.e. overreact), their forecast revisions are too intense, and the converse occurs when they underreact. As a proxy for uncertainty … sample using analyst forecast dispersion as a proxy for uncertainty and obtain similar results. We also document the fact …This article examines the link between uncertainty and analysts' reaction to earnings announcements for a sample of …

-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …

outline a novel model that considers the non-linear relationship between inattentiveness and aggregate uncertainty, which … crucially distinguishes between macro-economic and data ( measurement error) uncertainty. The empirical analysis uses the Survey …

-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …

analytical insights and other findings concerning ‘(un)certainty’ to decision-maker end-users; and mitigating risk. It also …Generating Cyber Intelligence (CYBINT) scenarios & solutions to address uncertainty for decision-advantage: Using … -- More than Semantics? Communication of (Un)certainty via ‘Estimative/Probabilistic Language’ -- Estimative …