标题： 使用Wishart自回归过程的多变量随机波动建模 显示英文标题

标题： Multivariate stochastic volatility modelling using Wishart autoregressive processes

摘要： 一种用于金融时间序列的新多变量随机波动率估计过程被提出。 考虑了波动率精度协方差矩阵的Wishart自回归过程，为此采用了一个两步程序。 第一步是对自回归参数的条件推断，第二步是基于牛顿-拉夫森迭代算法的无条件推断。 所提出的这种方法主要是贝叶斯方法，适用于中等维度的数据，并弥合了闭式估计与基于模拟的估计算法之间的差距。 一个由外汇汇率数据组成的例子说明了所提出的方法。 显示英文摘要

摘要： A new multivariate stochastic volatility estimation procedure for financial time series is proposed. A Wishart autoregressive process is considered for the volatility precision covariance matrix, for the estimation of which a two step procedure is adopted. The first step is the conditional inference on the autoregressive parameters and the second step is the unconditional inference, based on a Newton-Raphson iterative algorithm. The proposed methodology, which is mostly Bayesian, is suitable for medium dimensional data and it bridges the gap between closed-form estimation and simulation-based estimation algorithms. An example, consisting of foreign exchange rates data, illustrates the proposed methodology.