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Optimising Order Splitting and Execution with Fuzzy Logic Momentum Analysis

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Electrical Engineering and Applied Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 90))

Abstract

This study proposes a new framework for high frequency trading using a fuzzy logic based momentum analysis system. An order placement strategy will be developed and optimised with adaptive neuro fuzzy inference in order to analyse the current “momentum” in the time series and to identify the current market condition which will then be used to decide the dynamic participation rate given the current traded volume. The system was applied to trading of financial stocks, and tested against the standard volume based trading system. The results show how the proposed Fuzzy Logic Momentum Analysis System outperforms the standard volume based systems that are widely used in the financial industry.

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Notes

  1. 1.

    An interdealer broker is a member of a major stock exchange who is permitted to deal with market makers, rather than the public, and can sometimes act as a market maker.

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Acknowledgments

The authors would like to thank Mr. Phil Hodey, the head of portfolio management and electronic trading at ICAP plc for providing the tick data used in the simulations of the system and for his invaluable support and guidance.

Author information

Authors and Affiliations

  1. Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

    Abdalla Kablan & Wing Lon Ng

Authors
  1. Abdalla Kablan
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  2. Wing Lon Ng
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Corresponding author

Correspondence to Abdalla Kablan .

Editor information

Editors and Affiliations

  1. The University of Hong Kong, Hung To Road, Hong Kong, 3739, China, People's Republic

    Sio-Iong Ao

  2. School of Engineering, Applied Mathematics and Computing, Cranfield University, Cranfield, MK43 0AL, Montserrat

    Len Gelman

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Kablan, A., Ng, W.L. (2011). Optimising Order Splitting and Execution with Fuzzy Logic Momentum Analysis. In: Ao, SI., Gelman, L. (eds) Electrical Engineering and Applied Computing. Lecture Notes in Electrical Engineering, vol 90. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1192-1_31

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  • DOI: https://doi.org/10.1007/978-94-007-1192-1_31

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1191-4

  • Online ISBN: 978-94-007-1192-1

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