Measuring economic uncertainty using news-media textual data

I identify well-defined uncertainty measures related to categories of high economic relevance such as Oil price, Monetary policy, Politics, and Stock market.. Using textual

1 Simple update example: The upper plots present the results for a case with uncorrelated measurement errors, while the lower plots give the results when using measurements

The results show that neither overall analysis nor analysis with the control for dominant religion proved the hypothesis that Protestants have significantly higher values and

In particular, by decomposing the textual data into daily news topics, and using a mixed frequency time-varying Dynamic Factor Model, I show that it is possible to obtain nowcasts

Then we investigate, using a simple linear model, the relation between ensemble size, number of measurements, measurement uncertainty, and the accuracy of the estimated covariance

In this case study we have shown that by using automated text analysis methods like LDA to find the sub-topics within a news story we can describe who the most important persons

We describe two techniques for rendering isosurfaces in multiresolution volume data such that the uncertainty (error) in the data is shown in the resulting visualization.. In

Dynamic news entity visualization shows an implementation of visualizing news entity data to give an overview as well as to display emerging and vanishing news topics.. We present