Caporin, MassimilianoMcAleer, Michael2023-06-202023-06-202009-02Asai, M., M. McAleer and J. Yu (2006), Multivariate Stochastic Volatility: A Review, Econometric Reviews, 25, 145-175. Bollerslev, T. (1986), Generalised Autoregressive Conditional Heteroscedasticity, Journal of Econometrics, 31, 307-327. Caporin, M. and M. McAleer (2008), Scalar BEKK and Indirect DCC, Journal of Forecasting, 27, 537-549. Engle, R.F. (1982), Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 50, 987-1007. Engle, R.F. (2002), Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models, Journal of Business and Economic Statistics, 20, 339-350. Engle, R.F. and K.F. Kroner (1995), Multivariate Simultaneous Generalized ARCH, Econometric Theory, 11, 122-150. Ling, S. and M. McAleer (2003), Asymptotic Theory for a Vector ARMA-GARCH Model, Econometric Theory, 19, 278-308. McAleer. M. and M.C. Medeiros (2008), Realized Volatility: A Review, Econometric Reviews, 27, 10-45.https://hdl.handle.net/20.500.14352/49251Massimiliano Caporin pertenece a la Università degli Studi di Padova, Dipartimento di Scienze Economiche “Marco Fanno”.Modeling volatility, or “predictable changes” over time and space in a variable, is crucial in the natural and social sciences. Life can be volatile, and anything that matters, and which changes over time and space, involves volatility. Without volatility, many temporal and spatial variables would simply be constants. Our purpose is to propose a scientific classification of the alternative volatility models and approaches that are available in the literature, following the Linnaean taxonomy. This scientific classification is used because the literature has evolved as a living organism, with the birth of numerous new species of models.engtechnical reporthttps://www.ucm.es/icaeopen accessEstadística matemática (Estadística)1209 Estadística