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Chaotic Type-2 Transient-Fuzzy Deep Neuro-Oscillatory Network (CT2TFDNN) for Worldwide Financial Prediction

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Quantum Finance

Abstract

In this chapter, the author proposed a chaotic type-2 transient-fuzzy deep neuro-oscillatory network with retrograde signaling (aka CT2TFDNN) for worldwide financial prediction.

© Portions of this chapter are reprinted from Lee (2019a), with permission of IEEE.

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Acknowledgements

The author wishes to thank Forex.com and AvaTrade.com for the provision of historical and real-time financial data. The author also wishes to thank Quantum Finance Forecast Center of UIC for the R&D supports and the provision of the channel and platform qffc.org for worldwide system testing and evaluation.

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Authors and Affiliations

  1. Division of Science and Technology, Beijing Normal University-Hong Kong Baptist University United International College (UIC), Zhuhai, Guangdong, China

    Raymond S. T. Lee

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  1. Raymond S. T. Lee
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Correspondence to Raymond S. T. Lee .

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Lee, R.S.T. (2020). Chaotic Type-2 Transient-Fuzzy Deep Neuro-Oscillatory Network (CT2TFDNN) for Worldwide Financial Prediction. In: Quantum Finance. Springer, Singapore. https://doi.org/10.1007/978-981-32-9796-8_12

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  • DOI: https://doi.org/10.1007/978-981-32-9796-8_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-32-9795-1

  • Online ISBN: 978-981-32-9796-8

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