Abstract
Accurately predicting the trend of stock return rate is a hot research issue. With the development of artificial intelligence, machine learning, big data and other technologies, it brings new potential to the prediction of the stock market. In order to accurately predict the trend of stock return, this paper mainly constructs the time series ARMA model and random forest model, uses the stacking method to fuse the models, and predicts the daily return of Yangtze River Electric Power stock. The final fusion model has an MSE of 1.757 on the training set and 1.274 on the test set. The overall prediction error of the model is within an acceptable range. At the same time, the fused model can weaken the problem of underfitting of a single model, which provides a valuable reference for model optimization research.
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