Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP,...

This paper introduces the OECD Weekly Tracker of economic activity for 46 OECD and G20 countries using Google Trends search data. The Tracker performs well in pseudo-real time simulations including around the COVID-19 crisis. The underlying model adds to the previous Google Trends literature in...

Using a unique dataset of 22.5 million news articles from the Dow Jones Newswires Archive, we perform an in depth real-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature, namely the FRED-MD dataset. Focusing on U.S. GDP,...

Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...

In this work, we rely on unconventional data sources to nowcast the year-on-year growth rate of Finnish indus-trial production, for different industries. As predictors, we use real-time truck traffic volumes measured automatically in different geographical locations around Finland, as well as...

Regional banks as savings and cooperative banks are widespread in continental Europe. In the aftermath of the financial crisis, however, they had problems keeping their profitability which is an important quantitative indicator for the health of a bank and the banking sector overall. We use a...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...

Improving physicians’ prescription practices is a primary strategy for countering the rise in resistance to antibiotics. This would prevent physicians from incorrectly prescribing antibiotics, one of the main causes of antibiotic resistance. The increasing availability of medical data and...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...