Modelling Financial High Frequency Data Using Point Processes
Luc Bauwens () and
Nikolaus Hautsch ()
No SFB649DP2007-066, SFB 649 Discussion Papers from Humboldt University, Collaborative Research Center 649
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.
Keywords: Financial point processes; dynamic duration models; dynamic intensity models. (search for similar items in EconPapers)
JEL-codes: C22 C32 C41 (search for similar items in EconPapers)
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Working Paper: Modelling financial high frequency data using point processes (2009)
Working Paper: Modelling financial high frequency data using point processes (2006)
Working Paper: Modelling Financial High Frequency Data Using Point Processes (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:hum:wpaper:sfb649dp2007-066
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