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Do high-frequency stock market data help forecast crude oil prices? : evidence from the MIDAS models
Zhang, Yue-jun; Wang, Jin-Li - In: Energy economics 78 (2019), pp. 192-201
Persistent link: https://www.econbiz.de/10012159923
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Forecasting crude oil prices with shrinkage methods : can nonconvex penalty and Huber loss help?
Xing, Li-Min; Zhang, Yue-jun - In: Energy economics 110 (2022), pp. 1-19
Persistent link: https://www.econbiz.de/10013349910
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Do oil-price shocks predict the realized variance of U.S. REITs?
Bonato, Matteo; Çepni, Oğuzhan; Gupta, Rangan; … - In: Energy economics 104 (2021), pp. 1-19
Persistent link: https://www.econbiz.de/10013364407
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Forecasting the realized variance of oil-price returns using machine learning : is there a role for U.S. state-level uncertainty?
Çepni, Oğuzhan; Gupta, Rangan; Pienaar, Daniel; … - In: Energy economics 114 (2022), pp. 1-14
Persistent link: https://www.econbiz.de/10013477404