The Relationship between Economic indexes and Stock Market.

Marko Yacoub Anwar Yacoub

Master's thesis

Abstract:

There are many methods of the stock market analysis which investors depend on for providing them with a clear picture for the future of the stock market and the economic status so it could lower their investing risk. For example, we have fundamental analysis and technical analysis also there are macroeconomic variables which influence the stock market as the GDP, unemployment, inflation, interest rate and exchange rate. So, in my diploma thesis I’m discussing an overview about those different types of stock market analysis also I will investigate the correlation between the mentioned macroeconomic variables and the stock market index S&P500 and how each of those macroeconomic variables influence the index.Hypothesis: I assume that any change in the macroeconomic variables data (GDP, unemployment, inflation, interest rate and exchange rate) will influence the stock markets (S&P500 index is my measurement for the stock market).By creating a polynomial equation between each of the mentioned macroeconomic variables and the S&P500 index I got the correlation between them as I found that there is a direct proportional correlation between the GDP and the stock market index. Also, there is an inverse correlation between the unemployment and the stock market index. And for the inflation I found that the stock market and the inflation rate have a direct proportional correlation until the inflation reach almost to the rate of 1.7% then this correlation started to convert to an inverse correlation. Also, I found that there is an inverse correlation between the exchange rate (EUR/USD) and the American index S&P500. After this I wanted to gather all of those macroeconomic variables with S&P500 index in multi regression model to conclude the correlation among the macroeconomic variables and the stock market index S&P500 in one model so after doing the scatterplots and correlation test and the multicollinearity test I found that the only macroeconomic variables I could use are GDP, unemployment and the exchange rate as an independent variables with the S&P500 index as a dependent variable. Then after getting my multi regression model curve I compared it with S&P500 index values in one chart to understand the relation between my new multi regression model curve and the S&P500 index.All those correlations enabled me to create two indicators the first one is between GDP and S&P500. The second one is between my multiple regression model curve and S&P500 index.As a result, now with my new technical indicators it is easier for everyone to have a general expectations for the future of the stock market with more clear picture of the economic status by connecting between the mentioned macroeconomic variables and stock market index S&P500.

Keywords

GDP, Unemployment, Inflation, Interest rate, Exchange rate, Polynomial regression, Muliple regression model, S&P500

Language used: English

Date on which the thesis was submitted / produced: 26. 11. 2019

Thesis defence

• Supervisor: prof. Ing. Mansoor Maitah, Ph.D. Ph.D.

Czech University of Life Sciences Prague

Faculty of Economics and Management

Master programme / field:
Economics and Management / Economics and Management