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政大典藏 > College of Commerce > Department of MIS > Theses > Item 140.119/86219

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/86219

Title:	以類神經網路與區別分析模式研究證券風格之分類、辨識與投資績效 A study of equity style classification, identification and investment strategy with neural networks and discriminant analysis
Authors:	林為元 Lin, Wei-Yuan
Contributors:	蔡瑞煌沈中華林為元 Lin, Wei-Yuan
Keywords:	人工類神經網路風格投資分析 Artificial neural networks Style analysis
Date:	1997
Issue Date:	2016-04-27 11:13:09 (UTC+8)
Abstract:	就目前所知，這是第一篇應用人工類神經網路在股票風格投資方面的研究。類神經網路在樣本內與樣本外的分類正確率皆優於區別分析，而且類神經網路在樣本內的訓練範例中達成了百分之百的分類正確率。此外，我們也解決了傳統方法無法展示股票風格動態的問題。 This is the first study of applying artificial neural networks (ANN) to classify and identify the equity styles. Regarding the accuracy, ANN outperforms discriminant analysis (DA) in all pure samples from 1987 to 1997. The ANN also commits the 100% classification accuracy for the in-sample training samples. In addition, the problem that traditional approach couldn`t show equity style dynamics was solved with ANN and DA.
Description:	碩士國立政治大學資訊管理學系 85356005
Source URI:	http://thesis.lib.nccu.edu.tw/record/#B2002001948
Data Type:	thesis
Appears in Collections:	[Department of MIS] Theses

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