The Stock Price of the ThyssenKrupp AG - A Time Series Analysis Using the Box Jenkins Approach (e-book) (used book) | bookbook.eu

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Seminar paper from the year 2008 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1,0 (A), University of Wisconsin-Milwaukee (Department of Economics), course: Applied Econometrics, language: English, abstract: In this paper the Box- Jenkins forecasting technique should be applied to the stock price of the ThyssenKrupp AG. ThyssenKrupp arose from the merger of the "Thyssen AG" and the "Friedrich Krupp AG Hoesch-Krupp" in 1999. The main focus of the trust lies on steel, industrial goods and services with its five sections Stainless, Steel, Technologies, Elevator and Services. With 191,350 employees in over 70 countries and a turnover of 51.7 billion Euro p.a., ThyssenKrupp is one of the largest industry and technology groups in the world. At the same time it is Germany's biggest steel and armaments manufacturer. I chose the stock price of the ThyssenKrupp trust for several reasons. First, it is a blue chip listed on the stock exchange since 1999 allowing me easy access to a sufficient and reliable amount of data. Second, I have no reason to believe that this trust underlies any influence of seasonality since it has so many different segments that contribute to its economic performance. Third, since the steel demand and thus prices are steadily increasing in the last years it is not surprising that the stock price of the ThyssenKrupp AG does this too (see figure 2 further down) giving me a reason to question financial market theories. In particular, financial investors and researches are very often interested to predict future values of stock prices. On the one hand they do so, to gain profits from investing in stocks from buying at a low price and selling at a higher price and on the other hand to verify if financial markets work efficiently. For the latter reason, financial research for a long time believed stock prices to follow a random walk and thus that prices of the stock market cannot be predicted2. This implies that