Empirical Analysis of Establishing an Intrinsic Value Evaluation Model of Listed Companies Based on Multivariate Linear Regression Method
- 10.2991/amsm-16.2016.14How to use a DOI?
- value investing; intrinsic value evaluation model; listed company
Enterprise value assessment is a hotspot of research on modern financial problems; profound changes have taken place in China's stock market system and investment environment, in the direction of more fair, effective and standardized development, Chinese stock market is more and more showing the intrinsic investment value. On the basis of the value evaluation model of the mainstream asset appraisal method in the stock market, combining the profitability of the stock, the growth and the domestic current situation of the stock market, this article builds the suitable mathematical model for the evaluation of the intrinsic value of listed companies of China stock market, and selects the empirical model effect on listed companies in the Shanghai market. Through empirical analysis, it is found that: in this paper, the evaluation results from the construction of mathematical model of the intrinsic value of Shanghai a-share listed companies are in accordance with the reality, and are of certain rationality. At the same time, it is also found that the evaluation results of blue-chip shares with the model of correlation degree is higher, and the evaluation results of new shares and small-cap stocks in correlation with its share price a bit weak. This may be related to new shares and small-cap stocks in the full-bodied market hype atmosphere and share price volatility.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jiaxin Wang AU - Yanxia Wang AU - Donglin Wang PY - 2016/05 DA - 2016/05 TI - Empirical Analysis of Establishing an Intrinsic Value Evaluation Model of Listed Companies Based on Multivariate Linear Regression Method BT - Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling PB - Atlantis Press SP - 57 EP - 60 SN - 2352-538X UR - https://doi.org/10.2991/amsm-16.2016.14 DO - 10.2991/amsm-16.2016.14 ID - Wang2016/05 ER -