The purpose of this research is to investigate the relationship between Karachi stock market 100 index and macroeconomic variables, i.e., inflation, industrial production, money supply, exchange rate and interest rate. The long term relationship between macroeconomic variables and stock market returns has been analyzed by using Johnson Cointegration test, Augmented Dicky Fuller (ADF) and Phillip Perron (PP) tests. The Autoregressive Conditional heteroskedasticity Lagrange Multiplier (ARCH LM) test provided prudent evidence about the presence of heteroskedasticity in the data. The Generalized Autoregressive Conditional heteroskedasticity (GARCH) model was used to find out the relationship between stock returns and the variance of the squared error terms as there was heteroskedastic trend in the data. The results show that the cointegrating relationship exists between stock prices and the macroeconomic variables in Pakistani stock market. The GARCH model showed the significant relationships after mitigating the heteroskedasticity. The consumer price index (CPI), money supply (MS), exchange rates (ER) and interest rates (IR) proved to be negatively associated with the stock returns (SR), while industrial production index (IPI) was found to be positively associated with the stock returns. All the variables were significantly associated to stock market returns except inflation. The investors can use the GARCH results for investment decisions that is the returns are volatile not only due to any happening today but also on the past. The findings suggest that in the long run, the Pakistani stock market is reactive to macroeconomic indicators
Stock markets Pakistan Macroeconomics and heteroskedasticity
The purpose of this research is to investigate the relationship between Karachi stock market 100 index and macroeconomic variables, i.e., inflation, industrial production, money supply, exchange rate and interest rate. The long term relationship between macroeconomic variables and stock market returns has been analyzed by using Johnson Cointegration test, Augmented Dicky Fuller (ADF) and Phillip Perron (PP) tests. The Autoregressive Conditional heteroskedasticity Lagrange Multiplier (ARCH LM) test provided prudent evidence about the presence of heteroskedasticity in the data. The Generalized Autoregressive Conditional heteroskedasticity (GARCH) model was used to find out the relationship between stock returns and the variance of the squared error terms as there was heteroskedastic trend in the data. The results show that the cointegrating relationship exists between stock prices and the macroeconomic variables in Pakistani stock market. The GARCH model showed the significant relationships after mitigating the heteroskedasticity. The consumer price index (CPI), money supply (MS), exchange rates (ER) and interest rates (IR) proved to be negatively associated with the stock returns (SR), while industrial production index (IPI) was found to be positively associated with the stock returns. All the variables were significantly associated to stock market returns except inflation. The investors can use the GARCH results for investment decisions that is the returns are volatile not only due to any happening today but also on the past. The findings suggest that in the long run, the Pakistani stock market is reactive to macroeconomic indicators.
Stock markets Pakistan Macroeconomics and heteroskedasticity
Birincil Dil | İngilizce |
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Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 26 Ocak 2015 |
Yayımlandığı Sayı | Yıl 2014 |