This paper contains comments on Nonparametric Tail Risk, Stock Returns and the Macroeconomy …

returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of … generalized hyperbolic innovations. The novelty of the model is that parameter estimation is conducted by joint maximum likelihood …. An extensive empirical study confirms the COMFORT model’s superiority in terms of multivariate density and Value-at-Risk …

the financial risk management literature. Importantly, the proposed framework is intended to be applied to non … is relevant in applications concerning with extreme events. We show that the associated tail risk network can be used for … measuring systemic risk contributions. We also apply the framework to study international financial contagion and the impact of …

which data are discarded, leading to estimation inefficiencies. To solve these issues, we extend the tail regression model … issues at the estimation stage. We illustrate the superiority of our approach for inference over classical peaks … stability index, and credit spreads. Moreover, sorting funds along exposure to our tail risk measure discriminates between high …

the period 1972:1-2014:12 to forecasts our tail risk indicators with each model in pseudo-real time. Our key finding is …