Application of Improved Grammatical Evolution to Stock Price Prediction
نویسندگان
چکیده
Grammatical Evolution (GE), which is one of the evolutionary computations, aims to find function, program or program segment satisfying the design objective. This paper describes the improvement of the Grammatical Evolution according to Stochastic Schemata Exploiter (GE-SSE) and its application to symbolic regression problem. Firstly, GE-SSE is compared with original GE in symbolic regression problem. The results show that GE-SSE has faster convergence property than original GE. Secondly, GE-SSE is applied for the stock price prediction as the actual application of the GE-SSE. Keywords—Grammatical Evolution, Stochastic Schemata Exploiter, Symbolic Regression, Stock Price Prediction.
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