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This paper proposed a new evolutionary algorithm for generating trading rules on stock market, which is called Probabilistic Genetic Network Programming (P-GNP). P-GNP represents its solutions using graph structures based on probability. It has been clarified that P-GNP works well especially in dynamic environments. In the proposed hybrid stock trading model, P-GNP is applied to generating stock trading...
This paper proposes a new strategy β-GRA for portfolio selection in which the return and risk are considered as measures of strength in Genetic Relation Algorithm (GRA). Since the portfolio beta β efficiently measures the volatility relative to the benchmark index or the capital market, β is usually employed for portfolio evaluation or prediction, but scarcely for portfolio construction process. The...
In this paper, Robust Genetic Network Programming (R-GNP) for generating trading rules on stocks is described. R-GNP is a new evolutionary computation, which represents its solutions using graph structures. It has been clarified that R-GNP works well especially in dynamic environments. In the proposed hybrid stock trading model, R-GNP is applied to generating stock trading rules using variance of...
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