We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870-2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify...

The paper investigates the life-cycle of the 2008-2009 financial crisis by linking the Macroeconomic Imbalance Procedure (MIP) Scoreboard of the European Commission to the crisis database of the European Systemic Risk Board (ESRB). The novelty of the analysis is that early warning capacity of...

We study the economics and finance scholars' reaction to the 2008 financial crisis using machine learning language analyses methods of Latent Dirichlet Allocation and dynamic topic modelling algorithms, to analyze the texts of 14,270 NBER working papers covering the 1999–2016 period. We find...

We study the economics and finance scholars' reaction to the 2008 financial crisis using machine learning language analyses methods of Latent Dirichlet Allocation and dynamic topic modelling algorithms, to analyze the texts of 14,270 NBER working papers covering the 1999-2016 period. We find...

This paper proposes a general statistical framework for systemic financial stress indexes. Several existing index designs can be represented as special cases. We introduce a daily variant of the ECB's CISS for the euro area and the US. The CISS aggregates a representative set of stress...

We estimate new indices measuring financial and economic (in)stability in Austria and in the euro area. Instead of estimating the level of (in)stability in a financial or economic system we measure the degree of predictability of (in)stability, where our methodological approach is based on the...

This paper proposes a general statistical framework for systemic financial stress indices which measure the severity of financial crises on a continuous scale. Several index designs from the financial stress and systemic risk literature can be represented as special cases. We introduce an...

Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The...

This paper contributes to the old theme of testing for rationality of inflation expectations in surveys, using two very different surveys in parallel. Focusing on the euro area and using two well-known surveys that include questions on inflation expectations, the Consensus Forecast survey and...

We consider 1927 borrowers from 54 countries who had a credit rating by both Moody's and S&P at the end of 1998, and their subsequent default history up to the end of 2002. Viewing bond ratings as predicted probabilities of default, we consider partial orderings among competing probability...