Stock market information disclosure and risk management in the perspective of data fusion——Take market manipulation identification as an example - Yao, Sihan; Li, Aihua; Liu, Zhidong (Procedia computer science, 2023)
The stock market, one of the most important trading platforms, has been subject to many market manipulation practices since its emergence. At present, the phenomenon of market manipulation has become an obstacle that restricts the development of the stock market. Based on the data fusion background, this paper conducts a study on the A-share listed companies publicly investigated and confirmed as market manipulation by CSRC in China from 2018-2022 as a manipulation sample under the perspective of fusion of data, model and decision, to provide theoretical support for regulators to identify market manipulation under the new trend. The results show that: ① Comparing with single financial data, different types of models respond to text indicators significantly differently. More than that, a reasonable addition of text dimensions can optimize the model performance; ② Comparing with a single base classifier, integrated models generally have better recognition performance. In addition, this effect can be deeply improved with the diversification of the base classifier.