Research on the Prediction Effect of Stock Closing Prices Based on Machine Learning

Zimeng Hao

doi:10.54691/bcpbm.v34i.3098

Authors

Zimeng Hao

DOI:

https://doi.org/10.54691/bcpbm.v34i.3098

Keywords:

machine learning; stock prediction; neural network.

Abstract

In recent years, with the rapid development of the global economy and stock market, stock investment has become one of the most commonly used financial management methods. The main goal of this paper is to use the Python programming language to build a stock forecast model based on machine learning technology, select the model whose forecast effect is most in line with the real value through the forecast results of various models, and use this model to analyze my country's stock market. with the forecast. Using LSTM, KNN, moving average model, and linear regression model to predict and analyze the closing price of Ping An Bank stock, and finally, detect the value of the RMSE of each model. Machine learning technology has high research value in stock analysis and can effectively reduce the impact and impact of some stock market disasters on the economy.

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