32 is used to set the price that is displayed in the center of price axis ofthe satisfaction density profile.
  • a Price Range parameter 34 shows the range for the price on the price axis.
  • a Price Interval parameter 36 enables the trader to set the price interval (i.e.. scale) on the price axis ofthe satisfaction density profile. For example, as shown in Fig. 4A. the center price is set at 48 and the price range at 6. Thus, the price axis will vary from a price of 45 to a price of 51 (with 48 being in the center) in price increments of one quarter.
  • a Price parameter 37 can be used to set whether the price is absolute or relative (e.g., pegged to the bid/ask midpoint or to the average price ofthe last match of that security).
  • a Min Size parameter 38 and a Max Size parameter 40 allows the trader to set the minimum and maximum limits for the quantity axis ofthe satisfaction density profile.
  • the CMC 2 could determine the smallest grid resolution used and interpolate all coarser grid resolutions to that resolution.
  • the CMC 2 could specify a minimum resolution (e.g. 100 shares and 1/8 in price) and interpolate all coarser grid resolutions to the specified minimum resolution.
  • a Cursor Position segment 42 will display the coordinates (price, size) of the position ofthe cursor as the cursor is moved by the user over the satisfaction density profile being created.
  • a Cursor Type section 44 has a number of buttons to control the function ofthe cursor, for example, a set button, a more button, a less button, a boundary button, and an edit button. The more and less buttons allow the user to increase or decrease the satisfaction density level on the satisfaction density profile at the location ofthe cursor. In the representative embodiment, the selected satisfaction density value is increased or deceased each time the mouse button is "clicked.”
  • the boundary button allows the user to create a boundary, as discussed above at Fig. 2.
  • the edit button allows the user to edit the boundary.
  • the set button allows the user to set a satisfaction density value, so that each time the mouse is "clicked", the set value is placed in the satisfaction density profile at the location ofthe cursor.
  • a Display section 46 that has two buttons, namely, an Update button and a Display Surface button.
  • the Update Button will redraw the satisfaction density profile.
  • the Display Surface button will allow the user to change the way the satisfaction density profile is displayed, e.g., as a contour plot (as shown in Fig. 2) or a temperature graph (as shown in Fig. 7 below).
  • the interface window 21 can also have a quit button 50, a clear button 52, a reset button 54 and an apply button 56.
  • the quit button 50 enables a user to exit from the program that controls the interface window 21.
  • the clear button 52 clears the display ofthe graph (e.g., the display ofthe satisfaction density profile) and all other parameter values, such as, for example, the Min Size parameter 38 and the Max Size parameter 40.
  • the reset button 54 "undeletes" the most recent change to the graph, resetting the state ofthe graph to the immediately preceding state.
  • the apply button 56 when selected, causes the satisfaction density profile to be submitted for matching.
  • a remove boundary button 59 when selected, will remove all boundaries from the satisfaction density profile.
  • a patterns button 58 allows a user to retrieve pre-defined or user-defined parameterized templates for common types of satisfaction density profiles.
  • a load pattern window 60 (as shown in Fig. 5) will be displayed, that allows the user to select saved patterns.
  • there are two saved patterns namely ibm_seller_l and ibm_buyer_ l, that store patterns that enable a user to quickly load and use satisfaction density profiles to buy and sell IBM stock.
  • Certain common order types can be expressed as parameterized templates that could be selected directly using the Patterns button 58 and the Load Pattern window 60. Once the corresponding template pops up on the display, the user could morph the display to suit the user ' s preferences as described below.
  • Figs. 6A and 6B show a full screen display that includes an interface window 21 and the satisfaction density profile of Fig. 2.
  • the entry of buy/sell profiles can be facilitated by a combination of a user-friendly graphical interface and user-tailorable templates.
  • a user-friendly graphical interface and user-tailorable templates.
  • the GUI would provide a set of tools for quickly entering buy/sell profile "peg point" values at selected price/size grid coordinates, along with an arbitrarily drawn boundary outside of which the profile values would be set to zero at all grid points.
  • the CMC 2 would then calculate a two-dimensional (or multi-dimensional) profile that exactly matches the specified points and interpolates between these values to compute all other grid values.
  • This interpolation can be accomplished by a number of mathematical algorithms, including but not limited to triangular tessellations, spline functions, and surface and/or contour plotting programs.
  • the GUI would also include the ability to "morph" a surface profile created in this manner, using mouse hook-and-drag type operations or other similar methods, so that the profile can be altered by the user as desired to achieve a final configuration.
  • Fig. 7 shows a buy satisfaction density profile displayed as a temperature graph.
  • the user can cause any satisfaction density profile that has been inputted as a contour plot (or other representation) to be displayed in the form of a temperature graph by selecting the Display Surface button.
  • each (price, quantity) coordinate is represented by a colored square (e.g., 80), with the color ofthe square signifying the satisfaction density value.
  • a satisfaction density value of 0 is represented by a black square
  • a satisfaction density value of 1 is represented by a white square
  • a satisfaction density value of 0.1 is represented by a blue square
  • a satisfaction density value of 0.2 is represented by a red square
  • a satisfaction density value of 0.9 is represented by a yellow square, and so on.
  • the trader can view the satisfaction density profile as a meaningful and colorful graphical display.
  • Fig. 8 is a flow chart representing the overall steps performed in accordance with the present invention.
  • Traders enter satisfaction density profiles, as discussed above, at steps 100 and 102. It will be appreciated that many traders can each enter one or more satisfaction density profiles.
  • Fig. 8 shows that the buy and sell profiles are entered at different steps (i.e.. steps 100 and 102); however, the same interface (e.g., interface window 21) and terminals 10. 12, 14 are used for the input of both buy and sell profiles.
  • steps 100 and 102 could conceptually be considered to be the same step, merely with differing data.
  • buy satisfaction density profiles when ready for matching, are transmitted to the CMC 2 and stored in a buy profile database 6 (step 104).
  • Sell satisfaction density profiles when ready for matching, are transmitted to the CMC 2 and stored in a sell profile database 8 (step 106).
  • the CMC 2 calculates, for each possible buy /sell combination stored in the buy profile database 6 and sell profile database 8, a mutual satisfaction function, which, in the representative embodiment, is a mutual satisfaction cross product.
  • the mutual satisfaction cross product represents the potential for that buy/sell pair mutually to satisfy each side.
  • the CMC 2 will calculate six mutual satisfaction cross products, e.g. Al, A2. Bl. B2, CI, C2.
  • the CMC 2 ranks each grid element (possible buy /sell pair at a corresponding price and size) of each mutual satisfaction cross product in order from largest to smallest.
  • the buy /sell pairs are then matched in the ranked order (step 1 12), accumulating the price and size for the buyer and seller of each matched transaction (steps 1 14 and 116).
  • step 1 12 When the size limit for a particular satisfaction density profile is reached, all remaining lower ranked grid elements involving that profile are removed from consideration (steps 122 and 124). If all feasible (i.e.. non-zero mutual satisfaction) crosses have not been done (step 1 18), then control returns to step 112. If all feasible crosses have been completed, then the process is temporarily suspended until the next order is entered or an existing unmatched order is canceled or modified (step 120), upon which control returns to step 108.
  • Fig. 8 can be described more precisely in mathematical notation, as follows. This explanation will begin with a batch process description, and then show how this extends directly to a continuous crossing strategy.
  • B,(p,s) Assume we have M buyers and N sellers in a crossing pool for a given stock. We define B,(p,s) as the "satisfaction density" of the i-th buyer for receiving a portion, s. of his fill at price p, where 0 B(p,s) 1. Along with this profile, the buyer will have a maximum size limit , . Let S ⁇ (p,s) and ⁇ be the corresponding satisfaction density and size limit for the k-th seller. These satisfaction density profiles are two-dimensional surfaces over a grid of price and size coordinates that characterize the participant's degree of satisfaction in the transaction.
  • a value of zero in any coordinate cell indicates no satisfaction (i.e., no desire for any portion ofthe transaction to be accomplished at the corresponding cell price), while a value of unity indicates full satisfaction. In-between values correspond to limited degrees of satisfaction. Mathematically, these values represent "fuzzy " variables that characterize the degree of membership of a particular price/size transaction in the set of satisfying transactions.
  • the satisfaction density of a marketmaker at a given price p might be constant for sizes from zero up to 1.000 shares, and then decline rapidly to zero for larger sizes.
  • the satisfaction density of an agency broker might be non-zero only for sizes up to the client ' s order size.
  • the satisfaction density of an accumulating or divesting investor might exhibit a broad hump in size centered at some large value.
  • This product lies between zero and unity in value, and provides a measure ofthe relative degree to which a given price and size satisfy a particular pair of buyer and seller. There will be MN such mutual satisfaction densities for all participants in the batch.
  • J ik (p,s) min (B,(p,s), S k (p,s) ⁇
  • the optimization problem is: what allocation of amounts and prices
  • the present invention may allow a minimum threshold of mutual satisfaction in the ranking process, below which no allocations are made.
  • the satisfaction density for one stock can be made a function ofthe allocations already made in another stock.
  • each new satisfaction density entered into the crossing network of the present invention is treated as an event that triggers a new round of computation as described above. While the computation requirements to implement this process in real time for all stocks are significant, they are well within the capability of modern supercomputers.
  • Buyer #1 Profile is represented graphically as a contour plot in Fig. 3A.
  • Buyer #2 Profile is represented graphically as a contour plot in Fig. 3D.
  • Seller #1 Profile is represented graphically as a contour plot in Fig. 3C.
  • Seller #2 Profile is represented graphically as a contour plot in Fig. 3B.
  • J12 therefore equals 0.00 0.00 0.00 0.00
  • J21 therefore equals 0.10 0.10 0.10 0.00
  • J22 therefore equals 0.00 0.00 0.00 0.00
  • Jl 1 is represented graphically, as a contour plot, in Fig. 9A.
  • J12 is represented graphically, as a contour plot, in Fig. 9B.
  • J21 is represented graphically, as a contour plot, in Fig. 9C.
  • J22 is represented graphically as a blank contour plot (not illustrated).
  • the present invention can easily handle trades of baskets of securities.
  • the CMC 2 will functionally link related satisfaction density profiles into one. This linking process can be accomplished in its most general form, for example, by matrix manipulation of the two profiles utilizing a connection matrix.
  • additional variables can be included that have an effect on the satisfaction density profile.
  • an eligibility variable or an urgency variable could be set by the trader, as explained below.
  • a trader has a "buy basket” and a “sell basket” whose execution status cannot become too far unbalanced on either side, in dollars or shares or both.
  • the satisfaction density profile of the present invention can be augmented to include two other variables: eligibility and urgency.
  • each of these variables can take on a value between and including zero and one.
  • the eligibility variable has a binary value and the urgency variable has a value between and including zero and one.
  • Both the urgency variable and the eligibility variable can be associated with the satisfaction density profile as a whole (e.g.. one value per variable per profile) or each coordinate ofthe satisfaction density profile (e.g., one value for each (price, size) coordinate.)
  • the eligibility value when associated with each coordinate, represents the degree to which that grid point is eligible for matching.
  • the eligibility variable is a binary variable that is used to track execution status, i.e., all values ofthe eligibility variable are assigned a value of one at order profile entry, and matched values are set to zero upon matching.
  • the eligibility variable could keep track of when matches have occurred.
  • the eligibility of unmatched values could be held to zero pending satisfaction of execution status constraints of other securities (e.g.. as in scenario A. above).
  • the eligibility variable could be used as a coupling between two different stocks.
  • the eligibility variable could be a "fuzzy " variable, having values between and including zero and one. that would allow for " soft” (i.e.. continuous-
  • the urgency variable represents the degree to which a particular grid point satisfaction value should be either (a) translated in the direction of a more aggressive price, or (b) warped to a more aggressive satisfaction value, or both.
  • there is one urgency value per satisfaction density profile i.e., urgency is condensed to a single scalar value for each security, applied uniformly
  • the value ofthe urgency variable ranges from zero to one.
  • the urgency variable would have a value of zero, representing regular trading urgency.
  • Non-zero values ofthe urgency variable would signify the degree of urgency, with one being the most urgent.
  • the following provides a detailed description of an exemplary embodiment ofthe above-described matching system and method, including general protocols associated with preference profiles, and the detailed algorithmic process by which contra profiles are matched.
  • the latter description may include priority rules, matching constraints, and the handling of special cases such as ITS (Intermarket Trading System) trades and short sales.
  • ITS Intermarket Trading System
  • the basic user input to the crossing network is a preference or satisfaction density profile, which expresses the trader's degree of preference (a number between zero and one) to trade at each price/size coordinate in a given cycle. Any coordinate with a non-zero preference value is eligible to be matched one or more times at its corresponding size with one or more contra profiles, at its corresponding price or better, during that cycle, subject to the algorithmic process and constraints to be described below.
  • Fig. 10 depicts an exemplary embodiment of a preference profile 150 (in this case, a buy profile) in the graphical user interface (GUI) used in this exemplary embodiment ofthe present invention.
  • GUI graphical user interface
  • the white region 151 denotes ' 1 ' preference values, while the shaded region (between contour lines 153 and 154) denotes intermediate preference values between '0 * and ' 1 " .
  • the black region 152 indicates zero preference values (i.e., prohibited trades).
  • the actual grid over which preference profiles are defined is quantized in price (vertical axis) by the minimum trading increment in the corresponding security being traded. It is quantized in size (horizontal axis) to 1000 share increments. In the latter case, it is important to note the difference between the quantization of preference (which represents the granularity of expressing trading preference as a function of size) versus the unit of trading size in the system, which may be in round lots (100 shares). Any integer number of round lots can be traded, but the same preference value at a given price applies to each round lot size between, e.g., 1 100 and 2000 shares, or between 7100 and 8000 shares.
  • Every preference profile has an associated maximum quantity of shares (in round lot multiples) to be bought or sold. This quantity must be greater than or equal to 1000 shares, except for profiles that originate from the exchange's specialist's workstations or from the exchange's order book, which may be in any round lot quantity down to 100 shares, or from CQS (Consolidated Quote System) quotes, which may be in any round lot quantity greater than 100 shares. CQS quotes of 100 shares are ignored.
  • satisfaction density profiles are entered via the specification of preference contours, which are adequate to describe any practical preference profile.
  • the user can specify individual preference contours, corresponding to preference values from the set [0.0, 0.1. . . . 1.0]. manually via the GUI, or eventually by computer using an extension ofthe Financial Information Exchange (FIX) standard messaging format.
  • Each contour is specified in terms of its vertices (i.e., end points or bend points in the contour), which correspond to discrete preference coordinates in the specified price and size increments.
  • the profile in Fig. 10 is entirely defined by the two preference contours shown, each of which is specified by only two vertices.
  • contours are expanded into piecewise continuous line segments, each corresponding to a single specified preference value. Every profile must specify a ' 1 ' preference contour, and this * 1 ' contour must be specified over the entire size range of nonzero preference values in the profile. If a profile does not specify a "0 " contour, it will be automatically created by the matching engine. The zero contour will be inserted across all profile sizes at a price that is one tick more aggressive than the most aggressive coordinate specified with a non-zero preference.
  • the full matrix of preference values is constructed from the specified preference contour vertices in two stages.
  • the first stage linearly interpolates between adjacent vertices to create piecewise linear preference contours lying on the grid of price/size coordinates.
  • the corresponding preference value is assigned to the intersecting grid coordinate whose price is closest to the interpolated contour line.
  • This process is performed in decreasing order of contour preference values, so that lower- preference contours that intersect the same grid coordinate as a higher-preference contour overwrite previously assigned preference values.
  • the result is a vertically stacked set of grid coordinates for each size increment whose prices correspond to specified discrete preference values.
  • the second stage linearly interpolates the preference values over price increments lying between the prices corresponding to the discrete preference values assigned in the first stage, assigning floating point preference values to these coordinates.
  • For buy (sell) profiles all coordinates at a given size whose price is below (above) the coordinate assigned a ' 1 ' preference in the first stage are automatically assigned a ' 1 " preference.
  • For buy (sell) profiles all coordinates at a given size whose price is above (below) the minimum specified contour preference value in the first stage are assigned a zero preference value. In this manner, the entire preference matrix for a given profile is specified as a function ofthe preference contours.
  • T preference contour vertices (1000. $126,375). (65000, $125,750) '0' preference contour vertices: (1000. $126,625), (65000. $125,875)
  • the first step is to linearly inte ⁇ olate the prices between the defined contour vertices for each 1000 share size increment, followed by rounding ofthe resultant prices to the nearest price increment.
  • the next step is, for each size increment, to inte ⁇ olate linearly the preference values at each price increment lying between those prices assigned to the corresponding preference contour values in the above tables.
  • This operation fills in the intermediate preference values in the matrix, and for illustration, would result in the following table of inte ⁇ olated preference values for the price increment $126,500:
  • the matching engine may exclude profiles specifying preference contours that are too aggressively priced relative to the National Best Bid or Offer (NBB or NBO) at the time of the call from a match. Since the determination of the NBBO is not made until the start time ofthe match, users are not given an indication of the rejection ofthe profile.
  • NBO National Best Bid or Offer
  • a buy profile specifies any preference contour coordinate greater than 159 price ticks higher than the NBO. the profile is excluded from a match. For a 1/16 price increment, this means that a profile with a preference contour coordinate $10.00 or more above the NBO is excluded. Note that this includes the specification of points on the * 0 ' -preference contour. Similarly, if a sell profile specifies a preference contour coordinate more than 159 ticks lower than the NBB. it is excluded from a match.
  • buy (sell) profiles specifying preference contour coordinates that are much lower (higher) than the NBB (NBO) are also excluded from a match. If a buy profile specifies any preference coordinate more than 799 price ticks below the NBB (i.e.. more than $50.00 below the NBBj it will be rejected. Similarly, if a sell profile specifies a preference coordinate more than 799 price ticks above the NBO (i.e., more than $50.00 above the NBO), it will be rejected. Profiles that are rejected in these tests remain in the system with their original time stamps, so they may participate in future call cycles if the NBB or NBO changes so as to make them eligible for trading.
  • any profile whose maximum quantity is more than 20 times the maximum size of any non-zero preference coordinate in that profile will be excluded from all matches. For example, a profile whose maximum size coordinate is 5,000 shares, but whose maximum quantity is 101,000 shares, will be excluded from all matches.
  • Aggressively priced buy or sell profiles that are not excluded from a match based on the above tests may still be truncated in price if they extend too far from the NBO or NBB, respectively.
  • all non-zero preference coordinates more than 100 price ticks (i.e., $6.25 for a 1/16 price increment) above the NBO are truncated from the profile.
  • all non-zero preference coordinates more than 100 price ticks below the NBB are truncated from the profile.
  • any portion of a buy profile at prices more than 100 price ticks below the NBB is ineligible to trade, as is any portion of a sell profile at prices more than 100 price ticks above the NBO, since there will be no contra side profile coordinates extending beyond these limits.
  • the pegging reference price options available through the system user interface are: National best bid price: National best offer price: midpoint between the national best bid and best offer prices; and National last sale price prior to a system matching cycle.
  • pegging is invoked in the creation or modification of a profile
  • the prices displayed on the vertical axis ofthe profile are shown relative to the selected pegging price variable. All contours in a pegged profile, and their corresponding preference specifications, are updated with respect to the appropriate pegging price at the beginning of each system matching cycle.
  • Pegged profiles always receive a new time stamp at the beginning of each cycle, which puts them lower in time priority than any non-pegged profile. However, the relative time priorities among the subset of pegged profiles are preserved in accordance with their original time stamps, so that earlier submitted pegged profiles have time priority over later submitted ones.
  • the market data is filtered to determine the pegging reference prices in a manner to reduce the likelihood of an unintended outcome from a match.
  • the bids and offers are censored one at a time in reverse chronological order of their update times (i.e., the most recently updated bid/offer is censored first), until the remaining set of bids and offers is not locked or crossed. If the bid and offer from a single exchange are crossed then both quotes will be ignored for that exchange. If there is neither a bid nor offer from the primary exchange the cycle will be cancelled. If a crossed market is detected from different exchanges and the timestamps are equal then the offer will be ignored. If a quote has a size of 100 shares (1 round lot) or less it will be excluded from the cycle. If a quote is not flagged as 'firm' it will be excluded from the cycle. If a quote is flagged as 'fast market' it will be excluded from the cycle. Quotes from the following exchanges will be considered for the cycle: Boston, Chicago, Philadelphia, New York, Amex, Third Market and Cincinnati.
  • the remaining set of bids and offers is then used to calculate the NBBO.
  • a final validation test is performed to eliminate best bid, best offer, or last sale values that have deviated more than a threshold amount from their last reference values. This threshold is proportional to the price and the square root " of time since the last reference value. In the event that all bids are locked or crossed with respect to all offers, the match will not be executed. If either the NBB or the NBO (but not both) is missing or determined to be not valid, the match will be executed, but all pegged profiles except those pegged to the valid bid or offer will be excluded. If the last sale exceeds the threshold from its previous value, all profiles pegged against the last sale will be excluded from the cycle, but the tick direction will be taken "as-is".
  • the NBBO prices resulting from step 1 or step 3 are used as the pegging reference prices for profiles pegged to the best bid or best offer, respectively.
  • the midpoint price is calculated as the average ofthe best bid and best offer reference prices determined in step 3. If the midpoint price corresponds to a legitimate trading increment price, that price is used as the pegging reference price for profiles pegged to the midpoint ofthe national best bid and best offer. If not, buy profiles pegged to the midpoint will use the next lowest trading increment price below the midpoint price as the pegging reference price. Sell profiles pegged to the midpoint will use the next highest trading increment price above the midpoint price as the pegging reference price.
  • the national last sale price if the national last sale price lies on or within the NBBO price range, it is used as the pegging reference price for both buy and sell profiles. If the national last sale price is greater than the best offer price calculated in step 1 or 3, the national best offer price is used as the pegging reference price for buy profiles, and the national last sale value is used as the pegging reference price for sell profiles. If the national last sale price is less than the best bid price calculated in step 1 or 3, the national best bid price is used as the pegging reference price for sell profiles, and the national last sale value is used as the pegging reference price for buy profiles.
  • the above market data filtering algorithm does not correct erroneous market data that may be used to determine pegging reference prices.
  • any individual coordinate of a preference profile is eligible for multiple matches against contra profiles each time a new system matching cycle is performed. There are four basic constraints that limit this eligibility:
  • a coordinate whose size, when added to the cumulative size of potential allocations already made to its profile, would exceed the maximum quantity for the profile is not eligible for further matching.
  • a user may enter an arbitrary number of explicit price or volume controls that restrict the total number of shares that may be allocated from a particular price or size region ofthe preference profile. For example, the user may specify that, notwithstanding the overall shape ofthe preference profile, no more than 100,000 shares may be accumulated at a price of 57 or higher, and no more than 50.000 shares may be accumulated at sizes of 10,000 shares or less.
  • Explicit price and/or size controls are logically ANDed (i.e., each and every control must be satisfied by a prospective allocation), and they are neither reset nor adjusted from one matching cycle to the next. These boundary conditions provide a further degree of user control over the trade allocations that can be made to the profile, throughout its life. Note that pegged profiles are not permitted to have price controls.
  • a user may enter an Intermarket Trading System (ITS) restriction that limits the number of shares (as a percentage ofthe maximum quantity) in his profile that may be matched against the quotes of ITS participants, as described more fully in Section 6.3 below.
  • ITS Intermarket Trading System
  • Implicit price controls For buy (sell) profiles with regions of downward (upward) slope, where the maximum coordinate size with non-zero preference at a particular price is less than the maximum coordinate size with non-zero preference at any price in the profile, the system automatically generates an "implicit price control". This price control limits the number of shares that can be allocated at that price or above (below) in a single match to the size ofthe maximum-size non-zero preference coordinate at that price. Implicit price controls, at each price where they are generated, are automatically reset and/or recomputed at the beginning of each matching cycle. Thus they do not prevent the accumulation of trades at a particular price across multiple matches whose total volume might otherwise be disallowed in a single match. As an illustration, note that in the last table of Sectionl .2.
  • Fig. 11 illustrates the use of explicit price and volume controls in a profile
  • Fig. 12 details the generation of implicit price controls.
  • the explicit volume control limits total volume in trades of 300,000 shares or less to 400,000 shares
  • the explicit price control limits total volume at $39 15/16 and above to 510,000 shares.
  • Fig. 13 shows an example of a buy profile for which no implicit boundaries are generated, notwithstanding the downward slope region over a portion ofthe profile, since the maximum non-zero preference coordinate size at each price equals the maximum non-zero preference coordinate size at any price in the profile.
  • a regular-way limit order specifies a maximum size and a limit price against which one or more fills may be allocated, up to the maximum size and at or better than the limit price.
  • Such orders have "standing" in the sense that no trade is permitted that would trade through the limit price of such an order without first filling the order.
  • the key features of an order with standing are 1 ) it is a held order at the limit price or better; and 2) any portion ofthe order may be filled at the limit price or better.
  • the analogous concept of a preference profile coordinate with standing is defined by the following features: 1) the coordinate must have ' 1 ' preference. 2) the coordinate must lie in a row of contiguous coordinates of ' 1 ' preference at the same price, extending down to the minimum (i.e., leftmost) size increment, all of which are eligible to be matched, and 3) the profile must not have its ITS participation set to less than 100%. Thus if a coordinate has standing, it lies in a region ofthe preference profile that has ' 1 ' preference values for all coordinate sizes from the minimum preference increment (i.e., 1000 shares) up to and including the coordinate's size, at its corresponding price.
  • Fig. 14 illustrates the concept of standing.
  • no match is permitted that would trade through the price of a coordinate with standing, as described more fully below.
  • No coordinate has standing in any profile that inco ⁇ orates an (explicit) size boundary condition.
  • coordinates that otherwise would have standing may be traded through if the profile has failed to make a prospective trade at an earlier point in a given cycle as a result of its ITS restriction. Otherwise, these coordinates are treated as though they possess full standing.
  • Each limit order and specialist quote residing in the host exchange computer system at the time of a match is converted to a limit profile with Book class.
  • Each profile submitted via the system GUI must be identified by the user as either an Agency or Principal profile. The end user is responsible for properly identifying profiles as Agency or Principal.
  • the account type identification of electronically submitted limit orders to the system via the FIX protocol is specified using the Account Identification Codes (AIC) published by the New York Stock Exchange (NYSE).
  • AIC Account Identification Codes
  • NYSE New York Stock Exchange
  • Each profile created by the system from such orders is designated as either an Agency or Principal profile, in accordance with the following classification table: ⁇ t ⁇ iRVfmarw_MirBg waar(_iirwH_iM
  • AIC codes have no other impact on the system matching algorithm. Specifically:
  • the host exchange is the Pacific Exchange (PCX) which does not change its order processing when the NYSE invokes sidecar processing rules
  • PCX Pacific Exchange
  • the system does not change its processing of program trading order AIC codes (D, C, M, N, J, K, U, Y) when sidecars are triggered on the NYSE.
  • the system will comply with any changes to these rules if and when the PCX modifies its rules.
  • CQS profiles are created from the quotes of other market participants in the Intermarket Trading System (ITS) at the time of a match, provided that the size of such quotes exceeds 100 shares and the quote has not produced a locked or crossed market. In either of the latter cases, no CQS profile is created for the corresponding quote.
  • CQS profiles are analogous to regular limit orders, and thus possess standing.
  • the system prioritizes Book over Agency profiles, Agency over Principal profiles, and Principal over CQS profiles.
  • CQS profiles are canceled automatically at the end ofthe cycle in which they participate, since new CQS profiles are created at the beginning ofthe next cycle.
  • the system supports the following profile type eligibility conditions:
  • Fill or kill an all or none profile that is automatically cancelled after the next match, if it has not been filled.
  • Fill or kill profiles have the same restrictions regarding ITS participation as described above for all or none profiles.
  • Immediate or cancel a profile that is automatically cancelled after the next match, regardless of its leaves quantity.
  • Profiles marked as short sales are subject to intra-match cycle eligibility restrictions, as explained in detail below.
  • preference values of ' 1 ' are inte ⁇ reted as "non-discretionary", analogous to a held order at the corresponding price and size.
  • the matching of contra sides where both parties have a preference of ' 1 ' is analogous to the matching of held orders that occurs in existing markets.
  • the system uses matching rules consistent with the rules of priority used in existing markets.
  • This first stage of matching is denoted as “aggregation” in the system, since it permits multiple coordinates on one side ofthe market to be matched against a single coordinate on the contra side. Under a "crossed market” condition, as described hereinbelow, the aggregation stage matches multiple buyers and sellers at a clearing price.
  • Preference values of less than ' 1 ' (and greater than zero) are inte ⁇ reted as giving the system the corresponding degree of discretion in finding contra side matches.
  • the matching of contra sides where one or both parties have less than ' 1 ' (but greater than zero) preference is analogous to one-on-one manual negotiations that have no particular rules of priority, which occur in existing market structures. In these cases, the system uses mutual preference (with values less than ' 1 ', but greater than zero) as the primary determinant of trading priority. This second stage of matching is denoted as "negotiation" in the system, since it negotiates trades between contra pairs at individual price and size values. Where a prospective match based on partial preference would trade through coordinates with ' 1 ' preference that have standing, or trade at the price of such coordinates that have class or time priority, or violate the short sale rule (as described below), this match is blocked.
  • Time of entry Among coordinates that have equal price, standing and class status, the time of entry ofthe associated profile determines relative priority, with earlier time of entry having higher priority. Each profile has a unique time of entry assigned upon its receipt by the system, so there are no ties among profiles in this category. 5. Size. Among coordinates of a given price within the same profile, priority for matching is determined by size, with larger sizes having higher priority.
  • the matching algorithm never permits a match that would cause a trade through of any coordinate with standing. Furthermore, no match is permitted at the price of a coordinate with standing, if the latter coordinate has standing or class priority according to the above rules, with the following exceptions:
  • price priority overrules class priority, permitting more aggressively priced profiles with standing to trade at the price of less aggressively priced profiles that have class or time priority.
  • the matching algorithm never permits a match that would result in the violation of any price or size control (implicit or explicit) associated with any profile involved in a match.
  • Pegged profiles which the user designates to be adjusted with reference to the current market at the beginning of each match cycle) may not contain explicit price controls. All price and/or size control limits affecting a particular coordinate must be satisfied in order for the coordinate to participate in a trade.
  • a profile with one or more size controls has no coordinates with standing, at any size or price.
  • implicit price controls at each price where they are generated, are automatically reset and/or recomputed at the beginning of each matching cycle. Thus they do not prevent the accumulation of trade volumes at a particular price across multiple matches that otherwise might be disallowed in a single match. Users must employ explicit price controls to prevent this occurrence.
  • every profile submitted through the system GUI designates the portion ofthe maximum quantity associated with the profile that is eligible for matching against CQS profiles.
  • the system GUI default setting for ITS eligibility is 0% for all or none and fill or kill profile types, and is 100% for all other profile types.
  • CQS profiles are always included in system matches, but have lower class priority than any other profile type in the system. Matches involving a CQS profile carry an implicit risk of not executing the trade, since the ITS commitment sent to another market may be only partially filled, or may expire or be declined. Users who elect to limit the eligibility of their profile for ITS trades may lose some trading opportunities and/or some degree of standing protection in the system, since all CQS profile coordinates have standing, and thus trading through these coordinates is forbidden.
  • profile coordinates that possess standing, but have declined any portion of a trade due to ITS limits are not permitted to block other trades as a result of their standing. This may potentially result in a trade-through of these coordinates. Notwithstanding these considerations, the system and method does not permit a match that would result in a violation ofthe ITS eligibility limits for any profile.
  • ITS trading limits specify the percentage ofthe total original profile volume (not the remaining "leaves" quantity) that is eligible for matching against CQS profiles in each match.
  • the volume associated with this commitment is subtracted from the ITS eligible volume in the current match.
  • there is no possibility of exceeding the profile's ITS exposure limit For example, a profile submitted with the maximum quantity specified as 100.000 shares, and the ITS eligibility specified as 10%, normally is permitted to match up to 10.000 shares against CQS profiles in aggregate in each match cycle.
  • the national last sale and tick is used to initialize the eligibility of short sell profile coordinates.
  • the internal last sale and tick is used to update the eligibility of short sell profile coordinates. No allocation involving a short sell coordinate is allowed at a price less than the internal last sale (on a plus or zero-plus internal tick) or at a price less than one price increment above the internal last sale (on a minus or zero-minus internal tick).
  • Short sell coordinates that lose their eligibility at any stage internal to a match cycle receive a new effective time stamp upon restoration of their eligibility within that cycle, which results in a loss of their original time of entry priority for the balance of that matching cycle.
  • the profile's original time of entry is used to prioritize short sell coordinates at the same price that have been disabled during a cycle, and also is used at the start ofthe next cycle to determine time of entry priority for that cycle.
  • the matching system and method ofthe subject invention does not permit a match between two CQS profiles.
  • each kernel represents a single-price row of contiguous coordinates in the profile, having ' 1 ' preference values.
  • each kernel is parameterized by the minimum and maximum number of shares spanned by the row of ' 1 ' coordinates.
  • kernels are generated at every price increment lying in the range of price overlap with contra-side profiles.
  • a single buy kernel list and a single sell kernel list are constructed from the kernels of all profiles, via a sequence of nested sorts of each list in strict order of price, standing, class and time of entry priority, as described above. (Note that the size sort on coordinates mentioned hereinabove is implicit in the kernel structure, given that kernels always seek to fill their maximum size, but no less than their minimum size.)
  • normal aggregation is one-sided, in the sense that a single kernel on one side ofthe market aggregates potentially multiple kernels from the opposite side.
  • multiple kernels with standing on each side of the market overlap in price, in which case one-sided aggregation is blocked by the standing constraints.
  • two-sided aggregation is used (as described hereinbelow) to clear these overlaps before resuming with one-sided aggregation.
  • An earlier entered (non-CQS profile) kernel at the top of either the buy or sell kernel list is selected as the initial "aggregation attractor" kernel.
  • the matching algorithm attempts to aggregate volume from kernels on the contra list, in strict order of priority on that list, in order to match the aggregation attractor' s size and price.
  • the matching algorithm proceeds through the contra list in priority order in its attempt to allocate contra parties to the aggregation attractor. Kernels without standing in this contra list may be skipped over if their minimum and maximum size limits are incompatible with the size limits ofthe aggregation attractor kernel.
  • the potential trade price is set initially to the aggregation attractor's price, and the aggregate contra list is examined to see whether sufficient contra volume exists to satisfy at least the minimum volume demanded by the price ofthe aggregation attractor kernel.
  • the aggregation process always seeks the maximum volume available for the attractor kernel, and is repeated for that kernel if the profile maximum volume is larger than the aggregator kernel maximum volume, so long as none of the other profile constraints is violated.
  • the attractor kernel is skipped over, and the next-highest priority kernel is selected from either the buy or sell list. Also, if the resulting set of trades fills kernels with lower class priority (excluding CQS kernels) without completely filling all kernels with higher class priority and standing at that price, the attractor kernel is skipped over. This process continues until a price is determined at which the aggregation attractor can attract adequate volume from the contra list without trading through any contra kernels with standing, or trading at the price of higher class priority contra kernels with standing.
  • This price is then checked to see if it trades through the price of any kernel with standing on the attractor ' s side. If it does, the prospective aggregation trades are disallowed. If the unsuccessful aggregation attractor kernel has standing, the choice ofthe next aggregation kernel is restricted to the contra list. If an aggregation attractor kernel with standing cannot make an otherwise permissible trade due to its ITS participation being restricted, it may be traded through in subsequent trades of a given cycle, in order to prevent it from blocking other trades.
  • the matching algorithm seeks to improve the trade price for the aggregation attractor by one price increment, and recalculates the available trade volume. This price improvement process repeats until the improved price results in a decrease in the available volume to trade. However, price improvement for the aggregation attractor is halted if the resulting price would trade through the price of any coordinate with standing on its side ofthe market or trade through any coordinate that is willing to do the identical trade (i.e., same price and size), regardless of whether the latter coordinate has standing or not.
  • the attractor's price also may not trade at (if the aggregation attractor has standing but does not have class priority, or if the aggregation attractor does not have standing) the price of any kernel possessing standing from another profile on the aggregation attractor's side ofthe market, unless the latter is a CQS profile.
  • the matching algorithm selects the next aggregation attractor only from the contra list, and attempts aggregation. If the same situation arises in which a contra aggregation attractor with standing is blocked from trading by a kernel on its side ofthe market, then one-sided aggregation is blocked on both sides, and we proceed to the two sided aggregation stage described in the next section.
  • the aggregation process continues until no further aggregations are possible.
  • the matching algorithm then proceeds into the negotiation stage, described in detail hereinbelow.
  • the pu ⁇ ose of this stage of the matching algorithm is to clear multiple overlapping kernels with standing that block one-sided aggregation.
  • This stage operates in somewhat analogous fashion to a single-price call, but with greater generality, since all kernels with standing (even if they are derived from profiles that do not correspond to standard limit orders) are included in two-sided aggregation.
  • supply and demand schedules as a function of price, representing all trading interest with standing, are assembled.
  • the price that matches the most volume is selected, and the co ⁇ esponding trades are executed. If there are multiple prices that clear the same maximum volume, the highest price is selected if there exists a buyer su ⁇ lus, and the lowest price is selected if there exists a seller su ⁇ lus. If there is an exact match of buyer/seller volume over a range of prices, the middle price is selected if there are an odd number of tied prices with no su ⁇ lus. If there is an even number of tied prices with no su ⁇ lus, then ofthe two middle prices, the one is selected that is closer to the last sale price recorded by the system. This is the national last sale if this occurs at the beginning of a match cycle, or the last committed trade price in the middle of a cycle.
  • the priority order for trading is as follows: Price; Class; and Time of Entry.
  • two-sided aggregation price has strict priority over class.
  • a kernel with lower class priority may trade at the price of a kernel with higher class priority without completely filling the latter, if the former kernel is from a profile with more aggressively priced kernels than the latter.
  • the net effect of two-sided aggregation is to clear any overlapping active contra kernels with standing, so that one-sided aggregation can resume.
  • the negotiation stage begins by calculating mutual preference profiles between all pairs of buy and sell preference profiles.
  • the non-zero mutual preference coordinates from all mutual preference profiles are then entered into a single list that is rank ordered in descending order of priority as described hereinabove.
  • Prospective matches are assembled sequentially from the top of this list.
  • the matching algorithm ensures that none ofthe profile constraints of described above would be violated as a result of making the co ⁇ esponding allocation to either party.
  • the prospective match would:
  • negotiation coordinate list is re-sorted to inco ⁇ orate the changed eligibility and time stamps of these reactivated short sell coordinates, and is then rescanned from the top to continue trading. This revisits negotiation coordinates that previously may have been skipped over because they were blocked or ineligible to trade.
  • the negotiation stage terminates when no non-zero mutual preference coordinates remain on the list, i.e., there is no remaining overlap of trading desire between any buyer and seller.
  • Fig. 15 there is illustrated a schematic flow chart illustrating the overall system and method ofthe subject invention.
  • market data is received into the system to facilitate, for example, the determination of pegging reference prices for trades.
  • the CMC reads the preference profiles and generates the kernel lists on either side ofthe market.
  • the aggregation stage is conducted, which results in the execution of trades and the cancellation of filled buy/sell orders.
  • the negotiation stage is then conducted at step 230, whereupon trades are constructed based upon partial mutual preference, resulting in the cancellation of additional filled buy/sell orders and the execution of additional trades.
  • the method terminates.
  • Fig. 16 there is illustrated a schematic flow chart ofthe aggregation stage ofthe matching algorithm shown in Fig. 15.
  • the buy kernel lists and sell kernel lists constructed from the profiles on either side of the market are sorted in strict order of price, standing class and time of entry.
  • flags are initialized for each kernel so as to designate the profile characteristics associated therewith.
  • Step 320 represents a loop return point for the aggregation algorithm which is revisited until such time as the aggregation stage is completed.
  • the system determines whether any profiles have been cancelled. At such a time, the system looks to a prioritized queue to seek out client initiated profile cancellations. If the inquiry at step 330 is positive, kernels from any cancelled profile on either side ofthe market are removed from the contra side kernel lists at step 340. If the inquiry is negative, the
  • E 26 system proceeds to step 350, whereupon a determination is made as to whether there is a crossed market condition, i.e., if one-sided aggregation is blocked on both sides ofthe market.
  • step 360 the system performs a two-sided aggregation at step 360 to clear multiple overlapping kernels with standing that would block one-sided aggregation.
  • the trades resulting from the two-sided aggregation are executed at step 370, and the system returns to step 320 to begin the cancelled kernel removal subroutine at steps 330 and 340.
  • step 380 the system proceeds to step 380. whereupon a determination is made as to whether there are any kernels available for aggregation. If the inquiry is positive, the system constructs valid trades at step 390 until a profile constraint is violated. In conjunction with step 390, valid trades are committed at step 400.
  • inactive kernels may still have some remaining volume associated therewith, to the extent that a complete aggregation of contra side volume was not achieved.
  • the algorithm return to step 320 to perform the called kernel removal subroutine.
  • the aggregation stage ofthe subject matching algorithm will terminate at step 420 when it is determined that there are no kernels available for aggregation at step 380.
  • Fig. 17 there is illustrated a schematic flow chart depicting the negotiation stage ofthe subject matching algorithm identified at step 230 of Fig. 15.
  • the negotiation stage follows the aggregation stage as shown at step 500.
  • the system constructs a cross list of non-zero mutual preference coordinates by calculating mutual preference between all pairs of buy and sell profiles.
  • the list is sorted and ranked in descending order of priority by mutual preference, standing, class, time of entry, size and price.
  • the system then proceeds to step 530 whereupon, for each cross list entry, the following subroutine commences.
  • step 540 while the buyer and seller for each entry on the cross list have volume available, the system proceeds to step 550. Thereupon, a decision is made as to whether a trade should be allowed or blocked due to standing constraints. If the inquiry at step 550 is positive, the subroutine proceeds to step 560 whereupon a trade between the buyer and seller is committed. Thereafter, at step 570, the volumes are deceremented and appropriate flags are initialized with respect to the traded coordinates. The system then proceeds to step 580. At step 580 the negotiation stage can terminate, proceed to the next cross list entry at step 590 or return to step 540. Upon proceeding to step 590. the algorithm will return to step 530 to run through the trading subroutine. Returning to the decision at step 550.
  • step 590 the system proceeds directly to step 590 to evaluate the next cross list entry.
  • the negotiation stage terminates when there are no non-zero mutual preference coordinates remaining on the cross list. This indicates that there is an absence of overlap of trading desire between any paired buyer or seller.
  • Prints are disseminated to the host exchange in the sequence they are generated by the matching engine. Trades are aggregated into a single print until a break in seller profile or price occurs, but do not include any ITS commitment trade results (if accepted, these trades are reported by the away market).
  • exchange specialists are provided with an system electronic interface at their posts, which allows them to designate any regular limit or all-or-none limit orders in their book for inclusion in system matching cycles. Any regular limit book orders not designated by the specialist for the system are protected by the specialist at the best price of any resulting system trades.
  • ITS commitments resulting from aggregation trades are priced according to the ITS block rule. If the host exchange's portion of an aggregation trade is for 10.000 shares or more, or if the trade value exceeds $200,000, the ITS commitment is sent at the aggregation price computed by the system. If the host exchange ' s portion ofthe trade does not exceed either of these limits, then the ITS commitment is sent at the quote price. In any event, the price of an ITS commitment does not impact trade through restrictions in the system, since resulting trades are printed on the away exchange.
  • RCI Regional Computer Interface
  • the specialist on the away exchange has up to one minute to send a confirmation message for the ITS commitment generated by the system.
  • the fills associated with this commitment are marked as 'pending' by the system until an ITS response is received.
  • the confirmation may specify a lower quantity fill than the original commitment amount or, potentially, a better price. If the confirmation does not match the original commitment terms, the corresponding fill price and size sent to the user is adjusted.
  • the system maintains an ITS preference file that determines the priority with which ITS commitments to trade at a given price are routed to the different away exchanges.

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  • Finance (AREA)
  • Engineering & Computer Science (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Technology Law (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
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  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

L'invention concerne un réseau croisé adaptant des ordres d'achat et de vente basés sur des profils en matière de satisfaction et de quantités. Le réseau croisé comprend une pluralité de terminaux de transaction pouvant être utilisés pour l'introduction d'ordres. Les ordres sont introduits sous forme d'un profil de densité de satisfaction représentant un degré de satisfaction pour négocier un produit particulier à des combinaisons variées (prix et quantités). Les terminaux de transaction sont couplés à un ordinateur contrôleur d'adaptation. Ce dernier peut recevoir en entrée, les profils de densité de satisfaction introduits dans chacun des terminaux de transaction. L'ordinateur contrôleur d'adaptation adapte des ordres (représentés par profil de densité de satisfaction de chaque détaillant), de sorte que chaque détaillant est assuré que le résultat global du processus (en terme de prix moyens et importance de réponse aux besoins) a maximalisé la satisfaction mutuelle de tous les détaillants. Spécifiquement, le processus d'adaptation est anonyme et confidentiel. Le processus d'adaptation peut être réalisé en continu ou traité par lots.
PCT/US1999/025369 1998-10-30 1999-10-29 Reseau croise et procede y relatif WO2000026834A2 (fr)

Priority Applications (3)

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EP99971554A EP1131764A2 (fr) 1998-10-30 1999-10-29 Reseau croise et procede y relatif
AU14558/00A AU1455800A (en) 1998-10-30 1999-10-29 Crossing network and method
GBGB0428305.7A GB0428305D0 (en) 1998-10-30 2004-12-24 Crossing network and method

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US10626898P 1998-10-30 1998-10-30
US60/106,268 1998-10-30

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GB2352849A (en) * 1999-03-15 2001-02-07 Gary Renner Virtual marketplace
GB2366637A (en) * 2000-01-27 2002-03-13 Chabris Gloriana Marks De Computer based order matching system
GB2406923A (en) * 2003-10-09 2005-04-13 Duvacy Ltd Computer implemented trading system
US6882985B1 (en) 1999-04-08 2005-04-19 Alan F. Kay Marketplace system fees enhancing market share and participation
US7644031B2 (en) 2005-08-04 2010-01-05 Bgc Partners, Inc. System and method for replenishing quantities of trading orders
US7711627B2 (en) * 2002-01-07 2010-05-04 Bgc Partners, Inc. Methods and systems for providing crossing markets
US7720744B2 (en) 2000-12-07 2010-05-18 Bgc Partners, Inc. Systems and methods for shifting bids and offers in a trading interface
US7835987B2 (en) 2004-01-29 2010-11-16 Bgc Partners, Inc. System and method for routing a trading order according to price
US8311931B2 (en) 2008-04-21 2012-11-13 Bgc Partners, Inc. System and method for managing trading orders with decaying reserves
US8335734B1 (en) 2009-07-20 2012-12-18 The Vanguard Group, Inc. Method of administering an investment company having a class of crossing shares
US8346642B2 (en) 2008-04-21 2013-01-01 Bgc Partners, Inc. Trading orders with decaying reserves
US8494951B2 (en) 2005-08-05 2013-07-23 Bgc Partners, Inc. Matching of trading orders based on priority
US8738498B2 (en) 2004-01-29 2014-05-27 Bgc Partners, Inc. System and method for routing a trading order
US10304097B2 (en) 2004-01-29 2019-05-28 Bgc Partners, Inc. System and method for controlling the disclosure of a trading order
US10395310B2 (en) 2005-08-04 2019-08-27 Bgc Partners, Inc. System and method for apportioning trading orders based on size of displayed quantities
US10817938B2 (en) 2005-06-07 2020-10-27 Bgc Partners, Inc. Systems and methods for routing trading orders
US11010834B2 (en) 2006-04-04 2021-05-18 Bgc Partners, Inc. System and method for optimizing execution of trading orders
US11017410B2 (en) 2006-12-30 2021-05-25 Cfph, Llc Methods and systems for managing and trading using a shared order book as internal exchange
US11157999B2 (en) 2002-06-05 2021-10-26 Nasdaq, Inc. Distributed data processing
US20210383474A1 (en) * 2019-03-07 2021-12-09 Fujitsu Limited Computer-readable recording medium storing trading program, trading method and trading device
US11288745B2 (en) 2008-04-21 2022-03-29 Bgc Partners, Inc. Trading orders with decaying reserves
US11295383B2 (en) 2012-04-16 2022-04-05 Nasdaq Technology Ab Methods, apparatus, and systems for processing data transactions

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Publication number Priority date Publication date Assignee Title
GB2352849A (en) * 1999-03-15 2001-02-07 Gary Renner Virtual marketplace
US6882985B1 (en) 1999-04-08 2005-04-19 Alan F. Kay Marketplace system fees enhancing market share and participation
US8108294B2 (en) 2000-01-27 2012-01-31 Intellectual Ventures Fund 67 Llc Order matching system
GB2366637A (en) * 2000-01-27 2002-03-13 Chabris Gloriana Marks De Computer based order matching system
US7110975B2 (en) 2000-01-27 2006-09-19 Marks De Chabris Gloriana Order matching system
US7720744B2 (en) 2000-12-07 2010-05-18 Bgc Partners, Inc. Systems and methods for shifting bids and offers in a trading interface
US7711627B2 (en) * 2002-01-07 2010-05-04 Bgc Partners, Inc. Methods and systems for providing crossing markets
US11157999B2 (en) 2002-06-05 2021-10-26 Nasdaq, Inc. Distributed data processing
GB2406923A (en) * 2003-10-09 2005-04-13 Duvacy Ltd Computer implemented trading system
US10304097B2 (en) 2004-01-29 2019-05-28 Bgc Partners, Inc. System and method for controlling the disclosure of a trading order
US8738498B2 (en) 2004-01-29 2014-05-27 Bgc Partners, Inc. System and method for routing a trading order
US11244365B2 (en) 2004-01-29 2022-02-08 Bgc Partners, Inc. System and method for controlling the disclosure of a trading order
US7835987B2 (en) 2004-01-29 2010-11-16 Bgc Partners, Inc. System and method for routing a trading order according to price
US11625777B2 (en) 2005-06-07 2023-04-11 Bgc Partners, Inc. System and method for routing a trading order based upon quantity
US10817938B2 (en) 2005-06-07 2020-10-27 Bgc Partners, Inc. Systems and methods for routing trading orders
US10395310B2 (en) 2005-08-04 2019-08-27 Bgc Partners, Inc. System and method for apportioning trading orders based on size of displayed quantities
US11094004B2 (en) 2005-08-04 2021-08-17 Espeed, Inc. System and method for apportioning trading orders based on size of displayed quantities
US8706605B2 (en) 2005-08-04 2014-04-22 Bgc Partners, Inc. System and method for replenishing quantities of trading orders
US7644031B2 (en) 2005-08-04 2010-01-05 Bgc Partners, Inc. System and method for replenishing quantities of trading orders
US10424015B2 (en) 2005-08-05 2019-09-24 Bgc Partners, Inc. Managing trading orders based on priority
US11030693B2 (en) 2005-08-05 2021-06-08 Bgc Partners, Inc. System and method for matching trading orders based on priority
US8494951B2 (en) 2005-08-05 2013-07-23 Bgc Partners, Inc. Matching of trading orders based on priority
US11010834B2 (en) 2006-04-04 2021-05-18 Bgc Partners, Inc. System and method for optimizing execution of trading orders
US11017410B2 (en) 2006-12-30 2021-05-25 Cfph, Llc Methods and systems for managing and trading using a shared order book as internal exchange
US8732053B2 (en) 2008-04-21 2014-05-20 Bgc Partners, Inc. Trading orders with decaying reserves
US10713724B2 (en) 2008-04-21 2020-07-14 Bgc Partners, Inc. Trading orders with decaying reserves
US10453132B2 (en) 2008-04-21 2019-10-22 Bgc Partners, Inc. Trading orders with decaying reserves
US8311931B2 (en) 2008-04-21 2012-11-13 Bgc Partners, Inc. System and method for managing trading orders with decaying reserves
US8543491B2 (en) 2008-04-21 2013-09-24 Bgc Partners, Inc. System and method for managing trading orders with decaying reserves
US8346642B2 (en) 2008-04-21 2013-01-01 Bgc Partners, Inc. Trading orders with decaying reserves
US11288745B2 (en) 2008-04-21 2022-03-29 Bgc Partners, Inc. Trading orders with decaying reserves
US8335734B1 (en) 2009-07-20 2012-12-18 The Vanguard Group, Inc. Method of administering an investment company having a class of crossing shares
US11295383B2 (en) 2012-04-16 2022-04-05 Nasdaq Technology Ab Methods, apparatus, and systems for processing data transactions
US11908013B2 (en) 2012-04-16 2024-02-20 Nasdaq Technology Ab Methods, apparatus, and systems for processing data transactions
US20210383474A1 (en) * 2019-03-07 2021-12-09 Fujitsu Limited Computer-readable recording medium storing trading program, trading method and trading device
US11748809B2 (en) * 2019-03-07 2023-09-05 Fujitsu Limited Computer-readable recording medium storing trading program, trading method and trading device

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WO2000026834A3 (fr) 2000-09-08
AU1455800A (en) 2000-05-22
TW495691B (en) 2002-07-21
GB0428305D0 (en) 2005-01-26
EP1131764A2 (fr) 2001-09-12

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