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Research Paper | Statistics | India | Volume 10 Issue 4, April 2021 | Popularity: 6.4 / 10
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
Edition: Volume 10 Issue 4, April 2021
Pages: 379 - 382
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Statistics, Nepal, Volume 3 Issue 6, June 2014
Pages: 161 - 166Accelerated Failure Time Models: An Application in the Survival of Acute Liver Failure Patients in India
Shankar Prasad Khanal, V. Sreenivas, Subrat K. Acharya
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Statistics, India, Volume 8 Issue 5, May 2019
Pages: 35 - 39The Implementation of Total Quality Management (TQM) as a Function of Improving Quality in Educational Institutions
Rallabandi Srinivasu, G.V.S.R. Anjaneyulu
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Statistics, Kenya, Volume 8 Issue 5, May 2019
Pages: 66 - 69Survival Analysis of Cancer Patients Using Weibull Parametric Model
Wilson Kiprotich Chepkech, Joel Cheruiyot Chelule, Ayubu Anapapa, Herbert Imboga
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Statistics, India, Volume 9 Issue 3, March 2020
Pages: 1201 - 1204Customer Relationship Management (CRM) Viewed by and Analysed by Probability Distribution
Kamlesh L Patel, Dr. Sanjay G Raval, Dr. S R Patel
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Statistics, Congo, Volume 8 Issue 4, April 2019
Pages: 85 - 95Modeling Tax Revenues Using Kernel Approach Case Study: North Kivu Province (Democratic Republic of Congo) Tax Revenues Time Series Forecasting
Byamungu Wanguwabo David