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evaluation. An important implication is that forecasting superiority of models using high frequency data is likely to be …
Persistent link: https://www.econbiz.de/10008491711
been proposed. A related strand of literature focuses on dynamic models and covariance forecasting for high-frequency data … address, is the relative importance of the quality of the realized measure as an input in a given forecasting model vs. the …
Persistent link: https://www.econbiz.de/10008462028
A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave...
Persistent link: https://www.econbiz.de/10005002781
Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative...
Persistent link: https://www.econbiz.de/10005530935