ICBI 2017

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/18303

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Author: search.filters.author.Rathnayaka, R. M. K. T.Has files: Yes

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    Modeling the Best ARIMA Modeling Approach for Forecasting Market Indices in Colombo Stock Exchange, Sri Lanka.
    (8th International Conference on Business & Information ICBI – 2017, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2017) Madushani, M. L. P.; Erandi, M. W. A.; Madurangi, L. H. L. S.; Sivaraj, L. B. M.; Weerasinghe, W. D. D.; Jayasundara, D. D. M.; Rathnayaka, R. M. K. T.
    Generally, the movements of the stock prices are highly volatile and make much more dynamics. As a result day by day the large number of companies has been listed on stock exchanges across the world. Under this scenario, examine a suitable model for forecasting stock prices is a biggest challenge in the modern world. The propose of this study is to examine a suitable model for forecasting stock prices in the Colombo Stock Exchange (CSE), Sri Lanka. Since the data has a non-seasonal linear trend, an autoregressive integrated moving average model was used for modeling and forecasting. The empirical results suggested that ARIMA model is more accurate for forecasting ASPI index than other traditional regression methods.
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    Impact of Macroeconomic Variables on Stock Market Returns: A Case Study of Colombo Stock Exchange, Sri Lanka.
    (8th International Conference on Business & Information ICBI – 2017, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka., 2017) Rathnayaka, R. M. K. T.; Seneviratna, D. M. K. N.
    Unexpected circumstances with respect to the social and economic conditions, the stock market indices have been moving up and down with high volatility. This study examines the equilibrium relationships between the stock market indices and macro-economic factors in Sri Lankan during the period from January, 2009 to December 2016 to capture the linear inter-dependencies, by using Vector Autoregressive Regression and Vector Error Correlation Model, Estimated co-integration rank test and Max-eigenvalue test suggested that there are two co-integration equations exist at the 0.05 level of significance. Furthermore, findings revealed that macroeconomic variables have direct effect on high volatility in Stock Market fluctuations. Moreover, the results concluded that Colombo Stock Exchange (CSE) is highly sensitive to the macroeconomic variables such as real gross domestic product and broad money supply.