Purpose of the article The present article deals with associations between the development of money supply measured by the money aggregate M2 and the development of the Ameri-can stock index Dow Jones Industrial Average. The objective of the article is to determine, describe and assess the impact of the changes of money supply (as measured by the money aggregate M2) on the development of the American stock market. Another objective is to find out whether the changes in money supply are reflected in the changes of stock prices immediately or with a time delay of several weeks. Methodology/methods Regarding to the aim of the article was all useful historic data of money suplly (measured with money aggregate M2) and close values of DJIA obtain in monthly frequence, since 1959 to 2011. From econometric methods, will be using Pearson correlation index, Dickey-Fuller stationary test and test of Granger causality, which will be focus on realtionship between money supply (M2) and stock prices (DJIA index). Scientific aim The aim of this article is by using econometric methods find, describe and analyze ipact of changing money supply to selected stock market. The second aim is disclose, if stock market react immediately or with time delay (in week). Findings The correlation analysis shows, that between change of money supply and stock index is high dependence (correlation index 0.9224). By calculating with time delay, was correlation index high too, but slowly decrease. By market colaps in year 2007 and 2008, was correlation index negative with value -0.9477, no matter to money supply rasing, that is meaning, that investors have to calculate with psychologic factors, which are very strong in nervous time and market crashes. The result of Granger causality test for 1 month delay failed to show a relationship between money supply and DJIA index. With application of 2, 3 and 6 month delay the dependence was demonstrated, rejecting the null hypothesis stat-ing that the M2 money aggregate does not affect the DJIA stock index Conclusions (limits, implications etc) Reached results can be biased by using first diferention of raw data and in correlation analysis was using raw (non-sesonally adjusted) data of development DJIA index and sesonally adjusted data of money supply. The weak spot is using Dow Jones Index in place of S&P 500 index, which is more wider. By changes in analysis is possible to measure the impact of money supply (measured by Money with Zero Maturity aggregate) on stock index and compare both results and make decision, which aggregate is better for forecasting.
