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Multi-agent pre-trade analysis acceleration in FPGA

Gerlein, E, McGinnity, TM, Belatreche, A, Coleman, SA and Li, Y 2014, Multi-agent pre-trade analysis acceleration in FPGA , in: The Institute of Electrical and Electronics Engineers (IEEE) : Computational Intelligence for Financial Engineering and Economics Conference, 27-28 March 2014, London.

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Abstract

Electronic trading in global markets and exchanges requires sophisticated communication and data management systems. Novel computational infrastructures and trading strategies are required to support the massive amount of incoming streaming data, where the main problem is in latency management. Multi-agent Systems have been recognized as a promising solution to address complex problems in many areas such as biology, social sciences and financial markets and may provide powerful and flexible solutions for implementing trading engines. In addition, reconfigurable hardware based on Field Programmable Gate Arrays (FPGAs) offers many important performance benefits over software implementations,such as reducing decision making latency and high-throughput data processing. Robust and scalable trading engines can be developed by leveraging the benefits of reconfigurable FPGA platforms. This paper presents a multi-agent architecture in reconfigurable hardware for financial applications and the implementation of a trading engine for pre-trade analysis as a validation scenario. Performance results show that calculation of technical indicators and trading strategy evaluation to generate trading signals with a latency of 550 ns is achievable.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Computational Intelligence for Financial Engineering & Economics (CIFEr), 2104 IEEE Conference
Publisher: The Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Related URLs:
Funders: Non funded research
Depositing User: Yuhua Li
Date Deposited: 19 Jun 2015 18:26
Last Modified: 05 Apr 2016 18:18
URI: http://usir.salford.ac.uk/id/eprint/33096

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