Research Article
Time Series Based Data Analysis and Prediction for the Relationship Between China Concept Stock Price and Government Regulatory Policy
@INPROCEEDINGS{10.4108/eai.28-10-2022.2328415, author={Jiahe Fang and Jianheng Huang}, title={Time Series Based Data Analysis and Prediction for the Relationship Between China Concept Stock Price and Government Regulatory Policy }, proceedings={Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China}, publisher={EAI}, proceedings_a={FFIT}, year={2023}, month={4}, keywords={stock price; government regulatory policy; garch model; empirical distribution model; lstm model}, doi={10.4108/eai.28-10-2022.2328415} }- Jiahe Fang
Jianheng Huang
Year: 2023
Time Series Based Data Analysis and Prediction for the Relationship Between China Concept Stock Price and Government Regulatory Policy
FFIT
EAI
DOI: 10.4108/eai.28-10-2022.2328415
Abstract
Government regulatory policy often significantly impacts the stock price trend, which is rarely studied in past studies. This research explored the relationship between China concept stock price and Chinese government regulatory policy. The generalized autoregressive conditional heteroskedasticity (GARCH) model, empirical distribution model, and Long Short Term Memory (LSTM) machine learning model were used to examine the influence of Chinese government policy on China concept stock price using data and policy information from credible sources. Based on the model results, this study also came up with valuable conclusions and recommendations for investors and the government. For financiers, investing in China concept real estate stocks is advantageous in the short term. Set a 10% stop loss range and a 20% stop profit range based on the empirical distribution of effect percentage. The experimental results suggest that the government releases policies in a particular industry less frequently to ensure that the market works smoothly.