The comprehensive analysis of Googles stock using ARIMA model

Abstract

Predicting stock prices has long been a subject of keen interest due to its financial implications and inherent complexity. The examination of existing literature suggests the need for a focused study encompassing a diverse spectrum of stocks within a specific sector. In this research, the author evaluates the efficacy of the AutoRegressive Integrated Moving Average (ARIMA) model in forecasting Googles stock performance. The data used in this paper comes from the Chinese corn market price of 2018 to October 2023. The selection of the ARIMA model is based on its widespread acceptance and straightforward nature. This paper also explores how the accuracy of predictions is influenced by various historical data points. Simultaneously, the projections indicate that Googles stock is poised for continued growth in the upcoming weeks. This investigation aims to provide valuable insights into the stock markets behaviour, particularly within the context of Google, by leveraging the ARIMA models capabilities.