Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. This paper proposes embeddings - a language model trained using machine learning techniques - to locate words and documents in a multidimensional vector space. To accomplish this, we...

To which degree can variation in sentiment-based indicators of central bank communication be attributed to changes in macroeconomic, financial, and monetary variables; idiosyncratic speaker effects; sentiment persistence; and random "noise" ? Using the Loughran and McDonald (2011) dictionary on a...

Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. This paper proposes embeddings - a language model trained using machine learning techniques - to locate words and documents in a multidimensional vector space. To accomplish this, we...

To which degree can variation in sentiment-based indicators of central bank communication be attributed to changes in macroeconomic, financial, and monetary variables; idiosyncratic speaker effects; sentiment persistence; and random ‘noise’ ? Using the Loughran and McDonald (2011) dictionary...

We empirically examine how complexity of ECB communications affects financial market trading based on high-frequency data from European stock index futures trading. Our sam-ple covers ECB press conferences between January 2009 and December 2017, during which unconventional monetary policy...