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Modelling financial high frequency data using point processes

  • BAUWENS, Luc
  • HAUTSCH, Nikolaus

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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Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers RP with number 2123.

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Handle: RePEc:cor:louvrp:2123
Note: In : T.G. Andersen, R.A. Davis, J.-P. Kreiss, and T. Mikosch (eds.), Handbook of Financial Time Series. Springer-Verlag Heidelberg, 953-979, 2009
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