Publication:
The Fiction of Full BEKK: Pricing Fossil Fuels and Carbon Emissions

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2018-03
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The purpose of the paper is to (i) show that univariate GARCH is not a special case of multivariate GARCH, specifically the Full BEKK model, except under parametric restrictions on the off-diagonal elements of the random coefficient autoregressive coefficient matrix, that are not consistent with Full BEKK, and (ii) provide the regularity conditions that arise from the underlying random coefficient autoregressive process, for which the (quasi-) maximum likelihood estimates (QMLE) have valid asymptotic properties under the appropriate parametric restrictions. The paper provides a discussion of the stochastic processes that lead to the alternative specifications, regularity conditions, and asymptotic properties of the univariate and multivariate GARCH models. It is shown that the Full BEKK model, which in empirical practice is estimated almost exclusively compared with Diagonal BEKK (DBEKK), has no underlying stochastic process that leads to its specification, regularity conditions, or asymptotic properties, as compared with DBEKK. An empirical illustration shows the differences in the QMLE of the parameters of the conditional means and conditional variances for the univariate, DEBEKK and Full BEKK specifications.
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Revised: March 2018. The authors are most grateful to the Editor and a reviewer for very helpful comments and suggestions. For financial support, the first author wishes to thank the National Science Council, Ministry of Science and Technology (MOST), Taiwan, and the second author acknowledges the Australian Research Council and the National Science Council, Ministry of Science and Technology (MOST), Taiwan
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Amemiya, T. (1985), Advanced Econometrics, Harvard University Press, Cambridge, MA, USA. Baba, Y., R.F. Engle, D. Kraft, and K.F. Kroner (1985), Multivariate simultaneous generalized ARCH, Unpublished manuscript, Department of Economics, University of California, San Diego, CA, USA. Bollerslev, T. (1986), Generalised autoregressive conditional heteroscedasticity, Journal of Econometrics, 31, 307-327. Chang, C.-L, M. McAleer and Y.-A. Wang (2018), Modelling volatility spillovers for bio-ethanol, sugarcane and corn spot and futures prices, Renewable and Sustainable Energy Reviews, 81, 1002-1018. Chang, C.-L., M. McAleer and G.D. Zuo (2017), Volatility spillovers and causality of carbon emissions, oil and coal spot and futures for the EU and USA, Sustainability, 9(10:1789), 1-21. Dickey, D.A. and W.A. Fuller (1979), Distribution of the estimators for autoregressive time series with a unit root Journal of the American Statistical Association, 74, 427-431. Dickey, D.A. and W.A. Fuller (1981), Likelihood ratio statistics for autoregressive time series with a unit root, Econometrica, 49, 1057-1072. Elliott, G., T.J. Rothenberg, and J.H. Stock (1996), Efficient tests for an autoregressive unit root, Econometrica, 64, 813-836. Engle, R.F. (1982), Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50, 987-1007. Engle, R.F. and K.F. Kroner (1995), Multivariate simultaneous generalized ARCH, Econometric Theory, 11(1), 122-150. Glosten, L.R., R. Jagannathan, and D.E. Runkle (1993), On the relation between the expected value and volatility of nominal excess return on stocks, Journal of Finance, 48(5), 1779-1801. Jeantheau, T. (1998), Strong consistency of estimators for multivariate ARCH models, Econometric Theory, 14, 70-86. Kwiatkowski, D., P.C.B. Phillips, P. Schmidt, and Y. Shin (1992), Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?, Journal of Econometrics 54, 159-178. Ling, S. and M. McAleer (2003), Asymptotic theory for a vector ARMA-GARCH model, Econometric Theory, 19, 278-308. McAleer, M. (2014), Asymmetry and leverage in conditional volatility models, Econometrics, 2(3), 145-150. McAleer, M., F. Chan, S. Hoti and O. Lieberman (2008), Generalized autoregressive conditional correlation, Econometric Theory, 24(6), 1554-1583. McAleer, M. and C. Hafner (2014), A one line derivation of EGARCH, Econometrics, 2(2), 92-97. Nelson, D.B. (1990), ARCH models as diffusion approximations, Journal of Econometrics, 45(1-2), 7-38. Nelson, D.B. (1991), Conditional heteroskedasticity in asset returns: A new approach, Econometrica, 59(2), 347-370. Said, S.E. and D.A. Dickey (1984), Testing for unit roots in autoregressive-moving average models of unknown order, Biometrika, 71, 599-607. Tsay, R. S. (1987), Conditional heteroscedastic time series models, Journal of the American Statistical Association, 82(398), 590-604.