The aim of this paper is to show that measures on tail dependence can be estimated in a convenient way by regression analysis. This yields the same estimates as the non-parametric method within the multivariate Extreme Value Theory framework. The advantage of the regression approach is contained...

Extreme losses are the major concern in risk management. However, the dependence between financial assets and the market portfolio is known to change under extremely adverse market conditions. This is why we develop a measure of systematic tail risk, the tail regression beta, defined by an...

We test for the presence of a systematic tail risk premium in the cross-section of expected returns by applying a measure on the sensitivity of assets to extreme market downturns, the tail beta. Empirically, historical tail betas help to predict the future performance of stocks under extreme...

We consider extreme value analysis in a semi-supervised setting, where we observe, next to the n data on the target variable, n +m data on one or more covariates. This is called the semi-supervised model with n labeled and m unlabeled data. By exploiting the tail dependence between the target...

This paper provides a new estimation method for the marginal expected shortfall (MES) based on multivariate extreme value theory. In contrast to previous studies, the method does not assume specific dependence structure among bank equity returns and is applicable to both large and small systems....