A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations
Abstract
This discussion paper led to a publication in 'Journal of Business & Economic Statistics' , 29(4), 552-63. We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate Student's t distribution. The key novelty of our proposed model concerns the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account for heavy tails of distributions, we obtain estimates that are more robust to large innovations. The model also admits a representation as a time-varying heavy-tailed copula which is particularly useful if the interest focuses on dependence structures. We provide an empirical illustration for a panel of daily global equity returns. This discussion paper led to a publication in the Journal of Business and Economic Statistics (2011, 29(4) 552-63.Download Info
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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 10-032/2.Length:
Date of creation: 16 Mar 2010
Date of revision:
Handle: RePEc:dgr:uvatin:20100032
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Web page: http://www.tinbergen.nl
Related research
Keywords: dynamic dependence; multivariate Student's t distribution; copula;Other versions of this item:
- Creal, Drew & Koopman, Siem Jan & Lucas, André, 2011. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 552-563.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-02-26 (All new papers)
- NEP-ECM-2011-02-26 (Econometrics)
- NEP-ETS-2011-02-26 (Econometric Time Series)
References
References listed on IDEASPlease 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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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
- Andre Lucas & Bernd Schwaab & Xin Zhang, 2013. "Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics," Tinbergen Institute Discussion Papers 13-063/IV/DSF56, Tinbergen Institute, revised 30 May 2013.
- Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
- Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
- Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011.
"Financial Risk Measurement for Financial Risk Management,"
PIER Working Paper Archive
11-037, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2011. "Financial Risk Measurement for Financial Risk Management," CREATES Research Papers 2011-37, School of Economics and Management, University of Aarhus.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2012. "Financial Risk Measurement for Financial Risk Management," NBER Working Papers 18084, National Bureau of Economic Research, Inc.
- Jiangyu Ji & Andre Lucas, 2012. "A New Semiparametric Volatility Model," Tinbergen Institute Discussion Papers 12-055/2/DSF35, Tinbergen Institute.
- Tommaso, Proietti & Alessandra, Luati, 2012. "Maximum likelihood estimation of time series models: the Kalman filter and beyond," MPRA Paper 39600, University Library of Munich, Germany.
- Ito, Ryoko, 2013. "Modeling dynamic diurnal patterns in high frequency financial data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
- Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
- Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
- Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2012. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," Tinbergen Institute Discussion Papers 12-020/4, Tinbergen Institute.
- Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
- Harvey, A. & Luati, A., 2012. "Filtering with heavy tails," Cambridge Working Papers in Economics 1255, Faculty of Economics, University of Cambridge.
- Kris Boudt & Jon Danielsson & Siem Jan Koopman & Andre Lucas, 2012. "Regime switches in the volatility and correlation of financial institutions," Working Paper Research 227, National Bank of Belgium.
- Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
- Xin Zhang & Bernd Schwaab & Andre Lucas, 2011. "Conditional Probabilities and Contagion Measures for Euro Area Sovereign Default Risk," Tinbergen Institute Discussion Papers 11-176/2/DSF29, Tinbergen Institute, revised 28 Jun 2012.
- Harvey, A. & Sucarrat, G., 2012. "EGARCH models with fat tails, skewness and leverage," Cambridge Working Papers in Economics 1236, Faculty of Economics, University of Cambridge.
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