Affiliation:
1. Shanghai Jiaotong University
Abstract
Establishment of one process and some ameliorations of decision tree’s algorithm in order to predict the second day’s price change. The experiment builds a J48 tree, which is comfortable with continuous attributes, based on 10 years historical stock prices. After careful selection and preprocessing of financial data, high prediction accuracy is obtained. An introduction of dynamic-constructed tree reduces tree’s cost, and increases prediction’s quality on accuracy as well as average error distance.
Publisher
Trans Tech Publications, Ltd.
Reference6 articles.
1. Boris Kovalerchuk and Evgenii Vityaev, in: Data Mining For Financial Applications [M]. Springer, (2005).
2. J. R. Quinlan, in: Improved Use of Continuous Attributes in C4. 5 [D]. Sydney: University of Sydney, (2006).
3. J. Hull, in: Options, Futures and Other Derivatives. 6th edition [M]. New Jersey: Prentice Hall, (2005).
4. Damiano Brigo and Fabio Mercurio, in: Interest Rate Models - Theory and Practice: With Smile, Inflation and Credit [M]. Springer, (2007).
5. Kohavi, R. and John, G. H, in: Automatic parameter selection by minimizing estimated error [D]. San Francisco: Morgan Kaufmann, (1995).
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2 articles.
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