Prediction of stock price leveraging Arima model

In today`s world, more and more machine learning methods and prediction methods have been proposed. There are also lots of investors who choose the more difficult and complex models to use as technical analysis tools to predict stock prices. However, Rome wasn't built in a day. So, it`s necessary to learn the traditional models penetratingly. To have a more thorough understanding of classic models in the past, this paper provides a great way to analyze the ARIMA model. It explains the methods of fitting the ARIMA model step by step and improves the ARIMA model by adding seasonal parameters to fit the SARIMA model, enabling readers to better understand the advantages and disadvantages of this model. Although the results of the ARIMA model are unfortunately similar, and difficult to demonstrate its predictive power in images, the SARIMA model presents a trend prediction that conforms to people's imagine. As of today, the change in the price of Netflix's stock has been visible, which is different from the predicted price. Therefore, while making technical predictions, investors also need to combine fundamental analyses like the supply and demand balance, changes in interest rates, government regulations, macroeconomic indicators, and unique features of the industry in question, among others. Rather than relying solely on a model.