Sequential Estimation Of Shape Parameters In Multivariate Dynamic Models
AbstractSequential maximum likelihood and GMM estimators of distributional parameters obtained from the standardised innovations of multivariate conditionally heteroskedastic dynamic regression models evaluated at Gaussian PML estimators preserve the consistency of mean and variance parameters while allowing for realistic distributions. We assess the efficiency of those estimators, and obtain moment conditions leading to sequential estimators as efficient as their joint maximum likelihood counterparts. We also obtain standard errors for the quantiles required in VaR and CoVaR calculations, and analyse the effects on these measures of distributional misspecification. Finally, we illustrate the small sample performance of these procedures through Monte Carlo simulations.
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Bibliographic InfoPaper provided by CEMFI in its series Working Papers with number wp2012_1201.
Date of creation: Feb 2012
Date of revision:
Elliptical distributions; Efficient estimation; Systemic risk; Value at risk.;
Other versions of this item:
- Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-07-01 (All new papers)
- NEP-ECM-2012-07-01 (Econometrics)
- NEP-ETS-2012-07-01 (Econometric Time Series)
- NEP-ORE-2012-07-01 (Operations Research)
- NEP-RMG-2012-07-01 (Risk Management)
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- Fiorentini, Gabriele & Sentana, Enrique & Calzolari, Giorgio, 2003. "Maximum Likelihood Estimation and Inference in Multivariate Conditionally Heteroscedastic Dynamic Regression Models with Student t Innovations," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 532-46, October.
- Whitney K. Newey & Douglas G. Steigerwald, 1997. "Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models," Econometrica, Econometric Society, vol. 65(3), pages 587-600, May.
- M. Hashem Pesaran & Christoph Schleicher & Paolo Zaffaroni, 2008.
"Model Averaging in Risk Management with an Application to Futures Markets,"
CESifo Working Paper Series
2231, CESifo Group Munich.
- Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
- Pesaran, M.H. & Schleicher, C. & Zaffaroni, P., 2008. "Model Averaging in Risk Management with an Application to Futures Markets," Cambridge Working Papers in Economics 0808, Faculty of Economics, University of Cambridge.
- Newey, Whitney K, 1985. "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, Econometric Society, vol. 53(5), pages 1047-70, September.
- Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
- Shiqing Ling & Michael McAleer, 2001.
"Asymptotic Theory for a Vector ARMA-GARCH Model,"
ISER Discussion Paper
0549, Institute of Social and Economic Research, Osaka University.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Koenker,Roger, 2005.
Cambridge University Press, number 9780521845731.
- Jose A. Lopez, 1998.
"Methods for evaluating value-at-risk estimates,"
Economic Policy Review,
Federal Reserve Bank of New York, issue Oct, pages 119-124.
- N. Meddahi & C. Bontemps, 2004.
"Testing Distributional Assumptions: A GMM Approach,"
Econometric Society 2004 North American Winter Meetings
487, Econometric Society.
- Bontemps, Christian & Meddahi, Nour, 2007. "Testing Distributional Assumptions: A GMM Approach," IDEI Working Papers 486, Institut d'Économie Industrielle (IDEI), Toulouse.
- Dominicy, Yves & Veredas, David, 2013. "The method of simulated quantiles," Journal of Econometrics, Elsevier, vol. 172(2), pages 235-247.
- Douglas J. Hodgson & Keith Vorkink, 2001.
"Efficient Estimation of Conditional Asset Pricing Models,"
Cahiers de recherche CREFE / CREFE Working Papers
144, CREFE, Université du Québec à Montréal.
- Hodgson, Douglas J & Vorkink, Keith P, 2003. "Efficient Estimation of Conditional Asset-Pricing Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 269-83, April.
- Viral V. Acharya, 2010. "Measuring systemic risk," Proceedings 1140, Federal Reserve Bank of Chicago.
- Bahram Pesaran & M. Hashem Pesaran, 2010.
"Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash,"
CESifo Working Paper Series
3023, CESifo Group Munich.
- Pesaran, Bahram & Pesaran, M. Hashem, 2010. "Conditional volatility and correlations of weekly returns and the VaR analysis of 2008 stock market crash," Economic Modelling, Elsevier, vol. 27(6), pages 1398-1416, November.
- Mencía, Javier & Sentana, Enrique, 2009.
"Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation,"
Journal of Econometrics,
Elsevier, vol. 153(2), pages 105-121, December.
- Javier Mencía & Enrique Sentana, 2009. "Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation," Banco de Espaï¿½a Working Papers 0909, Banco de Espa�a.
- Enrique Sentana & Javier Mencía, 2008. "Multivariate Location-Scale Mixtures Of Normals And Mean-Variance-Skwness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
- repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
- Massimo Guidolin & Allan Timmerman, 2006.
"Asset allocation under multivariate regime switching,"
2005-002, Federal Reserve Bank of St. Louis.
- Guidolin, Massimo & Timmermann, Allan, 2007. "Asset allocation under multivariate regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3503-3544, November.
- Owen, Joel & Rabinovitch, Ramon, 1983. " On the Class of Elliptical Distributions and Their Applications to the Theory of Portfolio Choice," Journal of Finance, American Finance Association, vol. 38(3), pages 745-52, June.
- Adrian Pagan, 1985.
"Two Stage and Related Estimators and Their Applications,"
Cowles Foundation Discussion Papers
741, Cowles Foundation for Research in Economics, Yale University.
- Pagan, Adrian, 1986. "Two Stage and Related Estimators and Their Applications," Review of Economic Studies, Wiley Blackwell, vol. 53(4), pages 517-38, August.
- Sentana,E., 1995.
"Quadratic Arch Models,"
9517, Centro de Estudios Monetarios Y Financieros-.
- Enrique Sentana & Dante Amegual, 2008.
"A Comparison Of Mean-Variance Efficiency Tests,"
- Yves Dominicy & David Veredas, 2013. "The method of simulated quantiles," ULB Institutional Repository 2013/136280, ULB -- Universite Libre de Bruxelles.
- Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2010.
"Measuring systemic risk,"
1002, Federal Reserve Bank of Cleveland.
- Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-80, July.
- Chamberlain, Gary, 1983. "A characterization of the distributions that imply mean--Variance utility functions," Journal of Economic Theory, Elsevier, vol. 29(1), pages 185-201, February.
- Berkane, Maia & Bentler, P. M., 1986. "Moments of elliptically distributed random variates," Statistics & Probability Letters, Elsevier, vol. 4(6), pages 333-335, October.
- Jondeau, Eric & Rockinger, Michael, 2003. "Conditional volatility, skewness, and kurtosis: existence, persistence, and comovements," Journal of Economic Dynamics and Control, Elsevier, vol. 27(10), pages 1699-1737, August.
- Oliver Linton, 1993.
"Adaptive Estimation in ARCH Models,"
Cowles Foundation Discussion Papers
1054, Cowles Foundation for Research in Economics, Yale University.
- Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
- Durbin, J, 1970. "Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables," Econometrica, Econometric Society, vol. 38(3), pages 410-21, May.
- François Longin, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, 04.
- Bontemps, Christian, 2013. "Moment-Based Tests for Discrete Distributions," IDEI Working Papers 772, Institut d'Économie Industrielle (IDEI), Toulouse.
- Gabriele Fiorentini & Enrique Sentana, 2012. "Tests For Serial Dependence In Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.
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