The Conditional Value-at-Risk (CoVaR) proposed by Adrian and Brunnermeier (2016) - which quantifies the impact of a company in distress on the Value-at-Risk (VaR) of the financial system - has established itself as a reference measure of systemic risk. In this study, we extend the CoVaR along...

It is well known that quantile regression model minimizes the portfolio extreme risk, whenever the attention is placed on the estimation of the response variable left quantiles. We show that, by considering the entire conditional distribution of the dependent variable, it is possible to optimize...

We propose the use of state-space models (SSMs) to estimate dynamic spatial relationships from time series data. At each time step, the weight matrix, capturing the latent state, is updated by a spatial autoregressive model. Specifically, we consider two types of SSM: the first one calibrates...