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波动率鞅差散度矩阵及其在多元波动率降维中的应用AI 解读

In this article, we propose the so-called volatility martingale difference divergence matrix (VMDDM) to quantify the conditional variance dependence of a random vector Y∈Rp$Y\in \mathbb {R}^p$ given X∈Rq$X\in \mathbb {R}^q$, building on the recent work on martigale difference divergence matrix (MDDM) that measures the conditional mean dependence. We further generalize VMDDM to the time series context and apply it to do dimension reduction for multivariate volatility,…

鞅差散度矩阵及其在平稳多元时间序列降维中的应用AI 解读

In this article, we introduce a new methodology to perform dimension reduction for a stationary multivariate time series. Our method is motivated by the consideration of optimal prediction and focuses on the reduction of the effective dimension in conditional mean of time series given the past information. In particular, we seek a contemporaneous linear transformation such that the transformed time series has two parts with one part being conditionally mean independent of…