This paper investigates whether and how the COVID-19 pandemic affects bank funding costs in China. We find a significantly positive relationship between the offering yields of negotiable certificates of deposit and banks’ pandemic exposure. The surge in bank funding costs is alleviated by...

We characterize how risk evolves during a crisis. Using high-frequency data, we find that the first two principal components (PCs) of the covariance matrix of global asset returns experience large, sudden, and temporary spikes coinciding with well-known crises - Covid-19 pandemic, Global...

We combine a customized survey and randomized controlled trial (RCT) to study the effect of higher-order beliefs on U.S. retail investors' portfolio allocations. We find that investors' higher-order beliefs about stock market returns are correlated with but distinct from their first-order...

We document shifts in investor composition during quantitative tightening, which suggest that investors adjust their portfolios at different speeds. To understand its implications for bond valuation, we develop a general equilibrium model which highlights the dynamic interaction between...

This paper uses regulatory data to assess the value of retail order flow in the German equity market. To this end, we examine the performance of specialized retail market makers (RMMs) that internalize a large share of retail activity via affiliated trading venues. We show that retail market...

This paper proposes a forward-looking metric of transition risk that relates financial performance and incremental carbon costs at the firm level. To this end, we use a consistent dividend discount framework augmented with emission costs of firms and climate scenario projections from four...

We show that the stock market price reaction to monetary policy surprises upon announcements of the Federal Open Market Committee (FOMC) is explained mostly by changes in the default-free term structure of yields, not by changes in the equity premium. We reach this conclusion based on a new...

While Machine Learning (ML) excels at predictive tasks, its inferential capacity is limited due to its complex non-parametric structure. This paper aims to elucidate the analytical behavior of ML through Interpretable Machine Learning (IML) in a real estate context. Using a hedonic ML approach...

Using a new database of consumers expectations, this paper examines the nature of house price forecasts across a select sample of European Union (EU) member states for the period 2020 to 2024. Across many EU countries, post Covid-19, house price increases have been apparent. Therefore,...

We present two models for long-term inflation expectations and inflation risk premiums for Canada. First, we estimate inflation expectations using a vector autoregressive model based on the relationship of inflation with both the unemployment gap and the term structure of the Government of...