COMPARISION STUDY OF EFFICIENCY OF TIME SERIES MODELS IN FORECASTING STOCK PRICES IN SRI LANKA.
- Department of Mathematical Sciences, Faculty of Applied Sciences, South Eastern University of Sri Lanka.
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The Colombo Stock Exchange is broadest and entirelyinvoluntarytrade exchange system in Sri Lanka. Investigation and prediction of stock market time series data have elaborated significantattention from the investigators and academics over theprevious decade. In this research article, the Colombo Stock Exchange All Share Prices were figured and predicted the tendency of stock market variations using time series modeling procedures, alike exponential smoothing method and autoregressive integrated moving average technique. The forecasted values of Colombo Stock Exchange All Share Priceswere computed for both models distinctly and also compared the error rates. From the consequences, the autoregressive integrated moving average model accomplishedwell than the exponential smoothing model.
- Renhao Jin, Shawang, Fang Yan, et al. The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Science Journal of Applied Mathematics and Statistics. 2015; 3(4): 199?4p.
- Pankratz, Alan New York: John Wiley & Sons, (1983), ?Forecasting with Univariate Box?Jenkins models: concepts and cases?.
- K.Sureshkumar, Dr.N.M.Elango, November 2011, ?An Efficient Approach to Forecast Indian Stock Market Price and their Performance Analysis?, International Journal of Computer Applications (0975 ? 8887), Volume 34? No.5.
- Al Wadia, MohdTahir Ismail S, ?Selecting Wavelet Transforms Model in Forecasting Financial Time Series Data Based on ARIMA Model?, Applied Mathematical Sciences, Vol. 5, 2011, no. 7, 315 ? 326.
- Box, G. E. P., G. M. Jenkins, and G. C. Reinsel, 1994, ?Time Series Analysis: Forecasting and Control?, UpperSaddleRiver?, NJ: Prentice-Hall, 3rd ed.
- Fahim Faisal1, May 2012. Pp. 100 ? 117, ?Forecasting Bangladesh's Inflation Using Time Series ARIMA Models?, World Review of Business Research Vol. 2. No. 3.
- Leigh, W., Hightower, R. and Modani, N., ?Forecasting the New York Stock Exchange Composite Index with Past Price and Interest Rate on Condition of Volume Spike?, Expert Systems with Applications, Vol 28, pp. 1-8, 2005.
- Chatfield, C. (1989). The Analysis of Time Series: An Introduction. 4th Edition. New York: Chapman and Hall.
[Mohamed Aboobucker Haalisha. (2018); COMPARISION STUDY OF EFFICIENCY OF TIME SERIES MODELS IN FORECASTING STOCK PRICES IN SRI LANKA. Int. J. of Adv. Res. 6 (Dec). 126-130] (ISSN 2320-5407). www.journalijar.com
Department of Mathematical Sciences, Faculty of Applied Sciences, South Eastern University of Sri Lanka
