Title: On the architecture of financial networks
Authors: Ruben Hipp - University of Mannheim (Germany) [presenting]
Abstract: By using forecast error variance decompositions to identify networks, a popular connectedness measurement has been introduced and a new standard in estimating systemic risk has been successfully established. In contrast, we develop a model to estimate a network within a financial setting without a forecast horizon. By applying a structural vector autoregressive model, it is possible to identify immediate reactions within the system and therefore connections between financial firms. In addition, an application on the U.S. financial market quantifies systemic risk and identifies the most risk receiving and distributing financial firms in a dynamic fashion. Various simulations and applications indicate that a network containing structural VAR allows for a more sophisticated identification of connections and can give insights of how the architecture of financial networks looks like.