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A machine learning approach to volatility forecasting
Christensen, Kim; Siggaard, Mathias Voldum; Veliyev, … - 2021
Persistent link: https://www.econbiz.de/10012434010
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Tree-based synthetic control methods : consequences of moving the US embassy
Mühlbach, Nicolaj N. - 2020 - This version: May 18, 2020
Persistent link: https://www.econbiz.de/10012317688
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A neural network approach to the environmental Kuznets curve
Bennedsen, Mikkel; Hillebrand, Eric; Jensen, Sebastian - 2022
Persistent link: https://www.econbiz.de/10013367388
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Long memory and tail dependence in trading volume and volatility
Rossi, Eduardo; Santucci de Magistris, Paolo - 2009
Persistent link: https://www.econbiz.de/10003863172
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A no arbitrage fractional cointegration analysis of the range based volatility
Rossi, Eduardo; Santucci de Magistris, Paolo - 2009
Persistent link: https://www.econbiz.de/10003863181
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The shape and term structure of the index option smirk : why multifactor stochastic volatility models work so well
Christoffersen, Peter F.; Heston, Steven L.; Jacobs, Kris - 2009
Persistent link: https://www.econbiz.de/10003865680
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Evaluating value-at-risk models with desk-level data
Christoffersen, Peter F.; Berkowitz, Jeremy; Pelletier, … - 2009
Persistent link: https://www.econbiz.de/10003865687
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The dividend-price ratio does predict dividend growth : international evidence
Engsted, Tom; Pedersen, Thomas Q. - 2009
Persistent link: https://www.econbiz.de/10003865691
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Forecasting inflation with gradual regiem shifts and exogenous information
González, Andrés; Hubrich, Kirstin; Teräsvirta, Timo - 2009
Persistent link: https://www.econbiz.de/10003849428
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First and second order non-linear cointegration models
Lange, Theis - 2009
Persistent link: https://www.econbiz.de/10003849457