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We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …
Persistent link: https://www.econbiz.de/10012545165
We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …
Persistent link: https://www.econbiz.de/10012795319
A major problem in applying neural networks is specifying the sizeof the network. Even for moderately sized networks the number ofparameters may become large compared to the number of data. In thispaper network performance is examined while reducing the size of thenetwork through the use of...
Persistent link: https://www.econbiz.de/10010371106
Persistent link: https://www.econbiz.de/10000976085
Forecasts from various experts are often used in macroeconomic forecasting models. Usually the focus is on the mean or median of the survey data. In the present study we adopt a different perspective on the survey data as we examine the predictive power of disagreement amongst forecasters. The...
Persistent link: https://www.econbiz.de/10011381819
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Persistent link: https://www.econbiz.de/10008654192
We present new results for the likelihood-based analysis of the dynamic factor model that possibly includes intercepts and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are specified as autoregressive processes with mutually...
Persistent link: https://www.econbiz.de/10011373811
conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte …
Persistent link: https://www.econbiz.de/10011377261