Asymmetric CAPM dependence for large dimensions: the Canonical Vine Autoregressive Model
AbstractWe propose a new dynamic model for volatility and dependence in high dimensions, that allows for departures from the normal distribution, both in the marginals and in the dependence. The dependence is modeled with a dynamic canonical vine copula, which can be decomposed into a cascade of bivariate conditional copulas. Due to this decomposition, the model does not suffer from the curse of dimensionality. The canonical vine autoregressive (CAVA) captures asymmetries in the dependence structure. The model is applied to 95 S&P500 stocks. For the marginal distributions, we use non-Gaussian GARCH models, that are designed to capture skewness and kurtosis. By conditioning on the market index and on sector indexes, the dependence structure is much simplified and the model can be considered as a non-linear version of the CAPM or of a market model with sector effects. The model is shown to deliver good forecasts of Value-at-Risk.
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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2009069.
Date of creation: 01 Nov 2009
Date of revision:
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asymmetric dependence; high dimension; multivariate copula; multivariate GARCH; Value-at-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
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-03-28 (All new papers)
- NEP-ECM-2010-03-28 (Econometrics)
- NEP-ETS-2010-03-28 (Econometric Time Series)
- NEP-FOR-2010-03-28 (Forecasting)
- NEP-RMG-2010-03-28 (Risk Management)
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- David E Allen & Mohammad.A. Ashraf & Michael McAleer & Robert J Powell & Abhay K Singh, 2013.
"Financial Dependence Analysis: Applications of Vine Copulae,"
KIER Working Papers
843, Kyoto University, Institute of Economic Research.
- David Allen & Mohammad.A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Documentos del Instituto Complutense de AnÃ¡lisis EconÃ³mico 2013-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
- David.E. Allen & Mohammad.A. Ashraf & Michael. McAleer & Robert.J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Tinbergen Institute Discussion Papers 13-022/III, Tinbergen Institute.
- David E Allen & Mohammad A. Ashraf & Michael McAleer & Robert Powell & Abhay Kumar Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Working papers 2013-02, Edith Cowan University, School of Accounting Finance & Economics.
- Zhun Peng, 2011. "L'analyse dynamique des dépendances," Post-Print dumas-00651795, HAL.
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