Bollerslev T. Generalized autoregressive conditional heteroskedasticity [J]. Journal of Econometrics,1986,31(3):307-327.
[2]
Bollerslev T. A conditional heteroskedastic time series model for speculative prices and rates of return [J]. Review of Economics and Statistics, 1987,69(3):542-547.
[3]
Hung J C, Lee M C, Liu H C. Estimation of Value-at-Risk for energy commodities via fat-tailed GARCH models [J]. Energy Economics,2008,30(3):1173-1191.
[4]
Theodossiou P. Financial data and the skewed generalized t distribution [J]. Management Science, 1998,(44):1650-1661.
[5]
Wilhelmsson A. GARCH forecasting performance under different distribution assumptions [J]. Journal of Forecasting,2006,(25):561-578.
[6]
Chuang I Y, Lu J R, Lee P H. Forecasting volatility in the financial markets: A comparison of alternative distributional assumptions [J]. Applied Financial Economics,2007, 17(3):1051-1060.
[7]
Nelson D B. Conditional heterskedasticity in asset returns: A new approach [J]. Econometrica,1991,59(12):347-370.
[8]
Glosten L, Jagannathan R, Runkle D. On the relation between the expected value and the volatility nominal excess return on stocks [J]. Journal of Finance,1993,48(5):1779-1801.
[9]
Engle R F, Ng V K. Measuring and testing the impact of news on volatility [J]. Journal of Finance, 1993,48(5): 1749-1778.
[10]
Taylor J W. Volatility forecasting with smooth transition exponential smoothing [J]. International Journal of Forecasting, 2004, 20(2): 273-286.
[11]
Loudon G F, Watt W H, Yadav P K. An empirical analysis of alternative parametric ARCH models [J]. Journal of Applied Econometrics,2000,15(2):117-136. 3.0.CO;2-4 target="_blank">
[12]
Evans T, McMillan D G. Volatility forecasts: The role of asymmetric and long-memory dynamics and regional evidence [J]. Applied Financial Economics, 2007,17(17):1421-1430.
[13]
Awartani B M A, Corradi V. Predicting the volatility of the S&P-500 stock index via GARCH models: The role of asymmetries [J]. International Journal of Forecasting,2005,21(1): 167-183.
[14]
Brooks C, Persand G. Model choice and Value-at-Risk performance [J].Financial Analysts Journal, 2002,58(5): 87-97.
[15]
Sadorsky P. Modeling and forecasting petroleum futures volatility[J]. Energy Economics,2006,28(4):467-488.
Andersen T G, Bollerslev T, Meddahi N. Correcting the errors: Volatility forecast evaluation using high frequency data and realizedvolatilities [J], Econometrica, 2005, 73( 1) : 279-296.