FORECASTING BY REGRESSION ANALYSIS: A CASE STUDY OF LOCAL STOCK EXCHANGE MARKET BASED ON FOREIGN MARKETS
Abstract
Regression analysis is one of the most widely used techniques for analyzing multifactor data. The application of
regression analysis in stock market is a statistical technique used to forecast and to analyze teh factors that influnce the stock
market. By using the “multiple linear regression”, studies have been done in obtaining the best regression model to do
forecasting. The common types of “multiple linear regression” to be studied here would be estimation of the model parameters,
hypothesis testing and confidence intervals. The foreign stock markets for this reasearch are Hang Seng, All Ordinaries, Nikkei
225, Dow Jones and FTSE 100. The data are collected from 1 january to 31 December 2002. as result, that the closing value for
KLSE is related to at least one regressors and the closing values for Nikkei 225 and Dow Jones have strong influence on the
closing value for KLSE
regression analysis in stock market is a statistical technique used to forecast and to analyze teh factors that influnce the stock
market. By using the “multiple linear regression”, studies have been done in obtaining the best regression model to do
forecasting. The common types of “multiple linear regression” to be studied here would be estimation of the model parameters,
hypothesis testing and confidence intervals. The foreign stock markets for this reasearch are Hang Seng, All Ordinaries, Nikkei
225, Dow Jones and FTSE 100. The data are collected from 1 january to 31 December 2002. as result, that the closing value for
KLSE is related to at least one regressors and the closing values for Nikkei 225 and Dow Jones have strong influence on the
closing value for KLSE
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PDF (Bahasa Indonesia)DOI: https://doi.org/10.29313/jstat.v3i1.551
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