Hikvision Price Prediction based on ARIMA, OLS Multiple Regression and Random Forest

Abstract

As a matter of fact, stock price prediction is quite crucial for investors to gain extra return in financial market. Thanks to the rapid development of the machine learning techniques. With this in mind, this paper takes Hikvision as sample data to study the stock forecast situation based on ARIMA time series model, OLS multiple regression, random forest machine learning these three models, Hikvision as a sample is also fancy the high growth of the company, and the stock forecast meets the current needs, which is of great significance, and finally the random forest machine learning and ARIMA time series model are obtained by comparison finally predict better effects relatively, through the computer model to predict, compared with the manual, has a higher running speed, in order to achieve better prediction results, in line with the current needs, is of great significance. Overall, these results shed light on guiding further exploration of price prediction.