A component model for dynamic correlations
We propose a model of dynamic correlations with a short- and long-run component specification, by extending the idea of component models for volatility. We call this class of models DCC-MIDAS. The key ingredients are the Engle (2002) DCC model, the Engle and Lee (1999) component GARCH model replacing the original DCC dynamics with a component specification and the Engle etÂ al. (2006) GARCH-MIDAS specification that allows us to extract a long-run correlation component via mixed data sampling. We provide a comprehensive econometric analysis of the new class of models, and provide extensive empirical evidence that supports the model's specification.
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- Robert Engle & Neil Shephard & Kevin Shepphard, 2008.
"Fitting vast dimensional time-varying covariance models,"
OFRC Working Papers Series
2008fe30, Oxford Financial Research Centre.
- Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
- Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-63, July.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006.
"Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 4(4), pages 537-572.
- Sheppard, Kevin & Cappiello, Lorenzo & Engle, Robert F., 2003. "Asymmetric dynamics in the correlations of global equity and bond returns," Working Paper Series 0204, European Central Bank.
- Tobias Adrian & Joshua Rosenberg, 2008.
"Stock Returns and Volatility: Pricing the Short-Run and Long-Run Components of Market Risk,"
Journal of Finance,
American Finance Association, vol. 63(6), pages 2997-3030, December.
- Tobias Adrian & Joshua Rosenberg, 2006. "Stock returns and volatility: pricing the short-run and long-run components of market risk," Staff Reports 254, Federal Reserve Bank of New York.
- Engle, Robert & Colacito, Riccardo, 2006. "Testing and Valuing Dynamic Correlations for Asset Allocation," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 238-253, April.
- McAleer, Michael & Chan, Felix & Hoti, Suhejla & Lieberman, Offer, 2008. "Generalized Autoregressive Conditional Correlation," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1554-1583, December.
- 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.
- Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, 06.
- Christoffersen, Peter & Jacobs, Kris & Ornthanalai, Chayawat & Wang, Yintian, 2008.
"Option valuation with long-run and short-run volatility components,"
Journal of Financial Economics,
Elsevier, vol. 90(3), pages 272-297, December.
- Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai & Yintian Wang, 2008. "Option Valuation with Long-run and Short-run Volatility Components," CREATES Research Papers 2008-11, School of Economics and Management, University of Aarhus.
- Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2007.
"The determinants of stock and bond return comovements,"
Working Paper Research
119, National Bank of Belgium.
- Lieven Baele, 2010. "The Determinants of Stock and Bond Return Comovements," Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2374-2428, June.
- Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2009. "The Determinants of Stock and Bond Return Comovements," NBER Working Papers 15260, National Bureau of Economic Research, Inc.
- Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
- G. William Schwert, 1990.
"Why Does Stock Market Volatility Change Over Time?,"
NBER Working Papers
2798, National Bureau of Economic Research, Inc.
- Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-53, December.
- Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003.
"Alternative models for stock price dynamics,"
Journal of Econometrics,
Elsevier, vol. 116(1-2), pages 225-257.
- Robert F. Engle & Kevin Sheppard, 2001.
"Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH,"
NBER Working Papers
8554, National Bureau of Economic Research, Inc.
- Engle, Robert F & Sheppard, Kevin K, 2001. "Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH," University of California at San Diego, Economics Working Paper Series qt5s2218dp, Department of Economics, UC San Diego.
- A. Ronald Gallant & Chien-Te Hsu & George Tauchen, 1999.
"Using Daily Range Data To Calibrate Volatility Diffusions And Extract The Forward Integrated Variance,"
The Review of Economics and Statistics,
MIT Press, vol. 81(4), pages 617-631, November.
- Gallant, A. Ronald & Hsu, Chien-Te & Tauchen, George, 2000. "Using Daily Range Data to Calibrate Volatility Diffusions and Extract the Forward Integrated Variance," Working Papers 00-04, Duke University, Department of Economics.
- Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank, Research Department.
- Comte, F. & Lieberman, O., 2003. "Asymptotic theory for multivariate GARCH processes," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 61-84, January.
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