We propose a novel approach to quantify spillovers on financial markets based on a structural version of the Diebold-Yilmaz framework. Key to our approach is a SVARGARCH model that is statistically identified by heteroskedasticity, economically identified by maximum shock contribution and that...

We test the usefulness of Machine Learning (ML) for sovereign risk assessment and pricing in the euro area along two important dimensions: i) their predictive accuracy compared to traditional econometrics methods and, ii) their assessment on what are the most important economic factors behind...

Economic theory identifies two potential sources of return predictability: time variation in expected returns (beta-predictability) or market inefficiencies (alpha-predictability). For the latter, Samuelson argued that macro-returns exhibit more inefficiencies than micro-returns, as individual...

After the Covid-shock in March 2020, stock prices declined abruptly, reflecting both the deterioration of investors' expectations of economic activity as well as the surge in aggregate risk aversion. In the following months however, whereas economic activity remained sluggish, equity markets...

Stock prices declined abruptly in the wake of the Covid-19, reflecting both the deterioration of investors’ expectations of economic activity as well as the surge in risk aversion. In the following months, however, economic activity remained sluggish while equity markets bounced back. This...

This paper examines the dynamic nature of pro-environmental preferences through the analysis of sector valuations in global equity markets from 2018 to 2021. We classify companies' business activities into three categories: green (e.g., renewables), neutral, and brown (e.g., fossil energy). We...