METHOD AND SYSTEM FOR PROCESSING REAL-TIME, ASYNCHRONOUS FINANCIAL MARKET DATA EVENTS ON A PARALLEL COMPUTING PLATFORM

• US 20100211519A1
• Filed: 02/17/2009
• Published: 08/19/2010
• Est. Priority Date: 02/17/2009
• Status: Abandoned Application

• Current Assignee: Parallel Trading Systems Incorporated
• Original Assignee: Parallel Trading Systems Incorporated
• Inventors: Giannetti, Alberto E.
• Application Number:
  US12/372,184
• Publication Number:
  US 20100211519A1
• Time in Patent Office: Days
• US Class Current: 705/36.R
• 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

A method and system are provided for real-time, asynchronous processing of financial market data events on a parallel computing platform having a plurality of computer processes executing on one or more computers. The method includes: (a) receiving a generally continuous stream of market data events from an electronic exchange over a computer network; (b) sequentially storing the market data events received in (a) in at least one data queue; (c) distributing the market data events among the plurality of computer processes on a first in, first out basis such that the market data events can be processed by the processes in a coordinated fashion; (d) processing the market data events distributed in (c) at the respective computer processes using financial models to generate trading information on one or more financial instruments; and (e) making the trading information generated in (d) available through a common API or a client GUI to the a user.

Claims

1. A method for real-time, asynchronous processing of financial market data events on a parallel computing platform having a plurality of computer processes executing on one or more computers, comprising:

(a) receiving a generally continuous stream of market data events from an electronic exchange over a computer network;

(b) sequentially storing the market data events received in (a) in at least one data queue;

(c) distributing the market data events among the plurality of computer processes on a first in, first out basis such that the market data events can be processed by the processes in a coordinated fashion;

(d) processing the market data events distributed in (c) at the respective computer processes using financial models to generate trading information on one or more financial instruments; and

(e) making the trading information generated in (d) available through a common API or a client application to a user.

2. The method of claim 1 wherein the one or more computers comprise a cluster of computers connected by high-performance network interface cards.

3. The method of claim 1 wherein the trading information is used for pricing financial instruments, managing risk, or automatically making trading decisions.

4. The method of claim 1 wherein the market data events are distributed among the plurality of computer processes using atomic operations.

5. The method of claim 1 wherein the market data events are distributed among the plurality of computer processes based on load-balancing.

6. The method of claim 1 wherein computer processes are allocated to market data events associated with subsets of financial instruments to provide load-balancing based on estimated market volumes of each subset of financial instruments.

7. The method of claim 1 wherein the market data events are distributed among the plurality of computer processes using an MPI standard.

8. The method of claim 1 wherein the trading information is organized in a memory window for remote memory access (RMA) to allow data access from multiple processes in a single MPI communicator.

9. The method of claim 1 wherein the at least one data queue comprises a plurality of data queues, with each queue storing events relating to particular financial instruments, and wherein the method further comprises allocating each process to process events from a particular queue.

10. The method of claim 1 wherein the trading information is ordered in accordance with a sequence number or timestamp associated with a corresponding event.

11. The method of claim 1 further comprising converting the event data from an exchange specific format to a local trading system format.

12. The method of claim 1 wherein (e) comprises representing the trading information as a set of two dimensional arrays where one dimension indicates a particular instrument and another dimension indicates a time ordered index indicating one of the last N updates, where N is a parameter defined by the user.

13. The method of claim 1 wherein the at least one data queue comprises an inter-process, multiple-producer/multiple-consumer distributed queue or a single-producer/multiple-consumer distributed queue, and wherein each market data event can be submitted by one or more processes and consumed by the first available process.

14. A system for real-time, asynchronous processing of financial market data events on a parallel computing platform having a plurality of computer processes executing on one or more computers, comprising:

a market data component for receiving a generally continuous stream of market data events from an electronic exchange over a computer network, and sequentially storing the market data events received in at least one data queue;

a computing cluster comprising a plurality of computer processes;

a process for distributing the market data events among the plurality of computer processes in the computing cluster on a first in, first out basis such that the market data events can be processed by the processes in a coordinated fashion using financial models to generate trading information on one or more financial instruments; and

a process for making the trading information available through a common API or a client application to a user.

15. The system of claim 14 wherein the one or more computers comprise a cluster of computers connected by high-performance network interface cards.

16. The system of claim 14 wherein the trading information is used for pricing financial instruments, managing risk, or automatically making trading decisions.

17. The system of claim 14 wherein the market data events are distributed among the plurality of computer processes using atomic operations.

18. The system of claim 14 wherein the market data events are distributed among the plurality of computer processes based on load-balancing.

19. The system of claim 14 wherein computer processes are allocated to market data events associated with subsets of financial instruments to provide load-balancing based on estimated market volumes of each subset of financial instruments.

20. The system of claim 14 wherein the market data events are distributed among the plurality of computer processes using an MPI standard.

21. The system of claim 14 wherein the trading information is organized in a memory window for remote memory access (RMA) to allow data access from multiple processes in a single MPI communicator.

22. The system of claim 14 wherein the at least one data queue comprises a plurality of data queues, with each queue storing events relating to particular financial instruments, and wherein the method further comprises allocating each process to process events from a particular queue.

23. The system of claim 14 wherein the trading information is ordered in accordance with a sequence number or timestamp associated with a corresponding event.

24. The system of claim 14 further comprising converting the event data from an exchange specific format to a local trading system format.

25. The system of claim 14 wherein making the trading information available comprises representing the trading information as a set of two dimensional arrays where one dimension indicates a particular instrument and another dimension indicates a time ordered index indicating one of the last N updates, where N is a parameter defined by the user.

26. The system of claim 14 wherein the at least one data queue comprises an inter-process, multiple-producer/multiple-consumer distributed queue or a single-producer/multiple-consumer distributed queue, and wherein each market data event can be submitted by one or more processes and consumed by the first available process.