Abstract
The increasing reliance on Computational Intelligence applications to predict stock market positions have resulted in numerous researches in financial forecasting and trading trend identifications. Stock market price prediction applications are required to be adaptive to new incoming data as well as have fast learning capabilities due to the volatility nature of market movements. This paper analyses stock market price prediction based on a Fuzzy Cerebellar Model Articulation Controller – Bayesian Ying Yang (FCMAC-BYY) neural network. The model is motivated from the Chinese ancient Ying-Yang philosophy which states that everything in the universe can be viewed as a product of a constant conflict between opposites, Ying and Yang. A perfect status is reached if Ying and Yang achieves harmony. The analyzed experiment on a set of real stock market data (Singapore Airlines Ltd – SIA) in the Singapore Stock Exchange (SGX) and Ibex35 stock index shows the effectiveness of the FCMAC-BYY in the universal approximation and prediction.
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Fu, J., Lum, K.S., Nguyen, M.N., Shi, J. (2007). Stock Prediction Using FCMAC-BYY. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_42
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DOI: https://doi.org/10.1007/978-3-540-72393-6_42
Publisher Name: Springer, Berlin, Heidelberg
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