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Intraday high-frequency FX trading with adaptive neuro-fuzzy inference systems

Author

Listed:
  • Abdalla Kablan
  • Wing Lon Ng

Abstract

This paper introduces an adaptive neuro-fuzzy inference system (ANFIS) for financial trading, which learns to predict price movements from training data consisting of intraday tick data sampled at high frequency. The empirical data used in our investigation are five-minute mid-price time series from FX markets. The ANFIS optimisation involves back-testing as well as varying the number of epochs, and is combined with a new method of capturing volatility using an event-driven approach that takes into consideration directional changes within pre-specified thresholds. The results show that the proposed model outperforms standard strategies such as buy-and-hold or linear forecasting.

Suggested Citation

  • Abdalla Kablan & Wing Lon Ng, 2011. "Intraday high-frequency FX trading with adaptive neuro-fuzzy inference systems," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 2(1/2), pages 68-87.
    • Handle: RePEc:ids:ijfmkd:v:2:y:2011:i:1/2:p:68-87
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    Citations

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    Cited by:

    1. Aloud, Monira & Tsang, Edward & Olsen, Richard & Dupuis, Alexandre, 2012. "A directional-change event approach for studying financial time series," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-17.
    2. Edward P. K. Tsang & Ran Tao & Antoaneta Serguieva & Shuai Ma, 2017. "Profiling high-frequency equity price movements in directional changes," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 217-225, February.
    3. Monira Essa Aloud, 2016. "Time Series Analysis Indicators under Directional Changes: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 55-64.
    4. Ma, Junjun & Xiong, Xiong & He, Feng & Zhang, Wei, 2017. "Volatility measurement with directional change in Chinese stock market: Statistical property and investment strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 169-180.

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