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Construction of Valuation System with Chinese Characteristics Based on Entropy Weight Method and K-means

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DOI: 10.23977/ferm.2023.061119 | Downloads: 37 | Views: 372

Author(s)

Chengxin Ye 1, Weiming Li 1, Yongxuan Ye 2, Zhaokang He 3, Wanyu Zheng 1

Affiliation(s)

1 Guangzhou Maritime University, Guangzhou, Guangdong, China
2 Guangdong University of Finance, Guangzhou, Guangdong, China
3 Zhuhai College of Science and Technology, Zhuhai, Guangdong, China

Corresponding Author

Weiming Li

ABSTRACT

"Stock valuation" is one of the main reference factors for investment in the securities stock market. With the continuous development of China's securities market, the traditional "price-earnings ratio valuation model" is no longer adapted to the requirements of China's market, the logic of stock valuation in China's securities market needs to be redefined in order to enable investors to make better decisions. In this regard, Yi Huiman, Chairman of the China Securities Regulatory Commission (CSRC), has put forward the idea of constructing a valuation system with Chinese characteristics, so as to enable real quality stocks, i.e., those with high dividends, low valuation and good growth, to obtain more valuation and win the attention of investors. Therefore, this paper is dedicated to constructing a valuation system with Chinese characteristics and redefining the valuation model to help investors better value stocks in the Chinese stock market. After that, this paper categorizes the valuation stocks with Chinese characteristics in Shanghai and Shenzhen A-shares, and obtains two types of stocks: long-term investment type and short- and medium-term investment type, which help investors in stock investment in Chinese stock market.

KEYWORDS

Valuation System with Chinese Characteristics, Entropy-based TOPSIS Method, K-Means Cluster Analysis, Investment Strategy

CITE THIS PAPER

Chengxin Ye, Weiming Li, Yongxuan Ye, Zhaokang He, Wanyu Zheng, Construction of Valuation System with Chinese Characteristics Based on Entropy Weight Method and K-means. Financial Engineering and Risk Management (2023) Vol. 6: 132-139. DOI: http://dx.doi.org/10.23977/ferm.2023.061119.

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