A Comparison Between Ordinary Least Square And Robust Regression And Its Application In Macroeconomic Variables
This thesis investigates the relationship between stock market price and macroeconomic variables in Malaysia. There are six macroeconomic factors selected for this study namely Gross Domestic Product (GDP), Exchange Rate (ER), Money Supply (MI), Inflation Rate (IR) and Based Lending Rate (BLR)....
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| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
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| الملخص: | This thesis investigates the relationship between stock market price and
macroeconomic variables in Malaysia. There are six macroeconomic factors
selected for this study namely Gross Domestic Product (GDP), Exchange Rate
(ER), Money Supply (MI), Inflation Rate (IR) and Based Lending Rate (BLR).
The widely adopted method in examining this relationship is regression analysis in
which the Ordinary Least Square (OLS) method is applied. OLS however has a
limitation since the economic data is subjected to the influence of outliers. To
overcome such problem, a robust regression is employed by using M-estimation
and comparison is made to the OLS procedure. The results demonstrate that the
robust regression procedure is able to generate reliable results as well as
diagnosing a few outliers in the analysis. The findings are substantiated with
diagnostic procedures, which include leverage identification, standardized
residual, studentized residual, DFFITS and Cook's Distance in order to identify
the presence of outliers in the model. |
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