We examine the transmission of monetary policy via the euro area investment fund sector using a BVAR framework. We find that expansionary shocks are associated with net inflows and that these are strongest for riskier fund types, reflecting search for yield among euro area investors. Search for...

This paper studies the role of international investment funds in the transmission of global financial conditions to the euro area using structural Bayesian vector auto regressions. While cross-border banking sector capital flows receded significantly in the aftermath of the global financial...

The investment fund sector, the largest component of the non-bank financial system, is growing rapidly and the economy is becoming more reliant on investment fund financial intermediation. This paper builds a dynamic stochastic general equilibrium model with banks and investment funds. Banks...

During the March 2020 market turmoil, euro area money-market funds (MMFs) experienced significant outflows, reaching almost 8% of assets under management. This paper investigates whether the volatility in MMF flows was driven by investors' liquidity needs related to derivative margin payments....

Large-Scale Asset Purchases can impact the price of securities directly, when securities are targeted by the central bank, or indirectly through portfolio re-balancing of private investors. We quantify both the direct and the portfolio re-balancing impact, emphasizing the role of investor...

This paper studies the relationship between the business cycle and financial intermediation in the euro area. We establish stylized facts and study their stability during the global financial crisis and the European sovereign debt crisis. Long-term interest rates have been exceptionally high and...

In this study we investigate the determinants of financing obstacles using survey data on a sample of around 5000 firms from the euro area countries. This completely new survey - started at the end of 2009 - gives us the opportunity to test whether firm characteristics such as size, age,...

This paper describes a machine learning technique to timely identify cases of individual bank financial distress. Our work represents the first attempt in the literature to develop an early warning system specifically for small European banks. We employ a machine learning technique, and build a...