References Black, F. (1976), Studies of stock market volatility changes, in 1976 Proceedings of the American Statistical Association, Business & Economic Statistics Section, pp. 177-181. Bollerslev, T. (1986), Generalised autoregressive conditional heteroscedasticity, Journal of Econometrics, 31, 307-327. Brenner, M., E.Y. Ou and J.E. Zhang (2006), Hedging volatility risk, Journal of Banking and Finance, 30, 811-821. Caporin, M. and M. McAleer (2010), Model selection and testing of conditional and stochastic volatility models, to appear in L. Bauwens, C. Hafner and S. Laurent (eds.), Handbook on Financial Engineering and Econometrics: Volatility Models and Their Applications, Wiley, New York. Available at SSRN: http://ssrn.com/abstract=1676826. Caporin, M. and M. McAleer (2011), Do we really need both BEKK and DCC? A tale of two multivariate GARCH models, to appear in Journal of Economic Surveys. Chang, C.-L., J.-A. Jimenez-Martin, M. McAleer and T. Perez Amaral (2011), Risk management of risk under the Basel Accord: Forecasting value-at-risk of VIX futures, Managerial Finance, 37, 1088-1206. Available at SSRN: http://ssrn.com/abstract=1765202. Chicago Board Options Exchange (2003), VIX: CBOE volatility index, Working paper, Chicago. Engle, R.F. (1982), Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica, 50, 987-1007. Glosten, L., R. Jagannathan and D. Runkle (1992), On the relation between the expected value and volatility of nominal excess return on stocks, Journal of Finance, 46, 1779-1801. Huskaj, B. (2009), A value-at-risk analysis of VIX futures: Long memory, heavy tails, and asymmetry. Available at SSRN: http://ssrn.com/abstract=1495229. Ishida, I., M. McAleer and K. Oya (2011), Estimating the leverage parameter of continuous-time stochastic volatility models using high frequency S&P500 and VIX, Managerial Finance, 37, 1048-1067. Li, W.K., S. Ling and M. McAleer (2002), Recent theoretical results for time series models with GARCH errors, Journal of Economic Surveys, 16, 245-269. Reprinted in M. McAleer and L. Oxley (eds.), Contributions to Financial Econometrics: Theoretical and Practical Issues, Blackwell, Oxford, 2002, pp. 9-33. Ling, S. and M. McAleer (2002a), Stationarity and the existence of moments of a family of GARCH processes, Journal of Econometrics, 106, 109-117. Ling, S. and M. McAleer (2002b), Necessary and sufficient moment conditions for the GARCH(r,s) and asymmetric power GARCH(r,s) models, Econometric Theory, 18, 722-729. Ling, S. and M. McAleer, (2003a), Asymptotic theory for a vector ARMA-GARCH model, Econometric Theory, 19, 278-308. Ling, S. and M. McAleer (2003b), On adaptive estimation in nonstationary ARMA models with GARCH errors, Annals of Statistics, 31, 642-674. McAleer, M. (2005), Automated inference and learning in modeling financial volatility, Econometric Theory, 21, 232-261. McAleer, M., F. Chan and D. Marinova (2007), An econometric analysis of asymmetric volatility: theory and application to patents, Journal of Econometrics, 139, 259-284. McAleer, M., J.-Á. Jiménez-Martin and T. Pérez-Amaral (2010), Has the Basel II Accord encouraged risk management during the 2008-09 financial crisis?, Available at SSRN: http://ssrn.com/abstract=1397239. McAleer, M. and C. Wiphatthanananthakul (2010), A simple expected volatility (SEV) index: Application to SET50 index options, Mathematics and Computers in Simulation, 80, 2079-2090. Nelson, D.B. (1991), Conditional heteroscedasticity in asset returns: A new approach, Econometrica, 59, 347-370. Sepp, A. (2008), VIX option pricing in a jump-diffusion model, Risk Magazine, April, 84-89. Shephard, N. (1996), Statistical aspects of ARCH and stochastic volatility, in O.E. Barndorff- Nielsen, D.R. Cox and D.V. Hinkley (eds.), Statistical Models in Econometrics, Finance and Other Fields, Chapman & Hall, London, 1-67. Whaley, R.E. (1993), Derivatives on market volatility: Hedging tools long overdue, Journal of Derivatives, 1, 71-84. Zhang, J.E. and Y. Huang (2010), The CBOE S&P500 three-month variance futures, Journal of Futures Markets, 30, 48-70.