Technology Company Stock Trend Prediction Based on ARIMA Model

With the development of finance, more and more people are paying attention to stock price prediction, hoping to gain economic benefits from it. From the literature review, due to the complexity of stock trends, it is necessary to study the analysis of industry stocks. This paper studies the effectiveness of the autoregressive moving average model (ARIMA) for 5 stocks in the technology industry. Then, we will compare and parameterize the ARIMA model by using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). After the data processing, we find that the development prospects of four head technology companies have steadily increased due to years of economic accumulation and stable operation. However, as a technology company that has emerged in recent years, OpenAI is extremely susceptible to external factors such as academic fraud and AI replacing manual labor. Its stock trend has fluctuated greatly and its prospects are sluggish.