Volatility forecasting without data-snooping
No abstract is available for this item.
- Lux, Thomas & Kaizoji, Taisei, 2007.
"Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 31(6), pages 1808-1843, June.
- Thomas Lux & Taisei Kaizoji, 2006. "Forecasting Volatility and Volume in the Tokyo Stock Market: Long Memory, Fractality and Regime Switching," Working Papers wpn06-04, Warwick Business School, Finance Group.
- Taisei Kaizoji & Thomas Lux, 2006. "Forecasting Volatility and Volume in the Tokyo Stock Market: Long Memory, Fractality and Regime Switching," Working Papers wp06-20, Warwick Business School, Finance Group.
- Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006,13, Christian-Albrechts-University of Kiel, Department of Economics.
- Brailsford, Timothy J. & Faff, Robert W., 1996. "An evaluation of volatility forecasting techniques," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 419-438, April.
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- Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
- Bley, Jorg, 2011. "Are GCC stock markets predictable?," Emerging Markets Review, Elsevier, vol. 12(3), pages 217-237, September.
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- Ezzat, Hassan, 2012. "The Application of GARCH and EGARCH in Modeling the Volatility of Daily Stock Returns During Massive Shocks: The Empirical Case of Egypt," MPRA Paper 50530, University Library of Munich, Germany.
- Gita Persand & Chris Brooks, 2003. "Volatility forecasting for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(1), pages 1-22.
- repec:dau:papers:123456789/2138 is not listed on IDEAS
- Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
- Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
- Lux, Thomas & Kaizoji, Taisei, 2004. "Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models," Economics Working Papers 2004,05, Christian-Albrechts-University of Kiel, Department of Economics.
- Matei, Marius, 2010. "Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes," Working Papers of Institute for Economic Forecasting 100201, Institute for Economic Forecasting.
- Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
- Brooks, C. & Clare, A. D. & Persand, G., 2000. "A word of caution on calculating market-based minimum capital risk requirements," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1557-1574, October.
- Ezzat, Hassan, 2012. "The Application of GARCH Methods in Modeling Volatility Using Sector Indices from the Egyptian Exchange," MPRA Paper 51584, University Library of Munich, Germany.
- Frimpong, Joseph Magnus & Oteng-Abayie, Eric Fosu, 2006. "Modelling and Forecasting Volatility of Returns on the Ghana Stock Exchange Using GARCH Models," MPRA Paper 593, University Library of Munich, Germany, revised 07 Oct 2006.
- Blair, Bevan J. & Poon, Ser-Huang & Taylor, Stephen J., 2001. "Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 5-26, November.
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