Valuation Of High Growth Enterprises Based On Three Phase Correction Model Of EVA

With the process of economic globalization, corporate growth becomes an important source of competitiveness for enterprises. High-growth enterprises play a more and more important role in economic development. Domestic and foreign scholars have studied on the EVA model for a long time and get lots of theoretical and practical conclusion. Some believe EVA valuation model can explain the process of value creation and fully reflect the actual business operating conditions. According to the different forecasting growth, the EVA model can be divided into sustainable growth model, two-stage model and three-stage model. Considering the characteristics of high-growth companies, high-growth companies often experience long growth phase, transitional phase and stable stage. In theory, the integrating of EVA model and stage model will be feasible for the valuation of high-growth companies. Therefore, this paper chose the three-stage EVA to evaluate the valuation of high-growth companies. Stage forecasting growth reflects the future data, while the three-stage EVA model bases on historical financial data. So the historical factors such as R & D capabilities can’t be ignored. Therefore, in order to better assess the value of high-growth enterprises, the potential growth factor was introduced to correct the model.Based on the enterprise value theory, EVA theory and high-growth companies’ characteristics, the three-stage EVA model has been selected to evaluate the high growth companies. In the empirical section,19 high-growth enterprises of the GEM have been selected. The historical financial data was selected to assess corporate value by building regression models. We compared the corporate value before and after using the modified three-stage EVA model.Through theoretical analysis and empirical testing, this paper finally draw the following conclusions:the theoretical value and market value have high correction, while the theoretical value assessed by the adjusted model remains higher; the explanatory power before and after adjustment are 70.8 percent and 77.7 percent. In a word, the adjusted model has higher explanatory power and applicability.