摘要：Scientific literature has been seemingly enriched by various theoretical and empirical studies analysing the relationship between stock market returns and macroeconomic forces during the last few decades. It is often argued that stock prices are determined by some fundamental macroeconomic variables . This implies that macroeconomic variables can influence investors’ investment decisions and motivates many researchers to investigate the relationships between stock market prices and macroeconomic variables. Different authors select different macroeconomic variables seeking to detect their relationship with stock market prices in various countries. Simultaneously, a number of econometric techniques such as the arbitrage pricing theory, the impulse response function, the error variance decomposition analysis, the vector error correction model, the cointegration analysis, the Granger causality tests and others may be applied for checking the existence of relationship between stock market prices and macroeconomic variables. The current paper attempts to present several classifications of macroeconomic variables, then to select macroeconomic variables for seeking their relationship with stock market prices, and, finally, to define what macroeconomic variables have positive and what macroeconomic variables have negative effects on stock market prices in Lithuania in the short run. Augmented Dickey Fuller test has been employed to check the stationarity of the selected time series since a spurious regression may occur if a time series is not stationary. The Impulse response function has been chosen to test the existence of the short-run relationship between stock market prices and macroeconomic variables. As the results of the Impulse response function are reliable only with a stationary time series the data has been turned into stationary after the second difference. The study embraces six macroeconomic variables (seasonally adjusted gross domestic product at previous year prices, harmonised consumer price index as compared to 2005, the narrow money supply, unemployment rate, short-term interest rates, and exchange rate of the Litas against the US dollar) and the main Lithuanian stock market index – the OMX Vilnius index. The data are monthly and extend from the January of 2000 to the June of 2009. In general, the results of the paper clearly indicate that macroeconomic variables are significant determinants for stock market prices in Lithuania. Gross domestic product and money supply have a positive effect on stock market prices while most of the time unemployment rate, exchange rate, and short-term interest rates negatively influence stock market prices. The findings of the paper are similar to the results of some other empirical studies. If harmonised consumer price index is considered, then it is the best example of an unstable relationship between a macroeconomic variable and stock market prices in Lithuania.
其他摘要：Scientific literature has been seemingly enriched by various theoretical and empirical studies analysing the relationship between stock market returns and macroeconomic forces during the last few decades. It is often argued that stock prices are determined by some fundamental macroeconomic variables . This implies that macroeconomic variables can influence investors’ investment decisions and motivates many researchers to investigate the relationships between stock market prices and macroeconomic variables. Different authors select different macroeconomic variables seeking to detect their relationship with stock market prices in various countries. Simultaneously, a number of econometric techniques such as the arbitrage pricing theory, the impulse response function, the error variance decomposition analysis, the vector error correction model, the cointegration analysis, the Granger causality tests and others may be applied for checking the existence of relationship between stock market prices and macroeconomic variables. The current paper attempts to present several classifications of macroeconomic variables, then to select macroeconomic variables for seeking their relationship with stock market prices, and, finally, to define what macroeconomic variables have positive and what macroeconomic variables have negative effects on stock market prices in Lithuania in the short run. Augmented Dickey Fuller test has been employed to check the stationarity of the selected time series since a spurious regression may occur if a time series is not stationary. The Impulse response function has been chosen to test the existence of the short-run relationship between stock market prices and macroeconomic variables. As the results of the Impulse response function are reliable only with a stationary time series the data has been turned into stationary after the second difference. The study embraces six macroeconomic variables (seasonally adjusted gross domestic product at previous year prices, harmonised consumer price index as compared to 2005, the narrow money supply, unemployment rate, short-term interest rates, and exchange rate of the Litas against the US dollar) and the main Lithuanian stock market index – the OMX Vilnius index. The data are monthly and extend from the January of 2000 to the June of 2009. In general, the results of the paper clearly indicate that macroeconomic variables are significant determinants for stock market prices in Lithuania. Gross domestic product and money supply have a positive effect on stock market prices while most of the time unemployment rate, exchange rate, and short-term interest rates negatively influence stock market prices. The findings of the paper are similar to the results of some other empirical studies. If harmonised consumer price index is considered, then it is the best example of an unstable relationship between a macroeconomic variable and stock market prices in Lithuania.
