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FOREX Rate Prediction Using Chaos, Neural Network and Particle Swarm Optimization

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Advances in Swarm Intelligence (ICSI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8795))

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Abstract

This paper presents two two-stage intelligent hybrid FOREX Rate prediction models comprising chaos, Neural Network (NN) and PSO. In these models, Stage-1 obtains initial predictions and Stage-2 fine tunes them. The exchange rates data of US Dollar versus Japanese Yen (JPY), British Pound (GBP), and Euro (EUR) are used to test the effectiveness of hybrid models. We conclude that the proposed intelligent hybrid models yield better predictions compared to the baseline neural networks and PSO in terms of MSE and MAPE.

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Author information

Authors and Affiliations

  1. Center of Excellence in CRM and Analytics, Institute for Development and Research in Banking Technology, Hyderabad, 500057, India

    Dadabada Pradeepkumar & Vadlamani Ravi

  2. SCIS, University of Hyderabad, Hyderabad, 500046, India

    Dadabada Pradeepkumar

Authors
  1. Dadabada Pradeepkumar
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  2. Vadlamani Ravi
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical & Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Computer Science Department, CINVESTAV-IPN, Mexico

    Carlos A. Coello Coello

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© 2014 Springer International Publishing Switzerland

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Pradeepkumar, D., Ravi, V. (2014). FOREX Rate Prediction Using Chaos, Neural Network and Particle Swarm Optimization. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_42

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  • DOI: https://doi.org/10.1007/978-3-319-11897-0_42

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11896-3

  • Online ISBN: 978-3-319-11897-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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