Copula-Based Dynamic Conditional Correlation Multiplicative Error Processes
AbstractWe introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables revealing time-varying conditional variances and correlations. Modeling the variables’ conditional mean processes using a multiplicative error model we map the resulting residuals into a Gaussian domain using a Gaussian copula. Based on high-frequency volatility, cumulative trading volumes, trade counts and market depth of various stocks traded at the NYSE, we show that the proposed copula-based transformation is supported by the data and allows disentangling (multivariate) dynamics in higher order moments. To capture the latter, we propose a DCC-GARCH specification. We suggest estimating the model by composite maximum likelihood which is sufficiently flexible to be applicable in high dimensions. Strong empirical evidence for time-varying conditional (co-)variances in trading processes supports the usefulness of the approach. Taking these higher-order dynamics explicitly into account significantly improves the goodness-of-fit of the multiplicative error model and allows capturing time-varying liquidity risks.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2012-044.
Length: 29 pages
Date of creation: Jul 2012
Date of revision:
multiplicative error model; trading processes; copula; DCC-GARCH; liquidity risk;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-07-23 (All new papers)
- NEP-ECM-2012-07-23 (Econometrics)
- NEP-ETS-2012-07-23 (Econometric Time Series)
- NEP-MST-2012-07-23 (Market Microstructure)
- NEP-RMG-2012-07-23 (Risk Management)
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.:
- 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.
- Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
- Nikolaus Hautsch, 2007. "Capturing Common Components in High-Frequency Financial Time Series: A Multivariate Stochastic Multiplicative Error Model," SFB 649 Discussion Papers SFB649DP2007-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- BAUWENS, Luc & VEREDAS, David, 1999.
"The stochastic conditional duration model: a latent factor model for the analysis of financial durations,"
CORE Discussion Papers
1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011.
"Intra-daily Volume Modeling and Prediction for Algorithmic Trading,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 9(3), pages 489-518, Summer.
- Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading," Econometrics Working Papers Archive wp2009_01, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti".
- Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
- Manganelli, Simone, 2005.
"Duration, volume and volatility impact of trades,"
Journal of Financial Markets,
Elsevier, vol. 8(4), pages 377-399, November.
- Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2006.
"Vector Multiplicative Error Models: Representation and Inference,"
NBER Technical Working Papers
0331, National Bureau of Economic Research, Inc.
- Fabrizio Cipollini & Robert F. Engle & Giampiero Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," Econometrics Working Papers Archive wp2006_15, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti".
- Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," NBER Working Papers 12690, National Bureau of Economic Research, Inc.
- Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006.
"Multivariate GARCH models: a survey,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
- Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
- Patton, Andrew J, 2001. "Modelling Time-Varying Exchange Rate Dependence Using the Conditional Copula," University of California at San Diego, Economics Working Paper Series qt01q7j1s2, Department of Economics, UC San Diego.
- Liu, Yan & Luger, Richard, 2009. "Efficient estimation of copula-GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2284-2297, April.
- Meitz, Mika & Terasvirta, Timo, 2006.
"Evaluating Models of Autoregressive Conditional Duration,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 24, pages 104-124, January.
- Meitz, Mika & Teräsvirta, Timo, 2004. "Evaluating models of autoregressive conditional duration," Working Paper Series in Economics and Finance 557, Stockholm School of Economics, revised 13 Dec 2004.
- repec:ulb:ulbeco:2013/5865 is not listed on IDEAS
- Robert F. Engle, 2000.
"The Econometrics of Ultra-High Frequency Data,"
Econometric Society, vol. 68(1), pages 1-22, January.
- Glosten, Lawrence R, 1994. " Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-61, September.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RDC-Team).
If references are entirely missing, you can add them using this form.