Utilizations of the ARIMA Model: Empirical Findings from the Nasdaq Index

The Nasdaq Composite is one of the world's most watched stock indices and assumes an important role in the global financing trading process. Forecasting of stocks has always been the focus of scholars' research, but due to factors such as market sentiment fluctuations, it is difficult to obtain effective forecasting results using a macro approach. With the help of technological development, data has become more accessible. Scholars have started using statistical models to make predictions on stock prices. This study uses autoregressive integrated moving average (ARIMA) prediction model to forecast the Nasdaq composite index. After parametric statistics, fitting and residual tests, it was determined that the ARIMA (2,1,2) model produced the most accurate predictions. The results of this study enriched the prediction results of the relevant Nasdaq Composite Index for the ARIMA model, broadened the field of application of the ARIMA model, and provided investors with investment strategy references.