This paper applies algorithmic analysis to large amounts of financial market text-based data to assess how narratives and sentiment play a role in driving developments in the financial system. We find that changes in the emotional content in market narratives are highly correlated across data...

This paper applies algorithmic analysis to large amounts of financial market text-based data to assess how narratives and sentiment play a role in driving developments in the financial system. We find that changes in the emotional content in market narratives are highly correlated across data...

We introduce machine learning in the context of central banking and policy analyses. Our aim is to give an overview broad enough to allow the reader to place machine learning within the wider range of statistical modelling and computational analyses, and provide an idea of its scope and...

We forecast CPI inflation in the United Kingdom up to one year ahead using a large set of monthly disaggregated CPI item series combined with a wide set of forecasting tools, including dimensionality reduction techniques, shrinkage methods and non-linear machine learning models. We find that...

We propose a mixed‑frequency regression prediction approach that models a time‑varying trend, stochastic volatility and fat tails in the variable of interest. The coefficients of high‑frequency indicators are regularised via a shrinkage prior that accounts for the grouping structure and...

Motivated by the desire to probe macroeconomic tail events and to capture non-linear economic dynamics, we estimate two types of regime switching models: threshold VAR and Markov switching VAR. For each of the models, we estimate regimes which carry the interpretation of recessionary/normal and...

This paper studies the effects of macroeconomic shocks on business investment in the United Kingdom by filtering a large UK firm-level based dataset of financial accounts into macro-level proxy indicators, and then using these indicators in a Bayesian vector autoregression framework to analyse...

This paper provides robust evidence for the non-linear effects of mortgage spread shocks during recessions and expansions in the United States. Estimating a smooth-transition VAR model, we show that mortgage spread shocks hitting in recessionary regimes create significantly deeper and more...

This paper uses a vector autoregression model estimated with Bayesian methods to identify the effect of productivity news shocks on labour market variables by imposing that they are orthogonal to current technology but they explain future observed technology. In the aftermath of a positive news...

In this paper, we investigate the dynamic relationship between financial market volatility, macroeconomic fundamentals and investor sentiment, employing a two-factor model to decompose volatility into a persistent long-run component and a transitory short-run component. Using a structural VAR...