Building valuation model of enterprise values for construction enterprise with quantile neural networks

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.