Stock Price Forecasting of Maruti Suzuki using Auto Regressive Integrated Moving Average (ARIMA) Model

Abstract

Forecasting of stock prices is a very important subject in the financial world and economics. For many years, investors have been interested in making better forecasting models. The autoregressive integrated moving average (ARIMA) model was used previously for time series forecasting. This article shows the process of stock price forecasting using an ARIMA model. Historical stock data for analysis is obtained from the National Stock Exchange (NSE) and is used along with the stock price for forecasting using an ARIMA model. The result obtained from an ARIMA model is better for short-term forecasting and can be proven with existing methods for stock price prediction.