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An Up-Trend Detection Using an Auto-Associative Neural Network: KOSPI200 Futures

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2412))

Abstract

We propose a neural network based up-trend detector. An auto-associative neural network was trained with “up-trend” data obtained from the KOSPI 200 future price. It was then used to predict an up-trend. Simple investment strategies based on the detector achieved a two year return of 19.8 % with no leverage.

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© 2002 Springer-Verlag Berlin Heidelberg

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Baek, J., Cho, S. (2002). An Up-Trend Detection Using an Auto-Associative Neural Network: KOSPI200 Futures. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_53

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  • DOI: https://doi.org/10.1007/3-540-45675-9_53

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44025-3

  • Online ISBN: 978-3-540-45675-9

  • eBook Packages: Springer Book Archive

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