This paper computes data-driven correlation networks based on the stock returns of international banks and conducts a comprehensive analysis of their topological properties. We first apply spatial-dependence methods to filter the effects of strong common factors and a thresholding procedure to...

The network pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unobserved, and maximum entropy serves as the leading method for estimating counterparty exposures. This paper proposes an efficient alternative that combines...

In this paper, we focus on the interconnectedness of banks and the price they pay for liquidity. We assess how the concentration of credit relationships and the position of a bank in the network topology of the system influence the bank’s ability to meet its liquidity demand. We use quarterly...

The pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unknown, and maximum entropy serves as the leading method for estimating unobserved counterparty exposures. This paper proposes an efficient alternative that combines...

We provide empirical evidence on the relevance of systemic risk through the interbank lending channel. We adapt a spatial probit model that allows for correlated error terms in the cross-sectional variation that depend on the measured network connections of the banks. The latter are in our...