Capturing common components in high-frequency financial time series : a multivariate stochastic multiplicative error model

  • 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 high-frequency 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. JEL Classification: C15, C32, C52

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Author:Nikolaus Hautsch
Parent Title (German):Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2007,25
Series (Serial Number):CFS working paper series (2007, 25)
Document Type:Working Paper
Year of Completion:2007
Year of first Publication:2007
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2007/11/02
Tag:Common Factor; Efficient Importance Sampling; Intraday Trading Process; Multiplicative Error Models
Issue:July 2007
Page Number:47
Acknowledgements: Earlier versions of this paper have been presented at the EC2 conference 2003 in London, at the International Conference on Finance in Copenhagen, 2005, the 2005 Arne Ryde Workshop in Financial Economics in Lund, the International Conference on High Frequency Finance in Konstanz, 2006, the 2006 meeting of the European Econometric Society in Vienna as well as the 2006 meeting of the German Economic Association in Bayreuth. For valuable comments we would like to thank Torben G. Andersen, Luc Bauwens, Tim Bollerslev, Robert F. Engle, Timo Ter¨asvirta, Winfried Pohlmeier as well as the seminar participants at the Stockholm School of Economics and the Universit´e Libre de Bruxelles.
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
Licence (German):License LogoDeutsches Urheberrecht