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Modellierung von Aktienkursen im Lichte der Komplexitätsforschung

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  • Benjamin Kauper
  • Karl-Kuno Kunze
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    Abstract

    This paper offers empirical evidence on the power of Sornette et al's [2001] model of bubbles and crashes regarding the German stock market between 1960 and 2009. We identify relevant time periods and describe them with the function given by Sornette et al's model. Our results show some evidence in predicting crashes with the understanding of logarithmic periodic structures that are hidden in the stock price trajectories. It was shown that for the DAX most of the relevant parameters determining the shape of the logarithmic periodic structures are lying in the expected interval researched by Sornette et al. Further more the paper implicitly shows that the point of time of former crashes can be predicted with the presented formula. We conclude that the concept of financial time series conceived as purely random objects should be generalised as to admit complexity.

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    File URL: http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52285
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    Bibliographic Info

    Paper provided by Universität Potsdam, Wirtschafts- und Sozialwissenschaftliche Fakultät in its series Statistische Diskussionsbeiträge with number 49.

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    Date of creation: Apr 2011
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    Handle: RePEc:pot:statdp:49

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    Related research

    Keywords: Bubble Theory; Complexity Sciences; Crash Prediction; Econophysics; Nonlinear Dynamics; System Theory;

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