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
