Using recent advances in network theory, we estimate the intra-industry connectedness for US publicly traded companies going back to the 1920s. We develop a stock-level composite centrality measure that captures multiple dimensions of a stock's interdependence with its industry peers. Using our...

We study the 'interconnectedness' of stress-tested banks by exploiting how they are mentioned together in the context of financial news. We start by constructing weekly co-occurrence network matrices following Ronnqvist and Sarlin (2015) text-to-network approach. Using the COVID-19 pandemic as...

This paper explores the link between systemic risk and firm value gain in the context of bank acquisitions. We find that bank acquisitions on average lead to an increase in acquires' systemic risk (a public cost), which is in turn associated with an increase in firm value (a private benefit) for...

In this paper, I interpret a time series spatial model (T-SAR) as a constrained Structural Vector Autoregressive (SVAR) model. Based on these restrictions, I propose a Minimum Distance approach to estimate the (row-standardized) network matrix and the overall network influence parameter of the...

In this paper, I interpret a time series spatial model (T-SAR) as a constrained Structural Vector Autoregressive (SVAR) model. Based on these restrictions, I propose a Minimum Distance approach to estimate the (row-standardized) network matrix and the overall network influence parameter of the...