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Capturing Common Components in High-Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model

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Author Info
Nikolaus Hautsch () (Humboldt University Berlin and CFS)

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Abstract

We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects in the processes of highfrequency return volatilities, trade sizes and trading intensities. The model is estimated by simulated maximum likelihood using efficient importance sampling. Analyzing five minutes data from four liquid stocks traded at the New York Stock Exchange, we find that volatilities, volumes and intensities are driven by idiosyncratic dynamics as well as a highly persistent common factor capturing most causal relations and cross-dependencies between the individual variables. This confirms economic theory and suggests more parsimonious specifications of high-dimensional trading processes. It turns out that common shocks affect the return volatility and the trading volume rather than the trading intensity.

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Paper provided by Center for Financial Studies in its series CFS Working Paper Series with number 2007/25.

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Length: 47 pages
Date of creation: 04 Sep 2007
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Handle: RePEc:cfs:cfswop:wp200725

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Keywords: Net Foreign Assets Valuation Adjustment International Financial Integration

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  28. Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Université catholique de Louvain, Département des Sciences Economiques Working Paper 2006039, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Kerstin Kiefer & Philipp Schorn, 2007. "Auswirkungen der IFRS-Umstellung auf die Risikoprämie von Unternehmensanleihen - Eine empirische Studie für Deutschland, Österreich und die Schweiz," SFB 649 Discussion Papers SFB649DP2007-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  2. Marcus Wagner, 2007. "Determinants of the Acquisition of Smaller Firms by Larger Incumbents in High-Tech Industries: Are they related to Innovation and Technology Sourcing?," SFB 649 Discussion Papers SFB649DP2007-063, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  3. Volodymyr Perederiy, 2007. "Kombinierte Liquiditäts- und Solvenzkennzahlen und ein darauf basierendes Insolvenzprognosemodell für deutsche GmbHs," SFB 649 Discussion Papers SFB649DP2007-060, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
  4. 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!]
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