Applying text analysis to speeches and press releases we construct a Sentiment Index (CBSI) of four central banks to (i) investigate spillovers generated by CBSIs on financial variables with GIRF; (ii) analyze the time-varying and statistically significant spillovers among CBs’ communication...

Nowadays communication is acknowledged as a central bank tool to guide markets expectations. Speeches vary in topics, which are not discriminated ex-ante by text analysis. In this paper we develop a topic-weighted central bank sentiment index as a combination of machine learning and text...

We propose a new data-rich environment model of the yield curve, the macroeconomy, monetary policies and effective exchange rates for a panel of 11 countries: the iDREAM. The endogenous variables are observable (short- and long-term interest rates, exchange rates) and latent factors (economic...

Central banks communication has lately become an important tool to guide expectations and its impact on the economy has been acknowledged by the literature. Nowadays central banks speeches face an increasing variety of topics, which are not discriminated by text analysis. In this paper we...

While previous studies have mainly focused on the existence of a premium in the yield of green bonds, we test whether green bonds traded in the secondary market benefit from a liquidity greenium, i.e. they are more liquid compared to conventional bonds. To this end, we conduct several tests to...

We assess the extent to which loan losses affect banks’ provision of credit to companies and households and examine how feedback from losses to a reduction in credit is affected by the monetary policy stance. Using a unique cross-country dataset of more than 600 banks from 32 countries, we...

We propose a tool to predict risks to economic growth and international business cycles spillovers: the GDP-Network CoVaR. Our methodology to assess Growth-at-Risk is composed by two building blocks. First, we apply the network-based NETS methodology by Barigozzi and Brownlees to identify...