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政大機構典藏 > 商學院 > 會計學系 > 學位論文 > Item 140.119/86575

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/86575

Title:	盈餘預測準確度之實證研究：類神經網路與時間序列之比較
Authors:	劉元君
Contributors:	吳安妮蔡瑞煌劉元君
Keywords:	盈餘預測類神經網路
Date:	1997
Issue Date:	2016-04-27 14:06:03 (UTC+8)
Abstract:	盈餘預測不僅是公司本身管理決策的重要依據，更是廣大投資人做投資決策時仰賴甚深之基本面分析工具。過去的研究試圖以各種時間序列之計量方法找出較準確的盈餘預測，而本研究引進一個新的預測工具--類神經網路系統，希望比較傳統的預測盈餘計量模式--帶趨勢隨機漫步，以及類神經網路系統--BP、RNBP 對盈餘預測之能力何者較優。 Earning forecasting is an important information used by corporation management and investors. Researches in the past tempt to forecast earnings more accurately with time series models. My research introduces a new tool--Artificial Neural Networks--to predict earnings, and will be compared with the traditional time series model--random walk.
Description:	碩士國立政治大學會計學系 85353001
Source URI:	http://thesis.lib.nccu.edu.tw/record/#B2002002131
Data Type:	thesis
Appears in Collections:	[會計學系] 學位論文

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