METHOD AND APPARATUS FOR HIGH-SPEED PROCESSING OF FINANCIAL MARKET DEPTH DATA

• US 20120095893A1
• Filed: 12/14/2009
• Published: 04/19/2012
• Est. Priority Date: 12/15/2008
• Status: Abandoned Application

• Current Assignee: Exegy Incorporated
• Original Assignee: Exegy Incorporated
• Inventors: Taylor, David E., Parsons, Scott, Whatley, Jeremy Walter, Bradley, Richard, Gyang, Kwame, Dewulf, Michael
• Application Number:
  US13/132,408
• Publication Number:
  US 20120095893A1
• Time in Patent Office: Days
• US Class Current: 705/35
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Claims

1. A method for generating an order book view from financial market depth data, the method comprising:

maintaining a data structure representative of a plurality of order books for a plurality of financial instruments; and

hardware-accelerating a processing of a plurality of financial market depth data messages to update the order books within the data structure.

2. The method of claim 1 wherein the data structure comprises a plurality of limit order records, each limit order record pertaining to a limit order for a financial instrument on an exchange and comprising a plurality of data fields, and wherein the financial market depth data messages comprise a plurality of limit order events, each limit order event pertaining to a limit order for a financial instrument on an exchange and comprising a plurality of data fields, and wherein the processing step comprises building the limit order records in the data structure based at least in part on the limit order event data fields.

3. The method of claim 2 wherein the processing step comprises (1) receiving a limit order event, (2) determining whether the received limit order event represents a new limit order or whether the received limit order represents an update for a previous limit order, (3) in response to a determination that the received limit order event represents a new limit order, creating a new limit order record in the data structure, and (4) in response to a determination that the received limit order event represents an update for a previous limit order, (i) retrieving a limit order record from the data structure based on at least one data field of the received limit order event, and (ii) updating at least one of the data fields in the retrieved limit order record based on at least one data field of the received limit order event.

4. The method of claim 3 wherein the data structure is organized as a hash table, and wherein the retrieving step comprises (1) generating a hash key based on at least one field in the received limit order event, and (2) locating the limit order record for retrieval within the data structure using the generated hash key.

5. The method of claim 4 wherein the limit order event data fields comprise a financial instrument symbol field, and wherein the hash key generating step comprises generating the hash key based on at least the symbol field.

6. The method of claim 4 wherein the limit order event data fields comprise an order identifier field, and wherein the hash key generating step comprises generating the hash key based on at least the order identifier field.

7. The method of claim 3 wherein the data structure comprises a plurality of price point records, each price point record comprising a plurality of data fields and being representative of an aggregation of limit orders for a financial instrument at a particular price, and wherein the processing step comprises building the price point records in the data structure based at least in part on the limit order event data fields.

8. The method of claim 7 wherein the limit order event includes a price data field, and wherein the processing step comprises (1) determining whether a price point record associated with the limit order event exists in the data structure based at least in part on the price data field, (2) in response to a determination that a price point record associated with the limit order event exists in the data structure, (i) retrieving the price point record from the data structure, and (ii) updating at least one of the data fields in the retrieved price point record based on at least one data field of the received limit order event, and (3) in response to a determination that a price point record associated with the limit order event does not exist in the data structure, (i) creating a new price point record based on the received limit order event, and (ii) storing the created new price point record in the data structure.

9. The method of any of claim 1 wherein the data structure comprises a data structure indicative of a sort order for orders within the order book data structure, and wherein the processing step further comprises determining an updated sort order in the sort order data structure for a record in the updated order book based at least in part on the financial market depth data messages.

10. The method of claim 1 wherein the order book data structure is configured to store order books are a plurality of financial instruments, the order books comprising at least one member of the group consisting of (1) a limit order record book for a plurality of financial instruments, (2) a regional price aggregated order book for a plurality of financial instruments, and (3) a composite price aggregated order book for a plurality of financial instruments.

11. The method of claim 1 wherein the hardware-accelerating step comprises performing the processing step with a reconfigurable logic device.

12. The method of claim 1 wherein the method steps are performed within a ticker plant.

13. A system for generating an order book view from financial market depth data, the system comprising:

a memory for storing a data structure representative of a plurality of order books for a plurality of financial instruments; and

a coprocessor configured to process a plurality of financial market depth data messages to update the order books within the data structure.

14. The system of claim 13 wherein the data structure comprises a plurality of limit order records, each limit order record pertaining to a limit order for a financial instrument on an exchange and comprising a plurality of data fields, and wherein the financial market depth data messages comprise a plurality of limit order events, each limit order event pertaining to a limit order for a financial instrument on an exchange and comprising a plurality of data fields, and wherein the processing step comprises building the limit order records in the data structure based at least in part on the limit order event data fields.

15. The system of claim 14 wherein the processing step comprises (1) receiving a limit order event, (2) determining whether the received limit order event represents a new limit order or whether the received limit order represents an update for a previous limit order, (3) in response to a determination that the received limit order event represents a new limit order, creating a new limit order record in the data structure, and (4) in response to a determination that the received limit order event represents an update for a previous limit order, (i) retrieving a limit order record from the data structure based on at least one data field of the received limit order event, and (ii) updating at least one of the data fields in the retrieved limit order record based on at least one data field of the received limit order event.

16. The system of claim 15 wherein the data structure is organized as a hash table, and wherein the retrieving step comprises (1) generating a hash key based on at least one field in the received limit order event, and (2) locating the limit order record for retrieval within the data structure using the generated hash key.

17. The system of claim 16 wherein the limit order event data fields comprise a financial instrument symbol field, and wherein the hash key generating step comprises generating the hash key based on at least the symbol field.

18. The system of claim 16 wherein the limit order event data fields comprise an order identifier field, and wherein the hash key generating step comprises generating the hash key based on at least the order identifier field.

19. The system of claim 15 wherein the data structure comprises a plurality of price point records, each price point record comprising a plurality of data fields and being representative of an aggregation of limit orders for a financial instrument at a particular price, and wherein the processing step comprises building the price point records in the data structure based at least in part on the limit order event data fields.

20. The system of claim 19 wherein the limit order event includes a price data field, and wherein the processing step comprises (1) determining whether a price point record associated with the limit order event exists in the data structure based at least in part on the price data field, (2) in response to a determination that a price point record associated with the limit order event exists in the data structure, (i) retrieving the price point record from the data structure, and (ii) updating at least one of the data fields in the retrieved price point record based on at least one data field of the received limit order event, and (3) in response to a determination that a price point record associated with the limit order event does not exist in the data structure, (i) creating a new price point record based on the received limit order event, and (ii) storing the created new price point record in the data structure.

21. The system of claim 13 wherein the data structure comprises a data structure indicative of a sort order for orders within the order book data structure, and wherein the processing step further comprises determining an updated sort order in the sort order data structure for a record in the updated order book based at least in part on the financial market depth data messages.

22. The system of claim 13 wherein the order book data structure is configured to store order books are a plurality of financial instruments, the order books comprising at least one member of the group consisting of (1) a limit order record book for a plurality of financial instruments, (2) a regional price aggregated order book for a plurality of financial instruments, and (3) a composite price aggregated order book for a plurality of financial instruments.

23. The system of claim 13 wherein the coprocessor comprises a reconfigurable logic device.

24. The system of claim 13 wherein the memory and the coprocessor are resident within a ticker plant.

25-161. -161. (canceled)