Modelling Oil Price Volatility with the Beta-Skew-t-EGARCH Framework
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References listed on IDEAS
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Cited by:
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- Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Does Predictive Ability of an Asset Price Rest in 'Memory'? Insights from a New Approach," Working Papers of BETA 2019-43, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019.
"Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model,"
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07-19, Association Française de Cliométrie (AFC).
- Mohamed Chikhi & Claude Diebolt & Tapas Mishra, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers of BETA 2019-24, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
- Bala A. Dahiru & Pam W. Jim & Kalu N. Nwonyuku, 2017. "Equity markets volatility dynamics in developed and newly emerging economies: EGARCH-with-skewed-t density approach," Economics Bulletin, AccessEcon, vol. 37(4), pages 2394-2412.
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More about this item
Keywords
Oil price; Volatility; Student's t; Skewness; Leverage; Persistence;All these keywords.
JEL classification:
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
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