论文标题
多元实现的Garch模型
A Multivariate Realized GARCH Model
论文作者
论文摘要
我们提出了一类新型的多元GARCH模型，该模型结合了实现的波动性和相关性测量。关键创新是条件相关矩阵的不受约束的矢量参数化，它可以使用因子模型进行相关。这种方法优雅地解决了高维环境中多元Garch模型所面临的主要挑战。作为例证，我们探索了块相关矩阵，这些矩阵自然简化为条件相关性的线性因子模型。该模型应用于九种资产的回报，其样本和样本外部性能与几个流行的基准相比，可以进行比较。
We propose a novel class of multivariate GARCH models that incorporate realized measures of volatility and correlations. The key innovation is an unconstrained vector parametrization of the conditional correlation matrix, which enables the use of factor models for correlations. This approach elegantly addresses the main challenge faced by multivariate GARCH models in high-dimensional settings. As an illustration, we explore block correlation matrices that naturally simplify to linear factor models for the conditional correlations. The model is applied to the returns of nine assets, and its in-sample and out-of-sample performance compares favorably against several popular benchmarks.
