This paper considers sampling in proportion to size from a partly unknown distribution. The applied context is the exploration for undiscovered resources, like oil accumulations in different deposits, where the most promising deposits are likely to be drilled first, based on some geologic size...

A dynamic asset-allocation model is specified in probabilistic terms as a combination of return distributions resulting from multiple pairs of dynamic models and portfolio strategies based on momentum patterns in US industry returns. The nonlinear state space representation of the model allows...

It is a common understanding that bankruptcy is not a sudden occurrence for any organizations. Macro and micro economic studies have suggested numerous influential factors, which have substantial evidence toward firm's performance (Bekeris, 2012) and survivability (Nehrebecka & Dzik, 2013). With...

In this research note we report on our current efforts on developing a leading indicator of housing prices that could be used to forecast housing prices. Specifically we use Google search index at city level to predict Case-Shiller index. The methodology is based on Granger causality where we...

When searching the Finnish Liiga website for statistics, I discovered an interesting statistic called Corsi%-C. It is defined as “...when the score is within a goal in the first two periods and tied in the third period”. (liiga, 2021) Essentially, this is an enhanced version of Corsi for...

This paper examines point and density forecasts from the European Central Bank's Survey of Professional Forecasters. We derive individual uncertainty measures along with individual point- and density-based measures of disagreement. We also explore the relationship between uncertainty and...

We have studied the relationship between Receiver Operating Characteristics (ROC) and Precision Recall Curve (PRC) both analytically and using a real-life empirical example of yield spread as a predictor of recessions. We show that false alarm rate in ROC and inverted precision in PRC are...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

We propose a new variational approximation of the joint posterior distribution of the log-volatility in the context of large Bayesian VARs. In contrast to existing approaches that are based on local approximations, the new proposal provides a global approximation that takes into account the...