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

機構典藏 > College of Engineering > Graduate Institute & Department of Civil Engineering > Journal Article > Item 987654321/117137

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/117137

Title:	Building growth and value hybrid valuation model with errors-in-variables regression
Authors:	Kong, Derick;Lin, Cheng Ping;Yeh, I-Cheng;Chang, Wei
Keywords:	Valuation;book value;return on equity;market value;errors-in-variables JEL CLASSIFICATION: G12;G14
Date:	2018-06-29
Issue Date:	2019-09-26 12:10:46 (UTC+8)
Publisher:	Taylor & Francis
Abstract:	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.
Relation:	Applied Economics Letters 26(5), p.370-386
DOI:	10.1080/13504851.2018.1486005
Appears in Collections:	[Graduate Institute & Department of Civil Engineering] Journal Article

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