Multi-agent pre-trade analysis acceleration in FPGA

Eduardo Gerlein; T. M. McGinnity; Ammar Belatreche; Sonya Coleman; Yuhua Li

doi:10.1109/CIFEr.2014.6924082

Multi-agent pre-trade analysis acceleration in FPGA

Eduardo Gerlein
, T. M. McGinnity
, Ammar Belatreche
, Sonya Coleman
, Yuhua Li

University of Ulster

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

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.

Original language	English
Title of host publication	2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings
Editors	Antoaneta Serguieva, Dietmar Maringer, Vasile Palade, Rui Jorge Almeida
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	262-269
Number of pages	8
ISBN (Electronic)	9781479923809
DOIs	https://doi.org/10.1109/CIFEr.2014.6924082
State	Published - 14 Oct 2014
Externally published	Yes
Event	2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014 - London, United Kingdom Duration: 27 Mar 2014 → 28 Mar 2014

Publication series

Name	IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)

Conference

Conference	2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014
Country/Territory	United Kingdom
City	London
Period	27/03/14 → 28/03/14

Access to Document

10.1109/CIFEr.2014.6924082

Cite this

Gerlein, E., McGinnity, T. M., Belatreche, A., Coleman, S., & Li, Y. (2014). Multi-agent pre-trade analysis acceleration in FPGA. In A. Serguieva, D. Maringer, V. Palade, & R. J. Almeida (Eds.), 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings (pp. 262-269). Article 6924082 (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIFEr.2014.6924082

Gerlein, Eduardo ; McGinnity, T. M. ; Belatreche, Ammar et al. / Multi-agent pre-trade analysis acceleration in FPGA. 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings. editor / Antoaneta Serguieva ; Dietmar Maringer ; Vasile Palade ; Rui Jorge Almeida. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 262-269 (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)).

@inproceedings{2eca9f3e082647fa97f43c2336e56427,

title = "Multi-agent pre-trade analysis acceleration in FPGA",

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.",

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doi = "10.1109/CIFEr.2014.6924082",

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Gerlein, E, McGinnity, TM, Belatreche, A, Coleman, S & Li, Y 2014, Multi-agent pre-trade analysis acceleration in FPGA. in A Serguieva, D Maringer, V Palade & RJ Almeida (eds), 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings., 6924082, IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr), Institute of Electrical and Electronics Engineers Inc., pp. 262-269, 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr 2014, London, United Kingdom, 27/03/14. https://doi.org/10.1109/CIFEr.2014.6924082

Multi-agent pre-trade analysis acceleration in FPGA. / Gerlein, Eduardo; McGinnity, T. M.; Belatreche, Ammar et al.
2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings. ed. / Antoaneta Serguieva; Dietmar Maringer; Vasile Palade; Rui Jorge Almeida. Institute of Electrical and Electronics Engineers Inc., 2014. p. 262-269 6924082 (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Belatreche, Ammar

AU - Coleman, Sonya

AU - Li, Yuhua

PY - 2014/10/14

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N2 - 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.

AB - 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.

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ER -

Gerlein E, McGinnity TM, Belatreche A, Coleman S, Li Y. Multi-agent pre-trade analysis acceleration in FPGA. In Serguieva A, Maringer D, Palade V, Almeida RJ, editors, 2014 IEEE Conference on Computational Intelligence for Financial Engineering and Economics, CIFEr Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 262-269. 6924082. (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)). doi: 10.1109/CIFEr.2014.6924082

Multi-agent pre-trade analysis acceleration in FPGA

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