Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)
Reference28 articles.
1. Andersen, T. G., & Bollerslev, T. (1998). Answering the skeptics: Yes, standard volatility models do provide accurate forecasts. International Economic Review, 39, 885–905.
2. Baillie, R. T., Bollerslev, T., & Mikkelsen, H. O. (1996). Fractionally integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 74, 3–30.
3. Bernard, J., Khalaf, L., Kichian, M., & Mcmahon, S. (2008). Forecasting commodity prices: GARCH, jumps, and mean reversion. Journal of Forecasting, 27, 279–291.
4. Bezerra, P. C. S., & Albuquerque, P. H. M. (2017). Volatility forecasting via SVR-GARCH with mixture of gaussian kernels. Computational Management Science, 14, 179–196.
5. Bildirici, M., & Ersin, O. O. (2013). Support vector machine GARCH models in modeling conditional volatility: An application to Turkish financial markets. Conference Report, 13th International Conference on Econometrics, Operations Research and Statistics ICEOS, Famagusta, North Cyprus.
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