Stock market forecasting:investigation of a relationshipbetween GDP per capita and stockmarket volatility : A statistical study based on the GARCH(1,1)model

Abstract: Stock market indexes such as S&P 500 depends on many different variables, such as macroeconomic variables, causing the volatility to appear random. Getting a close estimation of the volatility is of high interest when making investments. Volatility models and analysis of different macroeconomic variables are often used when estimating the volatility in a market. This paper uses the volatility model GARCH(1,1) to estimate the volatility of the S&P 500 index with the goal of evaluating whether there may exist a relationship between decreases in GDP per capita in the U.S. and the volatility of S&P 500. A significance test with a significance level on 95 % determines that the median of the volatility is higher during periods of decreasing GDP per capita. Together with results from reading graphs of obtained data the conclusion is drawn that there might exista relationship where the S&P 500 index tends to have higher volatility during longer periods of decreasing GDP per capita.