Sama Circular Model on Forecasting Sri Lankan Stock Market Indices

Konarasinghe, W.G.S (2018). Sama Circular Model on Forecasting Sri Lankan Stock Market Indices. Proceedings of the International Multidisciplinary Research Conference, Thailand, 123.

4 Pages Posted: 26 Jun 2019

Date Written: June 10, 2018

Abstract

A stock market or share market is a network of transactions of financial instruments. In general, performances of stock markets are measured by stock market indices. A stock market index is an indicator of the direction of the overall stock market and individual stocks. It is a statistic reflecting the composite value of its components. An increase in the index indicates a rising market; a decreasing in the index indicates a falling market; fluctuation of the index series shows the volatility of the market. These patterns of stock market indices give insights to the investment decisions, as such forecasting market indices were an immense interest over the past decades. In the Sri Lankan context, All Share price index (ASPI) measures the overall movement of the market, whilst the S&P SL20 Index captures the movements of top 20 companies listed in the Colombo Stock Exchange (CSE). Many academicians and researchers have attempted to forecast the ASPI, yet the reliability and accuracy of them is questionable. Also, it was hard to find any attempts for forecasting S&P SL20 Index. Hence, it was intended to find suitable techniques for forecasting ASPI and S&P SL20 Index. Pattern recognition of indices was done by Time Series plots and Auto Correlation Functions (ACF’s). Results revealed that, data series follow irregular wave patterns with trends. This type of data series can be modeled by the Decomposition Technique or Sama Circular Model (SCM). However, applying Decomposition technique is time consuming and cumbersome. In contrast, the SCM is easy to use and less time consuming; especially the SCM is capable in separating the seasonal and cyclical components with less effort. Therefore the SCM was tested for the purpose. The ACF of residuals and Ljung-Box Q statistics (LBQ) were used to test the independence of residuals. The Anderson Darling test was used to test the normality of residuals. Forecasting ability of the models was assessed by Mean Square Error (MSE) and Mean Absolute Deviation (MAD). It is concluded that the SCM is capable in forecasting main indices of the Sri Lankan share market.

Keywords: Stock Market Index, Sama Circular Model

Suggested Citation

Konarasinghe, W.G.S., Sama Circular Model on Forecasting Sri Lankan Stock Market Indices (June 10, 2018). Konarasinghe, W.G.S (2018). Sama Circular Model on Forecasting Sri Lankan Stock Market Indices. Proceedings of the International Multidisciplinary Research Conference, Thailand, 123. , Available at SSRN: https://ssrn.com/abstract=3408643

W.G.S. Konarasinghe (Contact Author)

Institute of Mathematics & Management ( email )

312/8, Ekamuthu Mawatha
Ranala
COLOMBO, 10654
Sri Lanka

HOME PAGE: http://www.imathm.edu.lk

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