Enhanced stock price variation prediction via DOE and BPNN-based optimization

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題名:	Enhanced stock price variation prediction via DOE and BPNN-based optimization
作者:	謝素真 Chen, Hsieh Su
貢獻者:	財務管理學系 Finance
關鍵詞:	Stock price forecasting;Back-propagation neural network;Design of experiment;Taguchi method;Parameter optimization
日期:	2011
上傳時間:	2014-06-27 10:42:35 (UTC+8)
摘要:	Stock price variation predictions are at the core of many research issues, and neural networks (NNs) are widely applied and were proven to be more efficient than time series forecasting for stock price forecasting. However, this type of research always de
顯示於類別:	[財務管理學系] 期刊論文

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