基于偏t分布realized GARCH模型的尾部风险估计

借助偏t分布realized GARCH模型,提出同时考虑高频和低频信息的尾部风险估计方法,分别纳入RV、RRV和BPV构成尾部风险估计的对比模型,并利用上证综指高频数据进行实证分析.实证结果表明:相比EGARCH模型,realized GARCH模型能够提供更准确的VaR和ES估计;纳入对微观结构噪声和跳跃稳健的已实现测度有助于提高VaR和ES估计的准确性;realized GARCH模型在尾部风险估计中的表现对次贷危机前和次贷危机后两个不同的样本期间稳健.

Estimation of tail risk based on realized GARCH model with skew-t distribution

Based on realized GARCH model with skew t distribution, we proposed a tail risk estimation method which incorporates both high frequency and low frequency information. Realized GARCH models with RV, RRV and BPV constitute the competing models. The empirical analysis using high-frequency data of Shanghai composite index shows that the realized GARCH model estimates VaR and ES more accurately than the EGARCH model, and that incorporating realized measures robust to microstructure noise and jump contributes to improve the estimation accuracy of VaR and ES. Moreover, the performance of the realized GARCH model is robust during the pre-and post-crisis period.