Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory
Author:
Affiliation:
1. Graduate school of Engineering, Tottori University
2. FUJITSU LIMITED
Publisher
Institute of Electrical Engineers of Japan (IEE Japan)
Subject
Electrical and Electronic Engineering
Link
http://www.jstage.jst.go.jp/article/ieejeiss/132/3/132_3_455/_pdf
Reference32 articles.
1. (1) C. Frayn: “Genetic Programming in Finance”, Proceedings of the 4th International Workshop on Computational Intelligence in Economics and Finance(CIEF 2005), pp. 21-25 (2005)
2. (2) S. Chen, T. Kuo, and Y. Shieh: “Genetic Programming: A Tutorial”, Genetic Algorithms and Genetic Programming in Computational Finance, pp. 55-80, Springer (2002)
3. (3) Y. Chen, S. Mabu, K. Shimada, and K. Hirasawa: “A genetic network programming with learning approach for enhanced stock trading model”, Expert Systems with Applications, Vol. 36, No. 10, pp. 12537-12546 (2009-12)
4. (4) S. Martinez-Jaramillo and E. P. K Tsang: “An Heterogeneous, Endogenous and Coevolutionary GP-Based Financial Market”, IEEE Trans. on Evolutionary Computation, Vol. 13, No. 1, pp. 33-55 (2009)
5. (5) S. Chen, P. Wang, and T. Kuo: “Failure of Genetic-Programming Induced Trading Strategies: Distinguishing between Efficient Markets and Inefficient Algorithms”, Computational Intelligence in Economics and Finance, Vol. II, pp. 169-182 (2007)
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