In this paper we explore the use of Genetic Algorithms (GA) to calibrate seasonal BVAR models. In this way, the mechanistic use of seasonal adjustment procedures is avoided, since seasonality becomes a structural, basic and explicit part of the BVAR model. At the same time, the use of GA allows...

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...

Sentiment analysis is crucial in understanding and analyzing public opinions, feedback, and social media data. In this study, we propose a modified Bayesian Boosting algorithm with weight-guided optimal feature selection for sentiment analysis. The goal is to improve the accuracy and efficiency...