Issue |
SHS Web Conf.
Volume 181, 2024
2023 International Conference on Digital Economy and Business Administration (ICDEBA 2023)
|
|
---|---|---|
Article Number | 02027 | |
Number of page(s) | 6 | |
Section | Financial Analysis and Stock Market Strategies | |
DOI | https://doi.org/10.1051/shsconf/202418102027 | |
Published online | 17 January 2024 |
Research on Stock Market Decision Making based on Price-to-Earnings Ratio–Taking Shenzhen stock as an example
Central South University, School of Mathematics and Statistics, 410006, China
* Corresponding author: zxyzxy@csu.edu.cn
Taking Shenzhen stock as an example, this paper explores the opportunity for high returns in the stock market through the study of the price-to-earnings ratio, and finally determines the optimal stock market decision. By trying different numerical value on the price-to-earnings ratio and calculating the total return based on historical data, it is obtained that buying when the price-to-earnings ratio is lower than 156 and selling when it is higher than 224.5 can get the highest return. However, in the following general study of high-yield decisions, it is found that all decisions are concentrated in the rapid rise in stock prices caused by “reform cattle” in 2015 in China. Therefore, in order to study more general strategies, the scope and difference of price-to-earnings ratio are redrawn and two feasible decision-making methods are obtained: risk-averse decision-making and risk-preference decision-making. Both two decisions are suitable in a relatively stable stock market, and can earn almost the same profit theoretically, so investors can choose any of them based on their preferences.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.