Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction

作者：

Highlights：

• Integrating metaheuristics and ANN for improved stock price prediction.

• Both topology of ANN and the number of inputs are optimized.

• The number of the input variables is reduced to almost its half.

• HS-ANN has better generalization ability than GA-ANN model.

• Proposed methodologies outperformed both in statistical and financial terms.

摘要

•Integrating metaheuristics and ANN for improved stock price prediction.•Both topology of ANN and the number of inputs are optimized.•The number of the input variables is reduced to almost its half.•HS-ANN has better generalization ability than GA-ANN model.•Proposed methodologies outperformed both in statistical and financial terms.

论文关键词：Artificial Neural Network,Genetic Algorithm,Harmony Search Algorithm,Stock market price

论文评审过程：Received 1 December 2014, Revised 17 September 2015, Accepted 18 September 2015, Available online 28 September 2015, Version of Record 10 November 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.029