Stock Market Prediction using Auto Regressive Integrated Moving Averages (ARIMA)

K Murali, Sk Nafeez Umar, D Chandrakesavulu Naidu, MP Reddeppa Reddy, C Mani, B Ramana Murthy

Abstract: Stock market prediction plays an important role to decide investment in markets over the time period. The Auto Regressive Integrated Moving Averages (ARIMA) have been explored for time series prediction. This paper explores the process and method of building Stock predictive models is using ARIMA model. The Stock market indices data of Bombay Stock Exchange (BSE) is used in building stock predictive model. The Results revealed that the ARIMA model has a robust for particularly short term prediction and endorsed with current techniques for Stock Market prediction. The study made a few observations which may help the investors and model builders to understand better about the stock market analysis.

Keywords: Stock market prediction, ARIMA, Short term prediction

How to Cite?: K Murali, Sk Nafeez Umar, D Chandrakesavulu Naidu, MP Reddeppa Reddy, C Mani, B Ramana Murthy, "Stock Market Prediction using Auto Regressive Integrated Moving Averages (ARIMA)", Volume 10 Issue 4, April 2021, International Journal of Science and Research (IJSR), Pages: 379-382, https://www.ijsr.net/getabstract.php?paperid=SR21407121918, DOI: https://dx.doi.org/10.21275/SR21407121918