Predicting NEPSE Index Using ARIMA Model

• Published in: International research journal of innovations in engineering and technology Vol. 6; no. 2; pp. 80 - 85
• Main Author: Maskey, Avinash
• Format: Journal Article
• Language: English
• Published: 2022
• ISSN: 2581-3048; 2581-3048
• DOI: 10.47001/IRJIET/2022.602014

Since its inception, the stock market, one of the most financially turbulent markets, has captivated the hearts of thousands of investors. Predicting stock indexes or prices has long been a prominent subject of research in the domain of financial information because of the reward and risk. Also, it has a tremendous beauty as everyone wants to benefit from it. Many approaches are used to forecast stock indexes or prices in the stock market, including technical analysis, fundamental analysis, statistical analysis, and so on, but no single method has shown to be a reliable forecasting tool. This research work contributes to the subject of Time Series Analysis, which seeks to forecast stock market indexes using historical data. In this research work, ARIMA model for NEPSE index has been examined. Published data of daily closing stock index was obtained from Nepal Stock Exchange (NEPSE). With 1798 observations, the data set covers the NEPSE index for approximately eight years, from February 02, 2014 to January 13, 2022. Furthermore, based on the findings, the ARIMA model has a high potential for anticipating short-term market swings, which might be beneficial to short-term traders or investors.