Assessing the stock price variation based on the DOE-based optimization of neural network

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Please use this identifier to cite or link to this item: http://chur.chu.edu.tw/handle/987654321/41049

Title:	Assessing the stock price variation based on the DOE-based optimization of neural network
Authors:	謝玲芬 Hsieh, Ling-Feng
Contributors:	運輸科技與物流管理學系 Transportation Technology and Logistics Management
Keywords:	Stock price forecasting;Back-propagation neural network;Design of experiment;Financial Statements
Date:	2011
Issue Date:	2014-07-28 11:50:06 (UTC+8)
Abstract:	Stock return predictions are at the core of many research issues, and neural networks (NNs) are widely applied and were proven to be efficient for stock price forecasting. However, the stock return prediction by NNs always determines the parameter setting
Appears in Collections:	[Department of Transportation Technology and Logistice Management] Journal Articles

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