## Abstract

The thesis attempts to figure out if a simple yield curve can be used to predict the stock market. The yield curve is made up of two variables; the 10-year treasury bond and the 3- month treasury bill. Due to the fact that the Norwegian 3-month treasury bill was only established in 2003 the regression analysis was split into two. A short- and a long-term. The annualized quarterly return on seasonally adjusted, chained GDP was used as the dependent variable and the spread was the independent variable in the regression analysis. The results of the regression analysis, plotting GDP against the spread, indicated that the yield curve could be predicting seven quarters ahead for the long- and ten quarters for the short-term in Norway. In the US the yield curve seemed to predict ten quarters in the long- and sixteen in the short-term. These assumptions were based on the strength of the models. The S&P 500 and OSEBX indexes were used as proxies, representing their respective countries stock markets. The correlation test and the regression analysis was performed to see if the stock market is able to predict future changes in GDP. The stock market seems to be leading GDP by three quarters in Norway and one quarter in the US. The tests were only performed using the longterm scope. In order to test the overall research question, a comparison test was designed. The cumulative return on a risky, risk-free and Alternative portfolio were compared. The predictive horizon of the yield curve and stock market was decided on the basis of the results of the regression analysis. At least one Alternative portfolio outperformed the stock market proxy in all tests. It was, however, outperformed by the risk-free portfolio in the long-term Norway comparison. The only Alternative strategy portfolios that outperformed the stock market in both the short- and long-term were k3 and k9 in Norway and the US respectively. The null hypothesis was rejected and the yield curve is able to predict the stock market to a certain extent.

Educations | MSc in International Business, (Graduate Programme) Final Thesis |
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Language | English |

Publication date | 2015 |

Number of pages | 171 |