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Modelling Financial High Frequency Data Using Point Processes

Listed author(s):
  • Luc Bauwens
  • Nikolaus Hautsch

In this paper, we give an overview of the state-of-the-art in the econometric literature on the modeling of so-called financial point processes. The latter are associated with the random arrival of specific financial trading events, such as transactions, quote updates, limit orders or price changes observable based on financial high-frequency data. After discussing fundamental statistical concepts of point process theory, we review durationbased and intensity-based models of financial point processes. Whereas duration-based approaches are mostly preferable for univariate time series, intensity-based models provide powerful frameworks to model multivariate point processes in continuous time. We illustrate the most important properties of the individual models and discuss major empirical applications.

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File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2007-066.pdf
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Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2007-066.

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Length: 35 pages
Date of creation: Nov 2007
Handle: RePEc:hum:wpaper:sfb649dp2007-066
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