This report discusses the preliminary results for the analysis of the Baltic Dry Index (BDI) using data mining techniques. The overall aim of the project is to investigate ways to identify trends or stages in the BDI associated with economic cycles, as well as other relationships with economic...

The COVID-19 pandemic itself constitutes an environment for people to experience the potential loss of control and freedom due to social distancing measures and other government orders. Variety-seeking has been treated as a mechanism to regain a sense of self-control. Using Machine Learning...

In this paper we face the fitting versus forecasting paradox with the objective of realizing an optimal Early Warning System to better describe and predict past and future sovereign defaults. We do this by proposing a new Regression Tree-based model that signals a potential crisis whenever...

"'Big data' is now readily available to economic historians, thanks to the digitisation of primary sources, collaborative research linking different data sets, and the publication of databases on the internet. Key economic indicators, such as the consumer price index, can be tracked over long...

Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics...