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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cho, S., Han, C., Han, D., Kim, H.: Web Based Keystroke Dynamics Identity Verification using Neural Network. Journal of Organizational Computing and Electronic Commerce. Vol. 10, No. 4, December, 2000.
Baek, J., Cho, S.: Time to Jump in?: Long Rising Pattern Detection in KOSPI 200 Future Using an Auto-Associative Neural Network, ICONIP, pp. 160~165, Shanghai, China, Nov. 14–17, 2001.
Dempster, M.A.H., Jones, C.M.: Can technical pattern trading be profitably automated? 1. The channel & 2. Head and shoulders, Working Paper, Judge Institute of Management, University of Cambridge, 1999 (revised as: 2001 Can channel pattern trading be automated? Euro. J. Finance at press)
Bishop, C.: Neural Networks for Pattern Recognition. Oxford: Clarendon press, 1994.
Breiman, L.: Bagging Predictors, Machine Learning, Vol. 24, No. 2, pp. 123–140, 1994.
Kramer, M.A.: Nonlinear Principal Components Analysis Using Auto Associative Neural Networks, AIChe J., Vol 37, No. 2, pp. 233–243, 1991
Lo, A.W., Mamaysky, H., Wang, J.: Foundation of Technical Analysis: Computational Algorithms, Statistical Inference and Empirical Implementation. Journal of Finance, Vol LV, NO4, pp1705–1765, 2000
Deboeck, G.S., Cader, M.: Pre-and Postprocessing of Financial Data, Trading on The Edge, John Wiley & Sons, Inc, pp 27–44, 1994
Jang, G.S., Lai, F.: Intelligent Trading of an Emerging Market, Trading on The Edge, John Wiley & Sons, Inc, pp 80–101, 1994
Lane, G.C.: Trading Strategies, Future Symposium International, 1984
Murphy, J. J.: Technical Analysis of The Financial Markets: A Comprehension Guide to Trading Methods and Applications, New York Institute of Finance. 1999
Borsanaliz.com company, Tools for technical analysis stock exchange, http://www.geocities.com/ wallstreet/floor/ 1035/formations.htm, 2000
Korea Stock Exchange, KOSPI & KOSPI 200, http://www.kse.or.kr, 2000
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/3-540-45675-9_53
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44025-3
Online ISBN: 978-3-540-45675-9
eBook Packages: Springer Book Archive