References contributed by pfo235-2019140
Abadir, K. M., and J. R. Magnus (2005): Matrix Algebra. Cambridge University Press. Aielli, G. P. (2013): Dynamic Conditional Correlation: On Properties and Estimation, Journal of Business and Economic Statistics, 31, 282-299.
- Anderson, T. W. (2003): An Introduction to Multivariate Statistical Analysis. New York: Wiley, 3 edn.
Paper not yet in RePEc: Add citation now
Bauwens, L., S. Laurent, and J. V. K. Rombouts (2006): Multivariate GARCH Models: A Survey, Journal of Applied Econometrics, 21, 79-109.
Bera, A. K., and S. Kim (2002): Testing Constancy of Correlation and Other Specifications of the BGARCH Model with an Application to International Equity Returns, Journal of Empirical Finance, 9, 171-195.
Berben, R. P., and W. J. Jansen (2005): Comovement in International Equity Markets: A Sectoral View, Journal of International Money and Finance, 24, 832-857.
Bollerslev, T. (1987): A Conditionally Heteroskedastic Time Series Model for Security Prices and Rates of Return Data, Review of Economics and Statistics, 59, 542-547.
- Carroll, S. M., and B. W. Dickinson (1989): Construction of Neural Nets Using the Radon Transform, Proceedings of the International Joint Conference on Neural Networks, Washington, D.C., IEEE Press I, 607-611.
Paper not yet in RePEc: Add citation now
Castle, J. L., and D. F. Hendry (2010): A Low-Dimension Portmanteau Test for Non-Linearity, Journal of Econometrics, 150, 231-245.
Caulet, R., and A. Péguin-Feissolle (2000): Un test d’hétéroscédasticité conditionnelle inspiré de la modélisation en termes de réseaux neuronaux artificiels, Annales d’Économie et de Statistique, 59, 177-197.
Creal, D., S. J. Koopmans, and A. Lucas (2013): Generalized Autoregressive Score Models with Applications, Journal of Applied Econometrics, 28, 777-795.
- Cybenko, G. (1989): Approximation by Superpositions of a Sigmoid Function, Mathematics of Control, Signals and Systems, 2, 303-314.
Paper not yet in RePEc: Add citation now
- Ding, Z., and R. F. Engle (2001): Large Scale Conditional Covariance Matrix Modeling, Estimation and Testing, Academia Economic Papers, 29, 157-184.
Paper not yet in RePEc: Add citation now
- Engle, R. F. (2002): Dynamic Conditional Correlation – A Simple Class of Multivariate GARCH Models, Journal of Business and Economic Statistics, 20, 339-350.
Paper not yet in RePEc: Add citation now
Engle, R. F., and F. Kroner (1995): Multivariate Simultaneous Generalized ARCH, Econometric Theory, 11, 122-150.
Harvey, A. C. (2013): Dynamic Models for Volatility and Heavy Tails. Cambridge University Press.
Harvey, A., and G. Sucarrat (2014): EGARCH Models with Fat Tails, Skewness and Leverage, Computational Statistics and Data Analysis, 76, 320-338.
- Harvey, A., and S. Thiele (2014): Testing for Time Varying Correlation in a Dynamic Conditional Score Framework.
Paper not yet in RePEc: Add citation now
- Harvey, A., and T. Chakravarty (2008): Beta-t-(E)GARCH. Cambridge Working Papers in Economics, CWPE 0840.
Paper not yet in RePEc: Add citation now
- Hornik, K. (1991): Approximation Capabilities of Multilayer Feedforward Networks, Neural Networks, 4, 251-257.
Paper not yet in RePEc: Add citation now
- Hornik, K., M. Stinchcombe, and H. White (1989): Multi-Layer Feedforward Networks Are Universal Approximators, Neural Networks, 2, 359-366.
Paper not yet in RePEc: Add citation now
- Hornik, K., M. Stinchcombe, and H. White (1990): Universal Approximation of an Unknown Mapping and Its Derivatives Using Multi-Layer Feedforward Networks, Neural Networks, 3, 551-560.
Paper not yet in RePEc: Add citation now
Jeantheau, T. (1998): Strong Consistency of Estimators for Multivariate ARCH Models, Econometric Theory, 14, 70-86.
- Kamstra, M. (1993): A Neural Network Test for Heteroscedasticity. Working Paper, Simon Fraser University, Burnaby, Canada.
Paper not yet in RePEc: Add citation now
- Lütkepohl, H. (1996): Handbook of Matrices. Chichester: John Wiley & Sons.
Paper not yet in RePEc: Add citation now
Lebreton, M., and A. Péguin-Feissolle (2007): Robust Tests for Heteroscedasticity in a General Framework, Annales d’Économie et de Statistique, 85, 159-187.
- Lee, T. H., H. White, and C. W. J. Granger (1993): Testing for Neglecting Nonlinearity in Time Series Models, Journal of Econometrics, 56, 269-290.
Paper not yet in RePEc: Add citation now
- Péguin-Feissolle, A. (1999): A Comparison of the Power of Some Tests for Conditional Heteroscedasticity, Economics Letters, 63, 5-17.
Paper not yet in RePEc: Add citation now
Péguin-Feissolle, A., and B. Sanhaji (2015): Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models. Working Paper AMSE, WP 2015 Nr 16, Aix-Marseille University, France.
Péguin-Feissolle, A., and T. Teräsvirta (1999): A General Framework for Testing the Granger Noncausality Hypothesis. SSE/EFI Working Paper Series in Economics and Finance No. 343, Stockholm School of Economics.
Péguin-Feissolle, A., B. Strikholm, and T. Teräsvirta (2013): Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form, Communications in Statistics – Simulation and Computation, 42, 1063-1087.
Silvennoinen, A., and T. Teräsvirta (2005): Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations. SSE/EFI Working Paper Series in Economics and Finance No. 577, Stockholm School of Economics, Sweden.
- Silvennoinen, A., and T. Teräsvirta (2009a): Multivariate GARCH Models. In Handbook of Financial Time Series, Ed. by T. G. Andersen, R. A. Davis, J.-P. Kreiss, and T. Mikosch. New York: Springer, 201-229.
Paper not yet in RePEc: Add citation now
- Silvennoinen, A., and T. Teräsvirta (2009b): Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model, Journal of Financial Econometrics, 7, 373-411.
Paper not yet in RePEc: Add citation now
Silvennoinen, A., and T. Teräsvirta (2015): Modelling Conditional Correlations of Asset Returns: A Smooth Transition Approach, Econometric Reviews, 34, 174-197.
- Stinchcombe, M., and H. White (1989): Universal Approximation Using Feedforward Networks with Non-sigmoid Hidden Layer Activation Functions. In Proceedings of the international joint conference on neural networks, Washington, D.C., IEEE Press, I, 613-618.
Paper not yet in RePEc: Add citation now
Teräsvirta, T., C. F. Lin, and C. W. J. Granger (1993): Power of the Neural Network Linearity Test, Journal of Time Series Analysis, 14, 209-220.
Tse, Y. K. (2000): A Test for Constant Correlations in a Multivariate GARCH Model, Journal of Econometrics, 98, 107-127.