Dynamic Conditional Correlation: On Properties and Estimation
研究了动态条件相关（DCC）模型在大系统中的估计问题，发现传统估计量可能不一致，并提出了一个更易处理的c DCC模型，通过模拟和实际数据比较了两种模型的估计效果。
This article addresses some of the issues that arise with the Dynamic Conditional Correlation (DCC) model. It is proven that the DCC large system estimator can be inconsistent, and that the traditional interpretation of the DCC correlation parameters can result in misleading conclusions. Here, we suggest a more tractable DCC model, called the c DCC model. The c DCC model allows for a large system estimator that is heuristically proven to be consistent. Sufficient stationarity conditions for c DCC processes of interest are established. The empirical performances of the DCC and c DCC large system estimators are compared via simulations and applications to real data.