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Are central bankers inflation nutters? : an MCMC estimator of the long-memory üarameter in a state space model
Andersson, Fredrik N. G.; Li, Yushu - In: Computational economics 55 (2020) 2, pp. 529-549
Persistent link: https://www.econbiz.de/10012223649
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Modeling persistence and parameter instability in historical crude oil price data using a gibbs sampling approach
Nonejad, Nima - In: Computational economics 53 (2019) 4, pp. 1687-1710
Persistent link: https://www.econbiz.de/10012135601
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Bayesian unit root test in double threshold heteroskedastic models
Chen, Cathy W. S.; Chen, Shu-yu; Lee, Sangyeol - In: Computational economics 42 (2013) 4, pp. 471-490
Persistent link: https://www.econbiz.de/10010249863
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Forecasting financial returns volatility : a GARCH-SVR model
Sun, Hao; Yu, Bo - In: Computational economics 55 (2020) 2, pp. 451-471
Persistent link: https://www.econbiz.de/10012223641
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A hybrid metaheuristic for the efficient solution of GARCH with trend models
Uribe, Lourdes; Perea, Benjamin; Hernández del Valle, … - In: Computational economics 52 (2018) 1, pp. 145-166
Persistent link: https://www.econbiz.de/10012052926
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GARCHNet: Value‑at‑risk forecasting with GARCH models based on neural networks
Buczynski, Mateusz; Chlebus, Marcin - In: Computational economics 63 (2024) 5, pp. 1949-1979
Persistent link: https://www.econbiz.de/10014550845
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CO2 emission allowances risk prediction with gas and GARCH models
Trabelsi, Nader; Tiwari, Aviral Kumar - In: Computational economics 61 (2023) 2, pp. 775-805
Persistent link: https://www.econbiz.de/10014228462
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Proofs and predictions in human problem solving
Velupillai, Kumaraswamy - In: Computational economics 57 (2021) 3, pp. 935-947
Persistent link: https://www.econbiz.de/10012543226