Method for directing and executing certified trading interests

• US 8,010,438 B2
• Filed: 12/29/2000
• Issued: 08/30/2011
• Est. Priority Date: 06/01/2000
• Status: Active Grant

• Current Assignee: Virtu ITG Software Solutions LLC
• Original Assignee: Aritas Group, Inc.
• Inventors: Federspiel, Fred J., Waelbroeck, Henri, Angel, James J.
• Primary Examiner(s): HAMILTON, LALITA M
• Application Number:
  US09/750,768
• Publication Number:
  US 20020010672A1
• Time in Patent Office: 3,896 Days
• Field of Search: 705/35, 705/36, 705/37, 705/38, 705/36.R
• US Class Current: 705/37
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0633 Lists, e.g. purchase orders, compilation or processing
• CPC Class Codes: G06Q 30/08 Auctions
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

Preferred embodiments of the subject invention overcome the limitations of known trading interest targeting and execution systems by (1) enabling market participants to limit targeting of trading interests to only those other market participants likely to have a significant contra-interest; (2) enabling market participants to ensure that other market participants'"'"' disseminated trading interests are legitimate; and (3) enabling auctions among trading interests targeted and validated in this manner. Software of a preferred embodiment identifies likely contra-interests by analyzing information from various sources regarding certified trading interests. Preferred embodiments that route and otherwise manage orders based on trading interest information are also described.

Claims

1. A computer-implemented method of managing market information, comprising the steps of:

(a) electronically receiving with a computer system data including confidential information regarding market participants, wherein said data regarding market participants comprises data regarding a first market participant and a second market participant;

(b) electronically receiving with said computer system an electronically executable order and targeting parameters from said first market participant;

(c) electronically receiving with said computer system confidential trading interest information from said second market participant;

(d) identifying said second market participant as a market participant that is most likely to take a contra side of said electronically executable order and as unlikely to use information regarding said order in a manner that would affect the price or availability of said security, wherein said step of identifying is based, at least in part, on said received confidential information regarding market participants;

(e) routing said electronically executable order to said identified second market participant without revealing said first market participant'"'"'s identity or other confidential information regarding said first market participant to said second market participant, and wherein no information regarding said second market participant or said confidential trading interest information received from said second market participant is transferred to said first market participant; and

(f) producing a targeted dissemination list of market participants based, at least in part, on said received confidential information regarding market participants and said order and targeting parameters, and wherein the step of identifying a second market participant that is most likely to take a contra side of said order is based on said dissemination list.

2. A method as in claim 1, wherein said confidential trading interest information comprises certified trading interest information.

3. A method as in claim 1, wherein said confidential trading interest information comprises a time of a call.

4. A method as in claim 1, wherein the step of identifying said second market participant is based on order size.

5. A method as in claim 1, wherein the step of identifying said second market participant is based on execution size.

6. A method as in claim 1, wherein the step of identifying said second market participant is based on price aggression.

7. A method as in claim 1, wherein the step of identifying said second market participant is based on location.

8. A method as in claim 1, wherein the step of identifying said second market participant is based on comparing the past behavior of market participants after they received notifications or orders.

9. A method as in claim 1, wherein the step of identifying said second market participant is based on time of auction call.

10. A method as in claim 1, wherein the step of identifying said second market participant is based on comparing the past behavior of market participants after they received electronically executable orders.

11. A method as in claim 1, wherein the step of identifying said second market participant is based on time of most recent execution.

12. A method as in claim 1, wherein the step of producing a targeted dissemination list of market participants based on said stored data regarding market participants and said electronically executable order and targeting parameters is based on relations between said stored data not known to said first market participant.

13. A method as in claim 12, wherein said relations comprise information indicating that multiple data entries involve a same end party.

14. A method as in claim 13, wherein the step of producing said targeted dissemination list comprises calculating the total number of shares bought or sold by said end party.

15. A method as in claim 1, wherein the step of producing a targeted dissemination list of market participants based on said stored data regarding market participants and said electronically executable order and targeting parameters is based on data that is not available to any individual market participant, and wherein said step of producing a targeted dissemination list comprises aggregating data provided by a plurality of market participants.

16. A method as in claim 15, wherein said step of aggregating data is based on data that is provided by a marketplace.

17. A method as in claim 16, wherein said data that is provided by a marketplace is Automated Confirmation Transaction Service^SM data and said marketplace is the Nasdaq Stock Market'"'"'.

18. A method as in claim 15, wherein said step of aggregating data is based on data that is provided by a plurality of participating broker-dealers.

19. The method of claim 15, wherein said step of aggregating data is based on data that comprises the identity of a buy-side party for which a trade was executed.

20. A method as in claim 1, wherein the step of producing a targeted dissemination list of market participants based on said stored data regarding market participants and said electronically executable order and targeting parameters is based o11 data that is not available to any individual market participant, and wherein said step of producing a targeted dissemination list comprises comparing data provided by a plurality of market participants.

21. A method as in claim 20, wherein said step of comparing data provided by a plurality of market participants comprises the step of netting out middlemen to identify an end buyer and an end seller in a trade.

22. A method as in claim 21, wherein said second market participant is a market maker, and wherein said step of comparing data provided by a plurality of market participants comprises the step of netting out middlemen to identify an end buyer and an end seller in a trade results in identifying net market position of said market maker.

23. The method of claim 20, wherein said step of comparing data provided by a plurality of market participants comprises the step of calculating the total number of shares bought or sold by a buy-side party for which a trade was executed through one or more intermediaries.

24. A method as in claim 1, further comprising the steps of:

(c) ranking market participants on said targeted dissemination list in order of likelihood of taking the contra side of said electronically executable order; and

(d) if said identified second market participant does not execute said electronically executable order, successively routing said electronically executable order to the remaining market participants on said ranked targeted dissemination list, in order of likelihood of taking the contra side of said electronically executable order, until said electronically executable order is executed.

25. A method as in claim 24, wherein said ranking is based on probability of execution.

26. A method as in claim 25, wherein said probability of execution is calculated based on a count of number of orders delivered versus number of executions for different types of orders.

27. A method as in claim 25, wherein said probability of execution is calculated based on comparing the past behavior of market participants after they received notifications or orders.

28. A method as in claim 25, wherein said probability of execution is calculated based on comparing the past behavior of market participants after they received electronically executable orders.

29. A method as in claim 25, further comprising the steps of monitoring price fluctuation following order delivery to a market center and identifying statistically significant correlations between order delivery events and subsequent price fluctuations on a market.

30. A method of managing market information, comprising the steps of:

(a) electronically receiving with a computer system data including confidential information regarding market participants;

(b) electronically storing with said computer system said received data regarding market participants;

(c) electronically receiving with said computer system an order-related query from a first market participant;

(d) based on said received data regarding market participants, calculating with said computer system an estimate of a probability of execution if the order were routed to market participants based on said query; and

(e) electronically reporting with said computer system said probability to said first market participant.

31. A method as in claim 30, wherein said probability of execution is calculated based on a count of number of orders delivered versus number of executions for different types of orders.

32. A method as in claim 30, further comprising the step of electronically reporting an estimate of the price impact following the delivery of an order based on said query to said first market participant.