Textual analysis of news articles is increasingly important in predicting stock prices. Previous research has intensively utilized the textual analysis of news and other firm-related documents in volatility prediction models. It has been demonstrated that the news may be related to abnormal...

Machine learning (ML) has revolutionised data analysis over the past decade. Like innumerous other industries heavily reliant on accurate information, banking supervision stands to benefit greatly from this technological advance. The objective of this review is to provide a comprehensive...

Risk analysis and scenario testing are two of the core activities carried out by economists at central banks. With the increasing adoption of machine learning to enhance decision-support systems, and the amount of collected data spiking, institutions provide countless use-cases for the...

Textual analysis of news articles is increasingly important in predicting stock prices. Previous research has intensively utilized the textual analysis of news and other firm-related documents in volatility prediction models. It has been demonstrated that the news may be related to abnormal...

In this article is studied hypothesis, that every period (time interval) before financial crisis is distinguished by co-movement of several variables. The study is based on monthly data (that means no quarterly data, like portfolio investment, were used). This hypothesis, tested with vector...

Our study contains application of Latent Semantic Indexing on financial crises prediction. Hypothesis to test was that equity markets are able to predict even sharp changes in monetary policy during a quarter ahead of such a change (which was searched during two quarters that followed). This...