Forecasting and Error Factor Analysis of the CSI 300 Index Based on the ARIMA Model

Abstract

The CSI 300 stock index futures are futures contracts with the CSI 300 Index as the underlying asset. The CSI 300 Index represents the overall trend of the Chinese stock market, consolidating a representative variety of stocks for analysis. It is generally believed to reflect the highs and lows of the Chinese stock market, with individual stock price anomalies having limited impact on the overall index. Therefore, studying stock price fluctuations through technical means, focusing on the CSI 300 Index as the research subject, is more appropriate. Correspondingly, it also provides guidance for portfolio operations and institutional or fund investments. Specifically, it plays a guiding role in the research of stock index futures based on the CSI 300 Index. Hence, this paper employs the ARIMA model in time series analysis to establish a model for the CSI 300 Index. Utilizing mathematical methods to process the daily CSI 300 data sampled from January 3, 2023, to December 29, 2023, a one-year period, the ARIMA model is developed using the Python programming language based on economic theory and econometric knowledge. By testing, adjusting, and estimating the model, a reasonable economic interpretation of the model is provided to forecast the CSI 300 Index. Through the analysis of the actual results obtained from this model and the reasons for the differences between the actual values of the CSI 300 Index and the model's predicted values, this study aims to offer valuable insights for enterprises and investors in making relevant decisions.