Estimating portfolio risk for tail risk protection strategies
基于极值理论和copula-GARCH等模型，提出一种新的预期损失和风险价值预测组合方法，用于动态尾部风险保护策略，在建模投资组合收益尾部时优于单一模型和简单平均组合。
Abstract We forecast portfolio risk for managing dynamic tail risk protection strategies, based on extreme value theory, expectile regression, copula‐GARCH and dynamic generalized autoregressive score models. Utilizing a loss function that overcomes the lack of elicitability for expected shortfall, we propose a novel expected shortfall (and value‐at‐risk) forecast combination approach, which dominates simple and sophisticated standalone models as well as a simple average combination approach in modeling the tail of the portfolio return distribution. While the associated dynamic risk targeting or portfolio insurance strategies provide effective downside protection, the latter strategies suffer less from inferior risk forecasts, given the defensive portfolio insurance mechanics.