Building growth and value hybrid valuation model with errors-in-variables regression

淡江大學機構典藏 > 工學院 > 土木工程學系暨研究所 > 期刊論文 > Item 987654321/117137

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题名:	Building growth and value hybrid valuation model with errors-in-variables regression
作者:	Kong, Derick;Lin, Cheng Ping;Yeh, I-Cheng;Chang, Wei
关键词:	Valuation;book value;return on equity;market value;errors-in-variables JEL CLASSIFICATION: G12;G14
日期:	2018-06-29
上传时间:	2019-09-26 12:10:46 (UTC+8)
出版者:	Taylor & Francis
摘要:	Growth value model (GVM) considers stock intrinsic value as the synergy of book value and return on equity (ROE), which contains two parameters, value factor and growth factor. This study addresses the problem of independent variables having measurement errors by utilizing errors-in-variables regression to estimate accurate model parameters. Research findings show the following: (1) The regression curve derived by traditional regression analysis exhibits severe bias. Errors-in-variables regression is capable of correcting the bias. (2) Large-scale firms exhibit lower value factor and higher growth factor, which indicates that large-scale firms possess better profit persistence.
關聯:	Applied Economics Letters 26(5), p.370-386
DOI:	10.1080/13504851.2018.1486005
显示于类别:	[土木工程學系暨研究所] 期刊論文

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