The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private...

The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private...

In this paper we will propose a model and needed steps that one should undertake in order to try and predict potential stock price fluctuation solely based on financial news from relevant sources. The paper will start with providing background information on the problem and text mining in...

The paper evaluates the quality of the German national accounting data (GDP and its use-side components) as measured by the magnitude and dispersion of the forecast/revision errors. It is demonstrated that government consumption series are the least reliable, whereas real GDP and real private...

In this paper we will propose a model and needed steps that one should undertake in order to try and predict potential stock price fluctuation solely based on financial news from relevant sources. The paper will start with providing background information on the problem and text mining in...

This paper explores the quality of Scope 3 emission data in terms of divergence and composition and the performance of machine learning models in predicting Scope 3 emissions. We do so using the Scope 3 emission datasets of three of the largest data providers (Refinitiv Eikon, and ISS). We find...

The availability of copious amounts of data produced by the increasing datification of our society is nowadays deemed an opportunity to produce timely and convenient statistical information. This paper shows the building of economic sentiment indexes from the texts of the most read economic...

Outliers are observations that deviate significantly from the norm, and their detection has been a critical topic in various research areas and application domains, such as video surveillance, network intrusion detection, and disease outbreak detection. In recent years, deep learning-based...

The availability of copious amounts of data produced by the increasing datification of our society is nowadays deemed an opportunity to produce timely and convenient statistical information. This paper shows the building of economic sentiment indexes from the texts of the most read economic...

Having forecast of real estate sales done correctly is very important for balancing supply and demand in the housing market. However, it is very difficult for housing companies or real estate professionals to determine how many houses they will sell next year. Although this does not mean that a...