Technical Papers
Sep 11, 2015

Building Valuation Model of Enterprise Values for Construction Enterprise with Quantile Neural Networks

Publication: Journal of Construction Engineering and Management
Volume 142, Issue 2

Abstract

This paper aims to overcome the drawbacks of current business valuation models. The authors have developed a novel model, a growth value model, by employing the income-asset-hybrid-based approach and with the application of quantile neural networks. This model is greatly strengthened by the main assumption of stockholders equity growth rates following the mean reversion principle. This makes the discounted present value of stockholders equity in the infinite future converge to a bounded value. The empirical findings have significant contributions to the business valuation of property development and construction industries. First, they include the business valuation model of the aforementioned two industries is quite different from those of other industries. The enterprise values of these two can be significantly overestimated if the business valuation model for total industry is applied. Second, they also include the patterns of price-to-book value ratio (PBR) curves that indicate that the growth value model is highly useful and effective in various industries only if the return on equity ratio (ROE) is larger than zero.

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Information & Authors

Information

Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 142Issue 2February 2016

History

Received: Feb 13, 2015
Accepted: Jul 20, 2015
Published online: Sep 11, 2015
Published in print: Feb 1, 2016
Discussion open until: Feb 11, 2016

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Authors

Affiliations

Yi-Cheng Liu [email protected]
Associate Professor, Dept. of International Business, Tamkang Univ., 151 Yingzhuan Rd., Tamsui District, New Taipei City 25137, Taiwan. E-mail: [email protected]
I-Cheng Yeh [email protected]
Professor, Dept. of Civil Engineering, Tamkang Univ., 151 Yingzhuan Rd., Tamsui District, New Taipei City 25137, Taiwan (corresponding author). E-mail: [email protected]

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