English, Article, Journal or magazine article edition: Modelling Financial High Frequency Data Using Point Processes Luc, BAUWENS; Nikolaus, HAUTSCH

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Bookmark: http://trove.nla.gov.au/version/178094
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Modelling Financial High Frequency Data Using Point Processes
Author
  • Luc, BAUWENS
  • Nikolaus, HAUTSCH
Physical Description
  • preprint
Notes
  • 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.
  • Financial point processes, dynamic duration models, dynamic intensity models.
  • RePEc:hum:wpaper:sfb649dp2007-066
  • In this chapter written for a forthcoming Handbook of Financial Time Series to be published by Springer-Verlag, we review the econometric literature on dynamic duration and intensity processes applied to high frequency financial data, which was boosted by the work of Engle and Russell (1997) on autoregressive duration models
  • Duration, Intensity, Point process, High frequency data, ACD models
  • RePEc:ctl:louvec:2006039
Language
  • English
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