It is a challenging task to understand the complex dependency structures in an ultra-high dimensional network, especially when one concentrates on the tail dependency. To tackle this problem, we consider a network quantile autoregression model (NQAR) to characterize the dynamic quantile behavior...

A system of risk factors necessarily involves systemic risk. The analysis of systemic risk is in the focus of recent econometric analysis and uses tail event and network based techniques. Here we bring tail event and network dynamics together into one context. In order to pursue such joint...

The complex tail dependency structure in a dynamic network with a large number of nodes is an important object to study. Here we propose a network quantile autoregression model (NQAR), which characterizes the dynamic quantile behavior. Our NQAR model consists of a system of equations, of which...