Empirical Study on Forecast of Large Stock Dividends of Listed Companies Based on Integrated Learning.

In our country's stock market, the subject of large stock dividends is highly sought after by small and medium investors, but there is also the market chaos which is hyped by the concept of high-send transfers. How to use the financial data of listed companies to mine potential stocks is undoubtedly of great significance. The seven-year financial index of 2 158 listed manufacturing companies is used as the research data, and the prediction model of large stock dividends of listed companies is built by sampling, feature selection and integrated learning algorithm, and the empirical research is carried out. The results show that both sampling and feature selection methods can effectively improve the performance of the integrated prediction model. Compared with the redundant information in the dataset, the data imbalance has a more significant influence on the accuracy of model prediction. The combination model of ADASYN+mRMR+XGBoost achieves the best results, and the classification accuracy rate of large stock dividends samples reaches 84.96%. Investors are recommended to give priority to this combination model to predict the implementation of high send-to stocks by listed companies. [ABSTRACT FROM AUTHOR]