On the correlations in linearized multivariate stochastic volatility models
研究了多元随机波动模型线性化后观测误差相关性的序列，推导出其闭式表达式，并探讨了统计含义，还给出了矩估计示例，有助于理解该模型的估计方法。
In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data, taking the logarithm of the squared returns to obtain a linear state space model. A well-known series representation links the correlations between elements of the observation error in the actual and linearized forms of the model. This note derives a closed-form expression for the series and explores its statistical implications. The results are illustrated by means of a moment-based estimator of the correlations that is obtained in the process.