| dc.contributor | 政大經濟系 | en_US |
| dc.creator (作者) | 陳樹衡;H.-S Kao;J.-Z Lee | zh_TW |
| dc.creator (作者) | Chen,Shu-Heng;Kao,Hui-Sung ;Lee,Jan-Zan | - |
| dc.date (日期) | 2010 | en_US |
| dc.date.accessioned | 28-七月-2011 10:36:22 (UTC+8) | - |
| dc.date.available | 28-七月-2011 10:36:22 (UTC+8) | - |
| dc.date.issued (上傳時間) | 28-七月-2011 10:36:22 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/50620 | - |
| dc.description.abstract (摘要) | This study queries the linear information dynamics (LIM) assumption of the Ohlson (1995) valuation model, for it is as if the assumption of linear information dynamics (LIM) does not exist. Prior studies used the OLS model to estimate the relationship between firm value and corporate governance but in the wrong way. This may have been due to problems with the model’s specifications which led to the wrong empirical results. Thus, the purpose of this paper is to demonstrate that the artificial neural network (ANN) model is better than the OLS model. Moreover, we will examine whether a nonlinear model created by an artificial neural network (ANN) model will perform the best in predicting firm value. The empirical results indicate that the proposed neural network model can forecast firm values more accurately and have better explanatory power than the conventional OLS model. Even after 100 epochs of iterative simulation, the neural network still outperforms the OLS model in terms of explaining the training sample, verification sample, testing sample, and the holdout sample, with the confidence levels ranging from 99%~100%. The forecasted results are also tested using differential analysis. It is discovered that the MSE is extremely low, meaning that the accuracy of the neural network model is very high. The 100-epoch simulation and sensitivity test both empirically validate the robustness of the research results. The superior forecasting capability of neural networks found in this paper can be a reference for both the regulator concerned and for investors in decision making. | - |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | International Research Journal of Finance and Economics, 41, 68-92 | en_US |
| dc.subject (關鍵詞) | Neural network;Ohlson model;Corporate governance | - |
| dc.title (題名) | Corporate Governance and Equity Evaluation: Nonlinear Modeling via Neural Networks | en_US |
| dc.type (資料類型) | article | en |
