英文摘要 |
This study constructs an equity evaluation model by considering a firm's conditions, characteristics, and corporate governance. The model generalizes the key factors affecting the threshold of equity evaluation, and validates the importance of corporate conditions and characteristics on equity evaluations. Equity evaluation is very complicated and the application of OLS estimation to it may be overly simplified. Thus, this study adopts the Cubist regression tree model, which uses data characteristics to probe threshold variables and threshold values, to determine each equity evaluation model. The empirical results reveal that, according to the accuracy of the out-of-sample forecast, the MAPE value of the Cubist regression tree model is 36.54%, which is smaller than that value of 62.26% obtained by the OLS method. This result shows that the Cubist regression tree model is superior to the original estimation method for the equity evaluation model proposed by Ohlson (1995). A further comparison of existing and traditional models finds that considering corporate conditions and characteristics, as well as corporate governance mechanisms, one can obtain a more accurate construction of the equity evaluation model. In addition, financial variables seem to be more important than corporate governance factors and other firm characteristic factors. Moreover, as compared with traditional models, the Cubist regression tree model is found to be more accurate, more efficient, and more conducive in enhancing the quality of decision-making. The individual corporate conditions and characteristics are suggested to be incorporated into the construction of the equity evaluation model, which can lead to more accurate forecast results. The empirical findings may provide indication to management for what to be focused to strengthen corporate values and offer reference to regulatory bodies for formulating and mandating corporate governance policies. |