Selection of Best ARIMA Modeling Approach for Forecasting Time Series Patterns; A Case Study on Colombo Stock Exchange
(International Journal of Business, Economics and Management Works)
Vol. 4, Issue 11, PP. 1-5, November 2017
Modeling, Stock exchange, ARIMA
Stock market indexes provide a yardstick with which investors can compare the performance of their individual stock portfolios. The propose of this paper is to examine a suitable model for forecasting stock prices under the volatility in the Colombo Stock Exchange (CSE), Sri Lanka.Since the data has a non-seasonal linear trend, an autoregressive integrated moving average model has used for modeling and forecasting. The results suggested that ARIMA model is more suitable for forecasting ASPI index under the volatility.
- Madushani M.L.P*: Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Sri Lanka.
- Erandi M.W.A*: Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Sri Lanka.
- Madurangi L.H.L.S*: Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Sri Lanka.
- Sivaraj L.B.M*: Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Sri Lanka.
- Weerasinghe W.D .D*: Department of Statistics & Computer Science, Faculty of Science, University of Kelaniya, Sri Lanka.
- R.M KapilaTharangaRathnayaka: Faculty of Sciences, Sabaragamuwa University of Sri Lanka,Sri Lanka, firstname.lastname@example.org
Madushani M.L.P, Erandi M.W.A, Madurangi L.H.L.S, Sivaraj L.B.M, Weerasinghe W.D .D, R.M KapilaTharangaRathnayaka, "Selection of Best ARIMA Modeling Approach for Forecasting Time Series Patterns; A Case Study on Colombo Stock Exchange" International Journal of Business, Economics and Managment Works, Vol. 4, Issue 11, PP. 1-5, November 2017.
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