Volatility forecasting by quantile regression

References

• Baillie , RT , Bollerslev , T and Mikkelsen , HO . 1996 . Fractionally integrated generalized autoregressive conditional heteroscedasticity . Journal of Econometrics , 74 : 3 – 30 .
   Web of Science ®Google Scholar
• Bollerslev , T . 1986 . Generalized autoregressive conditional heteroscedasticity . Journal of Econometrics , 31 : 307 – 28 .
   Web of Science ®Google Scholar
• Cai , J . 1994 . A Markov model of unconditional variance in ARCH . Journal of Business and Economic Statistics , 12 : 309 – 16 .
   Web of Science ®Google Scholar
• Carr , P , Geman , H , Madan , DB and Yor , M . 2003 . Stochastic volatility for Lévy processes . Mathematical Finance , 13 : 345 – 82 .
   Web of Science ®Google Scholar
• Chiou , J , Wu , P , Chang , A and Huang , B . 2007 . The asymmetric information and price manipulation in stock market . Applied Economics , 39 : 883 – 91 .
   Web of Science ®Google Scholar
• Engle , RF and Manganelli , S . 2004 . CAViaR: conditional autoregressive value at risk by regression quantiles . Journal of Business and Economic Statistics , 22 : 367 – 81 .
   Web of Science ®Google Scholar
• Fabozzi , FJ , Racheva-Iotova , B and Stoyanov , V . 2006 . An empirical examination of the return distribution characteristics of agency mortgage pass-through securities . Applied Financial Economics , 16 : 1085 – 94 .
   Google Scholar
• Fornari , F and Mele , A . 1997 . Sign- and volatility-switching ARCH models: theory and applications to international stock markets . Journal of Applied Econometrics , 12 : 49 – 65 .
   Web of Science ®Google Scholar
• Ghysels , E , Harvey , A and Renault , E . 1996 . “ Stochastic volatility ” . In Handbook of Statistics: Statistical Methods in Finance , Edited by: Maddala , GS and Rao , CR . Vol. 14 , 119 – 91 . Amsterdam : Elsevier Science .
   Google Scholar
• Glosten , LR , Jagannathan , R and Runkle , DE . 1993 . On the relation between the expected value and the volatility of the normal excess return on stocks . Journal of Finance , 48 : 1779 – 801 .
   Web of Science ®Google Scholar
• Gray , SF . 1996 . Modeling the conditional distribution of interest rates as a regime-switching process . Journal of Financial Economics , 42 : 27 – 62 .
   Web of Science ®Google Scholar
• Hamilton , JD and Susmel , R . 1994 . Autoregressive conditional heteroscedasticity and changes in regime . Journal of Econometrics , 64 : 307 – 33 .
   Web of Science ®Google Scholar
• Hull , J and White , A . 1998 . Value at risk when daily changes in market variables are not normally distribute . The Journal of Derivatives , 5 : 9 – 19 .
   Google Scholar
• Klaassen , F . 2002 . Improving GARCH volatility forecasts with regime-switching GARCH . Empirical Economics , 27 : 363 – 94 .
   Web of Science ®Google Scholar
• Kuester , K , Mittnik , S and Paolella , MS . 2006 . Value-at-Risk prediction: a comparison of alternative strategies . Journal of Financial Econometrics , 4 : 53 – 89 .
   Google Scholar
• Li , LM . 2007 . Volatility states and international diversification of international stock markets . Applied Economics , 39 : 1867 – 76 .
   Web of Science ®Google Scholar
• Maris , K , Nikolopoulos , K , Giannelos , K and Assimakopoulos , V . 2007 . Options trading driven by volatility directional accuracy . Applied Economics , 39 : 253 – 60 .
   Web of Science ®Google Scholar
• Neftci , SN . 2000 . Value at risk calculations, extreme events, and tail estimation . The Journal of Derivatives , 7 : 23 – 37 .
   Google Scholar
• Nelson , DB . 1990 . Stationarity and persistence in the GARCH(1,1) model . Econometric Theory , 6 : 318 – 34 .
   Web of Science ®Google Scholar
• Nelson , DB . 1991 . Conditional heteroskedasticity in asset returns: a new approach . Econometrica , 59 : 347 – 70 .
   Web of Science ®Google Scholar
• Noh , J and Kim , TH . 2006 . Forecasting volatility of futures market: the S&P 500 and FTSE 100 futures using high frequency returns and implied volatility . Applied Economics , 38 : 395 – 413 .
   Web of Science ®Google Scholar
• Pearson , ES and Tukey , JW . 1965 . Approximate means and standard deviations based on distances between percentage points of frequency curves . Biometrika , 52 : 533 – 46 .
   Web of Science ®Google Scholar
• Poon , S and Granger , C . 2003 . Forecasting volatility in financial markets: a review . Journal of Economic Literature , 41 : 478 – 539 .
   Web of Science ®Google Scholar
• Taylor , JW . 2005 . Generating volatility forecasts from value at risk estimates . Management Science , 51 : 712 – 25 .
   Web of Science ®Google Scholar
• Taylor , SJ . 1986 . Modelling Financial Time Series , New York : John Wiley & Sons .
   Google Scholar
• Venkataraman , S . 1997 . Value at risk for a mixture of normal distributions: the use of quasi-Bayesian estimation techniques . Economic Perspectives , 21 : 2 – 13 .
   Google Scholar
• Wu , L . 2008 . “ Modeling financial security returns using Lévy processes ” . In Handbooks in Operations Research and Management Science , Edited by: Birge , J and Linetsky , V . 117 – 62 . Amsterdam : Elsevier Science .
   Google Scholar