Derivatives trading methods that use a variable order price

Information

  • Patent Grant
  • 9911157
  • Patent Number
    9,911,157
  • Date Filed
    Thursday, July 2, 2009
    15 years ago
  • Date Issued
    Tuesday, March 6, 2018
    6 years ago
Abstract
Methods and systems for an exchange to handle variable derivative product order prices are disclosed. The price of a derivative product order (bid or offer) is updated based on changes in the price of a related underlying product. Price determination variable(s), such as delta and gamma, are used to determine the price of the order. The exchange may periodically recalculate the price without requiring the trader to transmit additional information to the exchange.
Description
FIELD OF THE INVENTION

The present invention relates to derivative product trading methods and systems and, in particular, to methods and systems that utilize a variable defined order price.


DESCRIPTION OF THE RELATED ART

Computer systems and networks are increasingly being used to trade securities and derivatives. Computer systems and networks provide several advantages when compared to manual methods of trading. Such advantages include increased accuracy, reduced labor costs and the ability to quickly disseminate market information.


Options are frequently traded via computer systems and methods. An option may be used to hedge risks by allowing parties to agree on a price for a purchase or sale of another instrument that will take place at a later time. One type of option is a call option. A call option gives the purchaser of the option the right, but not the obligation, to buy a particular asset either at or before a specified later time at a guaranteed price. The guaranteed price is sometimes referred to as the strike or exercise price. Another type of option is a put option. A put option gives the purchaser of the option the right, but not the obligation, to sell a particular asset at a later time at the strike price. In either instance, the seller of the call or put option can be obligated to perform the associated transactions if the purchaser chooses to exercise its option or upon the expiration of the option.


Traders typically use theoretical models to determine the prices at which they will offer to buy and sell options. The theoretical option pricing models often produce values that reflect an option's sensitivity to changes in predefined variables. These predefined variables are assigned Greek letters, such as delta, gamma, theta and kappa. Kappa is sometimes referred to as vega or tau. Delta is a measure of the rate of change in a derivative's theoretical value for a one-unit change in the price of the option's underlying contract. Thus, delta is the theoretical amount by which the derivative price can be expected to change for a change in the price of the underlying contract. As such, delta provides a local measure of the equivalent position risk of an option position with respect to a position in the underlying contract. A “50 Delta” option should change its price 50/100, or ½ a point, for a one point move in its underlying contract.


Gamma is a measure of the rate of change in an option's delta for a one-unit change in the price of the underlying contract. Gamma expresses how much the option's delta should theoretically change for a one-unit change in the price of the underlying contract. Theta is a measure of the rate of change in an option's theoretical value for a one-unit change in time to the option's expiration date. Vega is a measure of the rate of change in an option's theoretical value for a one-unit change in the volatility of the underlying contract. Delta, gamma, and vega are the primary measures used by those who trade in options.


A single option order typically identifies the underlying security, the expiration month, whether the option is a call or a put, the strike price and all other standard order terms (e.g. buy/sell, quantity, account number etc.). Each time the price of the underlying contract changes or one of the variables in the trader's theoretical model changes, a trader may cancel all of the relevant pending orders, recalculate new order prices and transmit new order prices to the exchange. It is not uncommon for the price of an underlying contract to change multiple times per second. In addition to receiving a large volume of order traffic, options exchange computer systems transmit current market data to traders. One skilled in the art will appreciate that the amount of data sent to and from an options exchange computer system can be a significant challenge for the computer system and can limit the scalability of the computer system. In addition, there is a similar challenge to manage the bandwidth usage between the option's exchange computer system and network connecting the end user given the high volume of associated market data updates.


Therefore, there is a need in the art for improved derivative product trading methods and systems that better manage the amount of information that must be exchanged between traders and an exchange computer system.


SUMMARY OF THE INVENTION

The present invention overcomes the problems and limitations of the prior art by providing methods and systems that utilize a variable derivative product order price. Derivative products include options on futures contracts, futures contacts that are functions of other futures contracts, or other financial instruments that have their price related to or derived from an underlying product. The variable derivative product order price may be in the form of a model used to price options. When one of the variables of the model changes, an exchange computer system may recalculate the derivative product's price without requiring the trader to transmit additional or different information to the computer system.


In one embodiment, a method of trading variable derivative product orders at an exchange is provided. The method includes receiving from traders a plurality of derivative product orders. Each of the orders has a price that is a function of a predetermined formula, at least one underlying product and price determination variable values supplied by the trader. Bid and offer prices are calculated by applying the price determination variable values and underlying product values to the predetermined formula. Trades are executed based on matching bids and offers.


In another embodiment, a method of determining variable derivative product order prices is provided. A plurality of variable derivative product order prices that are each a function of at least one value of an underlying product are received from an exchange. Values of the underlying products are also received from the exchange. The variable derivative product order prices are determined from the received information.


In yet another embodiment of the invention, a method of distributing variable derivative product order information is provided. Variable derivative product order prices that are a function of at least one value of at least one underlying product are received from a first plurality of users. The variable derivative product order prices and the at least one value of the at least one underlying product are transmitted to a second plurality of users


In other embodiments, the present invention can be partially or wholly implemented on a computer-readable medium, for example, by storing computer-executable instructions or modules, or by utilizing computer-readable data structures.


Of course, the methods and systems of the above-referenced embodiments may also include other additional elements, steps, computer-executable instructions, or computer-readable data structures. In this regard, other embodiments are disclosed and claimed herein as well.


The details of these and other embodiments of the present invention are set forth in the accompanying drawings and the description below. Other features and advantages of the invention will be apparent from the description and drawings, and from the claims.





BRIEF DESCRIPTION OF THE DRAWINGS

The present invention may take physical form in certain parts and steps, embodiments of which will be described in detail in the following description and illustrated in the accompanying drawings that form a part hereof, wherein:



FIG. 1 shows a computer network system that may be used to implement aspects of the present invention;



FIG. 2 illustrates a system in which traders exchange information with a match system, in accordance with an embodiment of the invention;



FIG. 3 illustrates a variable derivative product order in accordance with an embodiment of the invention;



FIG. 4 illustrates a computer implemented method of trading a derivative product contract that involves the use of a variable order price, in accordance with an embodiment of the invention; and



FIG. 5 illustrates a method of processing variable derivative product orders by an exchange computer in accordance with an embodiment of the invention.





DETAILED DESCRIPTION OF THE INVENTION

Aspects of the present invention are preferably implemented with computer devices and computer networks that allow users to exchange trading information. An exemplary trading network environment for implementing trading systems and methods is shown in FIG. 1. An exchange computer system 100 receives orders and transmits market data related to orders and trades to users. Exchange computer system 100 may be implemented with one or more mainframe, desktop or other computers. A user database 102 includes information identifying traders and other users of exchange computer system 100. Data may include user names and passwords potentially with other information to identify users uniquely or collectively. An account data module 104 may process account information that may be used during trades. A match engine module 106 is included to match bid and offer prices. Match engine module 106 may be implemented with software that executes one or more algorithms for matching bids and offers. A trade database 108 may be included to store information identifying trades and descriptions of trades. In particular, a trade database may store information identifying the time that a trade took place and the contract price. An order book module 110 may be included to compute or otherwise determine current bid and offer prices. A market data module 112 may be included to collect market data and prepare the data for transmission to users. A risk management module 134 may be included to compute and determine a user's risk utilization in relation to the user's defined risk thresholds. An order processing module 136 may be included to decompose delta based and bulk order types for processing by order book module 110 and match engine module 106.)


The trading network environment shown in FIG. 1 includes computer devices 114, 116, 118, 120 and 122. Each computer device includes a central processor that controls the overall operation of the computer and a system bus that connects the central processor to one or more conventional components, such as a network card or modem. Each computer device may also include a variety of interface units and drives for reading and writing data or files. Depending on the type of computer device, a user can interact with the computer with a keyboard, pointing device, microphone, pen device or other input device.


Computer device 114 is shown directly connected to exchange computer system 100. Exchange computer system 100 and computer device 114 may be connected via a T1 line, a common local area network (LAN) or other mechanism for connecting computer devices. Computer device 114 is shown connected to a radio 132. The user of radio 132 may be a trader or exchange employee. The radio user may transmit order or other information to a user of computer device 114. The user of computer device 114 may then transmit the trade or other information to exchange computer system 100.


Computer devices 116 and 118 are coupled to a LAN 124. LAN 124 may have one or more of the well-known LAN topologies and may use a variety of different protocols, such as Ethernet. Computers 116 and 118 may communicate with each other and other computers and devices connected to LAN 124. Computers and other devices may be connected to LAN 124 via twisted pair wires, coaxial cable, fiber optics or other media. Alternatively, a wireless personal digital assistant device (PDA) 122 may communicate with LAN 124 or the Internet 126 via radio waves. PDA 122 may also communicate with exchange computer system 100 via a conventional wireless hub 128. As used herein, a PDA includes mobile telephones and other wireless devices that communicate with a network via radio waves.



FIG. 1 also shows LAN 124 connected to the Internet 126. LAN 124 may include a router to connect LAN 124 to the Internet 126. Computer device 120 is shown connected directly to the Internet 126. The connection may be via a modem, DSL line, satellite dish or any other device for connecting a computer device to the Internet.


One or more market makers 130 may maintain a market by providing constant bid and offer prices for a derivative or security to exchange computer system 100. Exchange computer system 100 may also exchange information with other trade engines, such as trade engine 138. One skilled in the art will appreciate that numerous additional computers and systems may be coupled to exchange computer system 100. Such computers and systems may include clearing, regulatory and fee systems.


The operations of computer devices and systems shown in FIG. 1 may be controlled by computer-executable instructions stored on computer-readable medium. For example, computer device 116 may include computer-executable instructions for receiving order information from a user and transmitting that order information to exchange computer system 100. In another example, computer device 118 may include computer-executable instructions for receiving market data from exchange computer system 100 and displaying that information to a user.


Of course, numerous additional servers, computers, handheld devices, personal digital assistants, telephones and other devices may also be connected to exchange computer system 100. Moreover, one skilled in the art will appreciate that the topology shown in FIG. 1 is merely an example and that the components shown in FIG. 1 may be connected by numerous alternative topologies.



FIG. 2 illustrates a system in which traders 202 and 204 exchange information with a match system 206, in accordance with an embodiment of the invention. Trader 202 is shown transmitting a variable derivative product order 208 and a limit data 210 to match system 206. Variable derivative product order 208 includes the identification of a derivative product and a variable order price. Variable derivative product orders are described in greater detail below in connection with FIG. 3. Limit data 210 may act as a throttle to limit the number of transactions entered into by trader 202. Limited data is also described in greater detail below. Trader 204 transmits derivative product orders 212 and 216 to match system 206. Each trader may transmit several derivative product orders and may associate limit data with one or more of the derivative product orders. As shown in order 212, one or more of the orders may include the identification of a hedge transaction.


Match system 206 may include several modules for determining prices, matching orders and executing transactions. An order book module 218 may be included to maintain a listing of current bid and offer prices. A price calculation module 220 calculates order prices based on price determination variables provided as part of variable derivative product orders. Price calculation module 220 may also calculate order prices based on formulas received from traders. For example, derivative product order 208 may include a formula that is a function of an underlying contract, delta and gamma. Price calculation module 220 may be configured to calculate an order price every time the price of the underlying contract changes.


Price calculation module 220 may use a default formula with price determination variable values supplied by a trader. In one embodiment, the change in a derivative product price is equal to

ChgUnderlyingPrice*delta+(½(ChgUnderlyingPrice^2*gamma)),   (1)

wherein ChgUnderlyingPrice is the change in the underlying price. A trader would supply price determination variables delta and gamma and price calculation module would track the derivative product price as the underlying contract changes.


An order risk management module 222 may be included to act as a limit for the user's exposure for a given risk variable as defined by the user. For example, trader 202 provided maximum and minimum delta, gamma and vega values to match system 206. Those values may be stored in the order risk management module 222 and computed before executing transactions. Depending on the user's order types and risk utilization for a given risk variable, the user's resting orders for a particular contract may be auto canceled by match system 206 so that the user is no longer at risk to exceed their limits. In addition, and depending on the user's order type and risk utilization for a given risk variable, the user's ability to enter a buy or sell order may be prohibited should the execution of that order cause the user to exceed their particular order risk management limit.


A formula database 224 may be included to store derivative product order formulas. The formulas may be provided by traders or may be standard formulas provided by an exchange. A market data module 226 may be used to collect and disseminate market data. A match engine module 228 matches bid and offer prices. Match engine module 228 may be implemented with software that executes one or more algorithms for matching bids and offers. A hedge module 230 may be included to perform hedge transactions based on derivative product transactions. The use of hedge transactions to counteract the risks associated with derivative product trading is well known in the art. In one embodiment of the invention, hedge module 230 conducts transactions with another trading engine other than match system 206. Hedge module 230 may also perform some or all of the function of risk management module 134 (shown in FIG. 1). An order processing module 236 may be included to decompose delta based and bulk order types for processing by order book module 218 and match engine module 228. A controller 232 may be included to control the overall operation of the components show coupled to bus 234. Controller 232 may be implemented with a central processing unit. Match system 206 may include modules that perform some or all of the functions of the modules shown in FIG. 1. Moreover, match system 206 may also be coupled to some or all of the elements shown in FIG. 1.



FIG. 3 illustrates a variable derivative product order 300 in accordance with an embodiment of the invention. Variable derivative product order 300 may include a field 302 for identifying a trader's account number. The underlying contract may be identified in field 304. The expiration month of the derivative product order may be identified in field 306. The order may be identified as a put or a call in field 308 and whether the order is to buy or sell in field 310. The quantity may be identified in field 312 and the strike price may be identified in field 314. Delta, gamma, and vega values may be identified in fields 316, 318 and 320 respectively. Of course, other price determination variables may also be identified as part of a standard variable derivative product order. The formula for calculating the price of variable derivative product order is identified in field 324. The trader can select a standard formula 326 to compute their derivative product price or select a custom formula 328. In one embodiment, a standard formula is supplied by or sponsored by an exchange. When a custom formula is selected, the trader may also provide a formula in field 330 and the variables in field 332. In one implementation of the invention, variable derivative product order 300 is created in the form of an XML for HTML document created by one of the computer devices shown in FIG. 1. Variable derivative product order 300 may be encrypted before being transmitted to an exchange. Of course one or more additional or alternative fields may be included. For example, a reference price may be included to protect against in flight conditions when the reference price changes while variable derivative product order 300 is in transit.



FIG. 4 illustrates a computer-implemented method of trading a derivative product contract that involves the use of a variable order price, in accordance with an embodiment of the invention. First, in step 402 it is determined whether the trader desires to use a standard exchange sponsored formula. In step 406, the trader transmits price determination variable values for the standard formula to an exchange computer. For example, step 406 may include transmitting delta and gamma values to an exchange computer. In step 408 the trader receives underlying data. The underlying data may include current bid and offer prices for underlying put and call futures contracts.


In step 410 it is determined whether the underlying data has changed. The price of an underlying contract may change multiple times per second. When the underlying contract data has changed, in step 412 the trader's computer device may recalculate the order price of their delta based order and all other delta based orders from other users based on current data. In step 414, it is determined whether any of the price determination variables used in the formula to calculate the order price have changed. The price determination variables may include delta, gamma, and vega. When the price determination variables have changed, in step 412, the order price is recalculated. Of course, step 412 may be performed based on changes in current underlying contract data and variables. The order price may be displayed to the trader or plotted on a graph that tracks order prices.


One of the advantages of the present invention is that it allows traders to maintain an order book and limits the amount of information that must be disseminated by an exchange computer. In particular, an exchange computer may transmit a plurality of variable derivative product orders to several different traders only when other derivative product order users establish their initial positions. Thereafter, the exchange computer may then only transmit underlying data or other data used to calculate variable derivative product order prices. Each trader computer may then periodically calculate current order prices based on information received from the exchange computer. For example, in step 416 it is determined whether other variable derivative product orders are received. When variable derivative product orders are received, in step 418 the trader computer may calculate new order book listings for current bids and offers related to variable derivative product based orders. The order book may be displayed to the trader in any one of a variety of conventional formats. After step 418, control returns to step 408.



FIG. 5 illustrates a method of processing variable derivative product orders by an exchange computer in accordance with an embodiment of the invention. First, in step 502 the exchange computer receives variable derivative product orders. As described above, the variable derivative product orders may be in the form of one or more formulas containing one or more price determination variables. In step 504, exchange computer may receive order risk management information to limit the user's exposure for a particular risk variable as given by the trader. Next, the exchange computer may receive or otherwise produce market data in step 506. The market data may include current underlying prices that may be used to calculate variable derivative product order prices. In step 508, bid and offer prices are calculated. The calculations may be based on a combination of formulas and variables provided by traders and/or the exchange. In step 510 the exchange computer finds a matching bid and offer. A matching bid and offer may be found by match engine 228. Before executing a transaction, in step 512 it is determined whether one or more order risk management limits provided by the trader have been exceeded. When a limit has been reached, all outstanding orders that contribute to the risk limit being exceeded further are automatically cancelled by the computer system. When the limits have not been exceeded, in step 514 the derivative product transaction is executed. Finally, in step 516 a hedge transaction may also be executed. A hedge transaction may be executed shortly after the execution of the derivative product transaction on a best efforts basis. Of course, an exchange computer may be configured to repeat the method shown in FIG. 5 several times.


The present invention has been described herein with reference to specific exemplary embodiments thereof. It will be apparent to those skilled in the art, that a person understanding this invention may conceive of changes or other embodiments or variations, which utilize the principles of this invention without departing from the broader spirit and scope of the invention as set forth in the appended claims. All are considered within the sphere, spirit, and scope of the invention. For example, while aspects of the present invention have been described in connection with the trading of derivative products, in other embodiments, aspects of the invention may be used in connection with the trading of securities, such as debt, foreign exchange, and equity commodities, and other instruments for which options or other derivative instruments are traded.

Claims
  • 1. A method of dynamically determining a price for an order for a derivative product at an exchange, comprising: receiving, by an exchange computer system and from a computing device, an order for a derivative product, wherein the order has a price, and wherein the order price has a value;receiving, by the exchange computer system and from the computing device, a designation of a formula by which updated order price values can be determined using values that include an underlying product price value, a delta variable value and a gamma variable value, wherein receiving the designation of the formula comprises receiving the formula with the order;determining by the exchange computer system and based on the order, new book listings for current bids and offers;transmitting, to the computing device, the new book listings;detecting a change in the underlying product price value;in response to detecting the change in the underlying product price value, utilizing the formula to determine, by the exchange computer system and based in part on the determined new book listings, an updated value for the order price without further input from the computing device; andexecuting, by the exchange computer system, a trade that includes the order.
  • 2. A method of dynamically determining a price for an order for a derivative product at an exchange, comprising: receiving, by an exchange computer system and from a computing device, an order for a derivative product, wherein the order has a price, and wherein the order price has a value;receiving, by the exchange computer system and from the computing device, a designation of a formula by which updated order price values can be determined using values that include an underlying product price value, a delta variable value and a gamma variable value, wherein receiving the designation of the formula comprises receiving a selection of the formula;determining, by the exchange computer system and based on the order, new book listings for current bids and offers;transmitting, to the computing device, the new book listings;detecting a change in the underlying product price value;subsequent to receiving the order and to receiving the designation, and in response to detecting the change in the underlying product price value, utilizing the formula to determine, by the exchange computer system and based in part on the determined new book listings, an updated value for the order price without further input from the computing device; andexecuting, by the exchange computer system, a trade that includes the order.
Parent Case Info

This application is a continuation of application Ser. No. 11/556,499 filed Nov. 3, 2006, which is a continuation of application Ser. No. 10/385,152 filed Mar. 10, 2003, the entire disclosure of which is hereby incorporated by reference.

US Referenced Citations (125)
Number Name Date Kind
5649116 McCoy Jul 1997 A
5799287 Dembo Aug 1998 A
5924082 Silverman Jul 1999 A
5950176 Keiser Sep 1999 A
6014643 Minton Jan 2000 A
6016483 Rickard Jan 2000 A
6018722 Ray Jan 2000 A
6061662 Makivic May 2000 A
6112189 Rickhard et al. Aug 2000 A
6195647 Martyn Feb 2001 B1
6236972 Shkedy May 2001 B1
6263321 Daughtery, III Jul 2001 B1
6282521 Howorka Aug 2001 B1
6317727 May Nov 2001 B1
6321212 Lange Nov 2001 B1
6347307 Sandhu Feb 2002 B1
6360210 Wallman Mar 2002 B1
6418419 Nieboer et al. Jul 2002 B1
6421653 May Jul 2002 B1
6505174 Keiser Jan 2003 B1
6616725 Cho Sep 2003 B2
6618707 Gary Sep 2003 B1
6622129 Whitworth Sep 2003 B1
6850907 Lutnick Feb 2005 B2
7024387 Nieboer et al. Apr 2006 B1
7089204 Nieboer et al. Aug 2006 B1
7117833 Spath et al. Oct 2006 B2
7152041 Salavadori et al. Dec 2006 B2
7177833 Marynowski et al. Feb 2007 B1
7321872 Kaminsky et al. Jan 2008 B1
7418422 Burns Aug 2008 B2
7440917 Farrell et al. Oct 2008 B2
7567499 Nakamura et al. Jul 2009 B2
7567932 Salvadori et al. Jul 2009 B1
7571133 Farrell et al. Aug 2009 B2
7672899 Farrell et al. Mar 2010 B2
7778911 Salvadori et al. Aug 2010 B2
7890418 Farrell et al. Feb 2011 B2
7991684 Salvadori et al. Aug 2011 B2
8060431 Farrell et al. Nov 2011 B2
8160949 Johnston et al. Apr 2012 B2
8224737 Farrell et al. Jul 2012 B2
8326738 Johnston et al. Dec 2012 B2
20010032163 Fertik Oct 2001 A1
20010034695 Wilkinson Oct 2001 A1
20010042036 Sanders Nov 2001 A1
20010044771 Usher Nov 2001 A1
20010056398 Scheirer Dec 2001 A1
20020002530 May Jan 2002 A1
20020016760 Pathak Feb 2002 A1
20020046151 Otero Apr 2002 A1
20020049661 Otero Apr 2002 A1
20020065755 Shlafman May 2002 A1
20020069155 Nafeh Jun 2002 A1
20020073007 Ayache Jun 2002 A1
20020082967 Kaminsky Jun 2002 A1
20020099651 May Jul 2002 A1
20020116317 May Aug 2002 A1
20020120542 Higgins Sep 2002 A1
20020128955 Brady Sep 2002 A1
20020133456 Lancaster Sep 2002 A1
20020138390 May Sep 2002 A1
20020156719 Finebaum Oct 2002 A1
20020169703 Lutnick et al. Nov 2002 A1
20020174055 Dick Nov 2002 A1
20020174056 Sefein Nov 2002 A1
20020194115 Nordlicht et al. Dec 2002 A1
20030004853 Ram Jan 2003 A1
20030009419 Chavez Jan 2003 A1
20030023536 Hollerman Jan 2003 A1
20030023546 Shepherd Jan 2003 A1
20030028468 Wong et al. Feb 2003 A1
20030028476 Jenkins Feb 2003 A1
20030033212 Sandhu et al. Feb 2003 A1
20030033240 Balson Feb 2003 A1
20030041009 Grey et al. Feb 2003 A1
20030046218 Albanese Mar 2003 A1
20030061148 Alavian Mar 2003 A1
20030069821 Williams Apr 2003 A1
20030069836 Penney Apr 2003 A1
20030074167 Browne Apr 2003 A1
20030083978 Brouwer May 2003 A1
20030093347 Gray May 2003 A1
20030093360 May May 2003 A1
20030097328 Lundberg May 2003 A1
20030101123 Alvarado May 2003 A1
20030101125 McGill May 2003 A1
20030115128 Lange Jun 2003 A1
20030195822 Tatge Oct 2003 A1
20030208430 Gershon Nov 2003 A1
20030216932 Foley Nov 2003 A1
20030220865 Lutnick Nov 2003 A1
20030220868 May Nov 2003 A1
20030225648 Hylton Dec 2003 A1
20030233308 Lundberg Dec 2003 A1
20030236737 Kemp, III Dec 2003 A1
20030236795 Kemp et al. Dec 2003 A1
20040006534 Fung Jan 2004 A1
20040044613 Murakami et al. Mar 2004 A1
20040064393 Luenberger Apr 2004 A1
20040083158 Addison Apr 2004 A1
20040083165 Lawrence Apr 2004 A1
20040128261 Olavson et al. Jul 2004 A1
20040148249 Kinnear Jul 2004 A1
20040172355 Pandher Sep 2004 A1
20040199452 Johnston et al. Oct 2004 A1
20040199455 Saliba Oct 2004 A1
20040199459 Johnston et al. Oct 2004 A1
20040267655 Davidowitz et al. Dec 2004 A1
20050160024 Soderborg Jul 2005 A1
20050260492 Tucholski et al. Nov 2005 A1
20060160024 Barr Jul 2006 A1
20060184447 Nieboer et al. Aug 2006 A1
20060253368 O'Callahan et al. Nov 2006 A1
20070255642 Keith Nov 2007 A1
20080052223 Johnston et al. Feb 2008 A1
20080091584 Johnston et al. Apr 2008 A1
20090119201 Burns et al. May 2009 A1
20090265267 Johnston et al. Oct 2009 A1
20100094746 MacGregor et al. Apr 2010 A1
20100306133 Johnston et al. Dec 2010 A1
20110040669 Lee et al. Feb 2011 A1
20110270737 Johnston et al. Nov 2011 A1
20120030090 Johnston et al. Feb 2012 A1
20120041896 Johnston et al. Feb 2012 A1
Foreign Referenced Citations (11)
Number Date Country
2406418 Oct 2001 CA
2430173 Jun 2002 CA
1178416 Feb 2002 EP
2003505794 Feb 2003 JP
9737735 Oct 1997 WO
02089027 Nov 2002 WO
02091650 Nov 2002 WO
3001325 Jan 2003 WO
03034297 Apr 2003 WO
2004008274 Jan 2004 WO
2004081737 Sep 2004 WO
Non-Patent Literature Citations (80)
Entry
Ross, Derek. “Controlling Derivatives”, Accountancy. London: Mar. 1995. vol. 115, Iss. 1219. p. 138.
Zeto, Samuel Yau Man. “Pricing and Hedging American Fixed-Income Derivatives with Implied Volatility Structures in the Two-Factor Health-Jarrow-Morton Model”. The Journal of Futures Markets. Hoboken. Sep. 2002. vol. 22, Iss. 9, p. 839.
Agarwal, Aman. “Defining Parameters of an Underlying Variable (Asset/Value) and Establishing Water Table as Underlying Value”. Finance India. Delhi: Dec. 2002. vol. 16, Iss. 4, p. 1273.
“Single Integrated Architecture” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL :http://www.sungard.com/products and services/stars/panorama/solutions/panoramatechnologvandinfrastr.
Senior, Adriana. “Morgan Buying Into Network for On-Line Security Trades” [retrieved on Mar. 25, 2005] Retrieved from the internet <URL :http://proquest.uni.com/pqdlink?index=26&sid=1&srchmode=3&vinst=PROD&fmt=3&st.
Ostrovsky, Arkady. “Working towards a seamless link: Global Protocol” [retrieved on Mar. 25, 2005] Retrieved from the internet <URL :http://proquest.uni.com/pqdlink?index=1&sid=1&srchmode=1&vinst=PROD&fmt=3&sta.
“Case Study: BSE implements intelligent switching architecture Combining networks intelligently” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL :http://www.networkmagazineindia.com/200302/case2.shtml.
“BSE The Stock Exchange, Mumbal Network Diagram” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL :http:/.
Domowitz, Ian. “Electronic Derivatives Exchanges: Implicit Mergers, Network Externalities, and Standardization” The Quarterly Review of Economics and Finance, vol. 35, No. 2, Summer, 1995, p. 163-175.
“Derivatives Drive New Network” Barron's, Nov. 4, 1991: 71, 44: ABLINFORM Global, p. 36.
NYFIX, Inc. Routes OTC Orders to American Stock Exchange [retrieved on Dec. 5, 2003] Retrieved from the internet <URL :http://www.prnewswire.com/cgi-bin/stories.pl?ACCT=SVBIZINK3.story&STORY=/www/story/11-24-2.
“Trading and Decision Support” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL :http://www.sungard.com/products—and—services/stars/panoram/solutions/panoramatrading.htm.
“Orc Technology” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL :http://www.orcsoftware.com/Technology/index.htm.
“Creditex widens access” [retrieved on Mar. 29, 2004] Retrieved from the internet <URL:http://www.efinancialnews.com/index.cfm? ...on=print—view&passedref=8000000000002212.
Treanor, Jill. “Banks plan trading network for $52 trillion derivatives” [retrieved on Mar. 18, 2004] Retrieved from the internet <URL :http://www.guardian.co.uk/business/story/0,3604,178019,00.html.
“OnExchange Selects Exodus to Host Online Derivatives Exchange; Leading Online Derivatives Exchange Optimizes Network Performance by Selecting Leader in Complex Internet Hosting” [retrieved on Mar. 25, 2004] Retrieved from the internet <URL :http://www.findarticles.com/cf—0/m0EIN/2000—Nov—7/66657629/pl/article.jhtml.
“ExNet Network” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL:http://www.orcsoftware.com/Products/ExNetPIPNetwork.htm.
“Orc Futures” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL:http://www.orcsoftware.com/Products/OrcFutures.htm.
“Orc Liquidator” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL:http://www.orcsoftware.com/Products/OrcLiquidator.htm.
[retrieved on Dec. 5, 2003] Retrieved from the internet <URL:http://www.wstonline.com/printableArticle/;jsessionid=NA3QPNTTNKCOIQSNDBCCK. . . .
[Retrieved on Dec. 5, 2003] Retrieved from the internet <URL:http://www.wstonline.com/printableArticle/;jsessionid=ILJHDTNYRJNVMQSNDBCCKHY?doc id=14. . . .
“Press Releases” [retrieved on Mar. 18, 2004] Retrieved from the internet <URL:htt;:www.swapswire.com/press/10—04—00.asp.
“Single Integrated Architecture” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL:htt;:www.sungard.com/products and services/stars/panorama/solutions/panoramatechnologyvandinfrastr.
“The integrated, real-time solution for bank treasure and portfolio management” SunGard Securities Processing.
“Panorama EQN” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL:htt;:www.sungard.com/products—and—ervices/stars/panorama/solutions/panaromaotcdistribution.htmr.
“Chicago Board of Trade certifies Orc Software for its electronic trading platform” [retrieved on Dec. 5, 2003] Retrieved from the internet <URL:http://www.orcsoftware.com/Company/PNR/PNR 031106 e-shot eng.htm.
“X—Trader Platform ”[retrieved on Mar. 18, 2004] Retrieved from the internet URL<http://www.tradingttechnologies.com/blue xtrader.html.
“X—Trader TT Net ”[retrieved on Dec. 5, 2003] Retrieved from the internet URL<http://www.tradingttechnologies.com/blue—net.html.
Ritchie, Joseph; Abstract “Why Market Maker Position Limits Should Be Delta-Based”; Futures, vol. 17, No. 9, pp. 42 (2), Aug. 1988; UMI Publication No. 00415047.
Meyer, Thomas O.; “Calculation and comparison of delta-neutral and multiple-Greek dynamic hedge returns inclusive of market frictions”; Department of Commerce, International Review of Economics and Finance;12 (2003); pp. 207-235.
Temple, Peter, et al; World Reporter (TM); Investors Chronicle; Dec. 11, 1998; Copyright (C) 1998 Investors Chronicle; p. 62.
Holter, James T.; It's Liquidity Stupid, CBOE Ups S & P Limits; www.futuresmag.com; Nov. 1996.
Kawaller, Ira G; “A novel approach to transactions-based currency exposure management”; Financial Analysts Journal; Nov./Dec. 1992; 48, 6; p. 79.
“S&P ComStock/Micro Hedge Windows: results rooted in reliability.”; Futures (Cedar Falls, Iowa); Annual 1993 v22 n7 p. 26(1); Copyright Oster Communications Inc. 1993.
Miller, Merton, “Financial Innovations and Market Volatility”, Chapter 11, 1991.
Wohl, Avi, “Implications of an Index-Contingent Trading Mechanism”, Journal of Business , vol. 70, No. 4, 1997.
“Record Volume on ITG Trading Desk”, ITG Connect, Spring 1996.
Schellhorn, Henry, “Combination Trading with Limit Orders”, Journal of Applied Mathematics & Decision Sciences, pp. 133-150, 1997.
“Securities and Exchange Commission Notice”, Federal Register, vol. 59, No. 24, Feb. 4, 1994.
Downes, John, “Dictionary of Finance and Investment Terms”, 1985.
POSIT Volume History, http://www.itginc.com/itg—posit—vol—hist.html, ITG POSIT Keeps growing, Aug. 20, 1998, 3 pages.
ITG Products, http://www.itginc.com/products.html , Aug. 19, 1998, 1 page.
ITG POSIT, http://www.itginc.com/products/pos—works.html, Aug. 20, 1998, 1 page.
ITG POSIT, http://www.itginc.com/products/pos—advan.html, Aug. 20, 1998, 2 pages.
ITGI's 1995 Third Quarter Results, ITG Press Release Oct. 9, 1998, http://www.itginc.com/itg—press—rel1.html, Aug. 20, 1998, 2 pages.
ITGI's 1995 Fourth Quarter Results: Record Earnings, ITG Press Release Jan. 23, 1996, http://www.itginc.com/4qpress.html, Aug. 20, 1998, 3 pages.
ITG Press Release—Dec. 9, 1996, http://www.itginc.com/presindi.html, Aug. 19, 1998, 2 pages.
ITG POSIT, The worlds largest Intra-day trade matching system, http://www.itginc.com/products/posit.html, Aug. 19, 1998, 2 pages.
Record Trading Desk Volume, ITG Connect—Spring 96, http://www.posit.com/4con—02.html, Aug. 20, 1998, 3 pages.
The Future of Trading, ITG QuantEx Brochure, 7 pages.
ITG Platform Brochure, 6 pages.
“Introducing the OptiMark System”, Technologies Inc., 17 pages.
ITG POSIT Brochure, 4 pages.
POSIT “Portfolio System for Institutional Trading”, User's Guide, 93 Pages.
Robert A. Schwartz, “Reshaping the Equity Markets, A Guide for the 1990's”, Harper Business, 1991, 7 pages.
Oct. 15, 1993—“The Chicago Basket” (CXM Basket), Letter, 21 pages.
“Trading on the Frontier”, Plan Sponsor, Oct. 1996, 8 pages.
“Optimark Technologies to Announce Trading System Aimed at Institutions”, the Wall Street Journal, Sep. 24, 1996, 1 page.
“Great Expectations”, Howard Banks, Forbes, Dec. 2, 1996, 3 pages.
Downes, et al., Dictionary of Finance and Investment Terms, Barrons Educational Services, 1998, pp. 27-28.
Carandang, “Deriviative Portfolio Risk Management Using a Value-at-Risk Framework”, Proceedings of the IEEE/IAFE 1997, Computational Intelligence for Financial Engineering (CIFEr) (Cat. No. 97TH8304), Inclusive p. Nos. 260-265, New York, NY 1997.
U.S. Appl. No. 13/182,178, filed Jul. 13, 2011.
David G. Mcmillan, Alan E.H. Speight, The Journal of Futures Markets, Hoboken: Nov. 2002, vol. 22, Iss. 11, p. 1037.
Stanley Kucemba, Brian Petrak, and Comerica Bank, “Active and Passive Foreign Exchange Risk Management: A Primer,” TMA Journal; Nov./Dec. 1996, pp. 18-22 and 24.
Document titled “The Peg Orders”, downloaded from <http://www.euronext.com/>, first published before Nov. 3, 2011.
Chacko, et al., “Pricing Interest Rate Derivatives”, the Review of Financial Studies, Mar. 2002; 15, 1; ABI/INFORM Global, p. 195.
Introduction to the International Securities Exchange, International Securities Exchange, pp. 1-12, 1999.
Bleakly, “Firms Approach Hedges with Caution”, Asian Wall Street Journal, New York, NY, Aug. 18, 1993, p. 1.
Lee, “Industry Standard Sought for Valuing Options”, Euromoney, London, May 1993, p. 48, 2 pages.
U.S. Appl. No. 13/288,397, filed Nov. 3, 2011.
International Search Report and Written Opinion for PCT/US04/07064 dated May 31, 2005.
Examination Report in EP 04718565.7 dated Sep. 2, 2008.
Office Action with English translation in JP2006-506956 dated Jul. 21, 2009.
Document attached to Notice of Allowance dated Mar. 19, 2009, from file history of U.S. Appl. No. 10/611,458.
Final Office Action in U.S. Appl. No. 13/182,178 dated Apr. 20, 2012.
U.S. Appl. No. 13/660,486, filed Oct. 25, 2012.
Barone-Asesi, et al., “Efficient Analytic Approximation of American Option Values”, Journal of Finance, vol. 42, No. 2 (Jun. 1987), pp. 301-320.
International Search Report and Written Opinion for PCT/US12/61840 dated Dec. 28, 2012.
Canadian Patent Application No. 2,518,623 Examiner's Report dated Sep. 30, 2013.
Office Action in CA 2,518,623 dated Feb. 16, 2012.
Related Publications (1)
Number Date Country
20090265267 A1 Oct 2009 US
Continuations (2)
Number Date Country
Parent 11556499 Nov 2006 US
Child 12496831 US
Parent 10385152 Mar 2003 US
Child 11556499 US