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    Title: Building Valuation Model of Enterprise Values for Construction Enterprise with Quantile Neural Networks
    Authors: Yi-Cheng Liu;I-Cheng Yeh
    Keywords: Quantile regression analysis;neural network;construction enterprise;enterprise value
    Date: 2016/02/01
    Issue Date: 2016-04-22 13:23:53 (UTC+8)
    Publisher: American Society of Civil Engineers
    Abstract: This paper aims to overcome the drawbacks of current business valuation models. The authors have developed a novel model: Growth Value Model by employing the Income-Asset-Hybrid-based approach and with the application Quantile Neural Networks. This model is greatly strengthened with 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. They include (1) the business valuation model of the above 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. (2) The patterns of Price-to-Book value ratio (PBR) curves 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.
    Relation: Journal of Construction Engineering and Management 142(2), 04015075(12 pages)
    DOI: 10.1061/(ASCE)CO.1943-7862.0001060
    Appears in Collections:[土木工程學系暨研究所] 期刊論文

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