Measuring extreme risk dependence between the oil and gas markets
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DOI: 10.1007/s10479-020-03796-1
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- Tiwari, Aviral Kumar & Sharma, Gagan Deep & Rao, Amar & Hossain, Mohammad Razib & Dev, Dhairya, 2024. "Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting," Energy Economics, Elsevier, vol. 134(C).
- Lu, Xunfa & He, Pengchao & Zhang, Zhengjun & Apergis, Nicholas & Roubaud, David, 2024. "Extreme co-movements between decomposed oil price shocks and sustainable investments," Energy Economics, Elsevier, vol. 134(C).
- Cui, Jinxin & Alshater, Muneer M. & Mensi, Walid, 2023. "Higher-order moment risk spillovers and optimal portfolio strategies in global oil markets," Resources Policy, Elsevier, vol. 86(PA).
- Jain, Prachi & Maitra, Debasish, 2023. "Risk implications of dependence in the commodities: A copula-based analysis," Global Finance Journal, Elsevier, vol. 57(C).
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More about this item
Keywords
Systemic risk; VaR; CoVar; Dynamic copula; Intraday data;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G1 - Financial Economics - - General Financial Markets
- Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
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