Abstract
We propose a knowledge discovery process for multi-factor portfolio management on a financial decision support system. We first construct an OPen Intelligent Computing System (OPICS) to support time series management and knowledge management. A system, Cyclone, which efficiently supports financial applications, is developed under the OPICS. We then introduce a data mining solution for equity portfolio construction using the simulated annealing algorithm. Two data sets consist of small stocks ranging from 11/86 to 10/91 and from 6/93 to 5/96 are used. The corresponding rates of return of Russell 2000 index are collected as benchmarks for evaluation based on the Sharpe ratios and the turnover ratios. The result shows that the simulated annealing algorithm outperforms both the market index and the gradient maximization method.
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© 1999 Springer-Verlag Berlin Heidelberg
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Lu, YC., Cheng, H. (1999). Towards Automated Optimal Equity Portfolios Discovery in a Knowledge Sharing Financial Data Warehouse. In: Zhong, N., Skowron, A., Ohsuga, S. (eds) New Directions in Rough Sets, Data Mining, and Granular-Soft Computing. RSFDGrC 1999. Lecture Notes in Computer Science(), vol 1711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48061-7_55
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DOI: https://doi.org/10.1007/978-3-540-48061-7_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66645-5
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