In this paper, we provide evidence that fat tails and stochastic volatility can be important in improving in-sample fit and out-of-sample forecasting performance. Specifically, we construct a VAR model where the orthogonalised shocks feature Student's t distribution and time-varying variance. We...

Using novel data and machine learning techniques, we develop an early warning system for bank distress. The main input variables come from confidential regulatory returns, and our measure of distress is derived from supervisory assessments of bank riskiness from 2006 through to 2012. We...

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...

Multidimensional Value at Risk (MVaR) generalises VaR in a natural way as the intersection of univariate VaRs. We reduce the dimensionality of MVaRs which allows for adapting the techniques and applications developed for VaR to MVaR. As an illustration, we employ VaR forecasting and evaluation...

We propose a generic workflow for the use of machine learning models to inform decision making and to communicate modelling results with stakeholders. It involves three steps: (1) a comparative model evaluation, (2) a feature importance analysis and (3) statistical inference based on Shapley...

Evidence from a large and growing empirical literature strongly suggests that there have been changes in inflation and output dynamics in the United Kingdom. This is largely based on a class of econometric models that allow for time-variation in coefficients and volatilities of shocks. While...

In this paper we assess the macroeconomic effects of two of the flagship unconventional monetary policies used by the Bank of England during the later stages of the global economic crisis: additional quantitative easing (QE) and the introduction of the Funding for Lending Scheme (FLS). We argue...

With the aim to provide a detailed understanding of global financial cycles and their relevance over time, we analyse co-movement in credit, house prices, equity prices, and interest rates across 17 advanced economies over 130 years. Using a time-varying dynamic factor model, we observe global...