Intraday Transaction Price Dynamics

Gaelle Le Fol, Serge Darolles and Christian Gourieroux
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Serge Darolles: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique
Christian Gourieroux: CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, Department of Economics - University of Toronto

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Abstract: High frequency transaction prices exhibit two major characteristics: they are discrete in level and only exist at random transaction dates. In this paper we seek to model transaction price dynamics, taking into account these two features. We specify the transaction price process as a Markov Chain with random transaction dates, and discuss various tools for dynamic analysis like the canonical decomposition, the scale and speed measures. The approach is applied to high frequency data on the stock Elf-Aquitaine traded on the Paris Bourse.

Keywords: High Frequency Data; Markov Chain; Nonlinear Canonical Analysis; Durations; Données haute fréquence; Chaine de Markov; Analyse canonique non linéaire; Durées (search for similar items in EconPapers)
Date: 1999
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Published in Annales d'Economie et de Statistique, 1999, 60, pp.207-238

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Journal Article: Intraday Transaction Price Dynamics (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00536272

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