Abstract. We show that the use of correlations for modeling dependencies may lead to counterintuitive behavior of risk measures, such as Value-at-Risk (VaR) and Expected Short- fall (ES), when the risk of very rare events is assessed via Monte-Carlo techniques. The phenomenon is demonstrated for...

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...

Accurate estimation and optimal control of tail risk is important for building portfolios with desirable properties, especially when dealing with a large set of assets. In this work, we consider optimal asset allocations strategies based on the minimization of two asymmetric deviation measures,...

Empirical evidence suggests that asset returns correlate more strongly in bear markets than conventional correlation estimates imply. We propose a method for determining complete tail-correlation matrices based on Value-at-Risk (VaR) estimates. We demonstrate how to obtain more effi cient...