We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

A new model for time-varying spatial dependencies is introduced. It forms an extension to the popular spatial lag model and can be estimated conveniently by maximum likelihood. The spatial dependence parameter is assumed to follow a generalized autoregressive score (GAS) process. The theoretical...

We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...

The market-based SRISK measure introduced in Brownlees and Engle (2015) is used to measure the level of systemic risk in Danish banks for the period 2005-15. We find that SRISK was a very good predictor of which banks that needed public capital injections during the financial crisis of 2007-09....

The malfunction of the Value-at-risk (VaR) model is a risk management failure during the 2008 credit crisis. This metric is now criticized for being too little, too late. We propose an improvement - making VaR countercyclical and more robust to fat-tails. The new metric is called, bubble-VaR...

This paper proposes a novel methodology to construct optimal portfolios that incorporates the occurrence of systemic events. Investors maximize a modified Sharpe ratio conditional on a systemic event. We solve the portfolio allocation problem analytically under the absence of short-selling...