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An artificial neural network-GARCH model for international stock return volatility

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Donaldson, R. Glen
Kamstra, Mark

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File URL: http://www.sciencedirect.com/science/article/B6VFG-3SWTKRP-2/2/d2765b388f2a341d56849fdd1729905d
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Article provided by Elsevier in its journal Journal of Empirical Finance.

Volume (Year): 4 (1997)
Issue (Month): 1 (January)
Pages: 17-46
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Handle: RePEc:eee:empfin:v:4:y:1997:i:1:p:17-46

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  1. Valeriy Gavrishchaka & Supriya Banerjee, 2006. "Support Vector Machine as an Efficient Framework for Stock Market Volatility Forecasting," Computational Management Science, Springer, vol. 3(2), pages 147-160, April. [Downloadable!] (restricted)
  2. Renaud Caulet & Anne Peguin-feissolle, 2000. "Un test d'hétéroscédasticité conditionnelle inspiré de la modélisation en termes de réseaux neuronaux artificiels," Annales d'Economie et de Statistique, ADRES, issue 59, pages 09, Juillet-S. [Downloadable!]
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  3. Georgios Kouretas & Eleni Constantinou & Robert Georgiades & Avo Kazandjian, 2005. "Regime Switching and Artificial Neural Network Forecasting of the Cyprus Stock Exchange Daily Returns," Money Macro and Finance (MMF) Research Group Conference 2005 46, Money Macro and Finance Research Group. [Downloadable!]
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  4. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, School of Economics and Management, University of Aarhus. [Downloadable!]
  5. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2003. "Winter Blues: A SAD Stock Market Cycle," American Economic Review, American Economic Association, vol. 93(1), pages 324-343, March. [Downloadable!]
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  6. Menelaos Karanasos & J. Kim, . "Moments of the ARMA-EGARCH Model," Discussion Papers 00/29, Department of Economics, University of York. [Downloadable!]
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  7. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315. [Downloadable!]
  8. 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. [Downloadable!]
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  9. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer, vol. 14(1), pages 112-124, February. [Downloadable!] (restricted)
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  10. Teo Jasic & Douglas Wood, 2004. "The profitability of daily stock market indices trades based on neural network predictions: case study for the S&P 500, the DAX, the TOPIX and the FTSE in the period 1965-1999," Applied Financial Economics, Taylor and Francis Journals, vol. 14(4), pages 285-297, January. [Downloadable!] (restricted)
  11. Arie Preminger & Uri Ben-Zion & David Wettstein, 2006. "Extended switching regression models with time-varying probabilities for combining forecasts," European Journal of Finance, Taylor and Francis Journals, vol. 12(6-7), pages 455-472, October. [Downloadable!] (restricted)
  12. Glen Donaldson & Mark Kamstra, 2004. "Volatility forecasts, trading volume, and the ARCH versus option-implied volatility trade-off," Working Paper 2004-6, Federal Reserve Bank of Atlanta. [Downloadable!]
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  13. HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & VAN DIJK, Herman K., 2005. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," CORE Discussion Papers 2005029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
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  14. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Regime Switching and Artificial Neural Network Forecasting," Working Papers 0502, University of Crete, Department of Economics. [Downloadable!]
  15. Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2008. "Support Vector Regression Based GARCH Model with Application to Forecasting Volatility of Financial Returns," SFB 649 Discussion Papers SFB649DP2008-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
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