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Modelling Financial High Frequency Data Using Point Processes

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Author Info
Luc, BAUWENS (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics)
Nikolaus, HAUTSCH

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Abstract

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

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Publisher Info
Paper provided by Université catholique de Louvain, Département des Sciences Economiques in its series Université catholique de Louvain, Département des Sciences Economiques Working Paper with number 2006039.

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Length: 33
Date of creation: 18 Sep 2006
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Handle: RePEc:ctl:louvec:2006039

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Related research
Keywords: Duration Intensity Point process High frequency data ACD models

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Find related papers by JEL classification:
C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models

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  1. Nikolaus Hautsch, 2007. "Capturing Common Components in High-Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model," CFS Working Paper Series 2007/25, Center for Financial Studies. [Downloadable!]
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  2. Frank Gerhard & Nikolaus Hautsch, 2007. "A Dynamic Semiparametric Proportional Hazard Model," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(2), pages 1377-1377. [Downloadable!] (restricted)
    Other versions:
  3. Sebastian Braun & Nadja Dwenger & Dorothea Kübler, 2007. "Telling the Truth May Not Pay Off: An Empirical Study of Centralised University Admissions in Germany," SFB 649 Discussion Papers SFB649DP2007-070, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
    Other versions:
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