论文标题
股票市场回报的大型确认动态因素模型在不同时区
A Large Confirmatory Dynamic Factor Model for Stock Market Returns in Different Time Zones
论文作者
论文摘要
我们为大量股票提出了一个验证性动态因子模型，这些股票每天都在多个时区观察到回报。该模型具有全球因素和大陆因素，都可以推动单个股票回报系列。我们提出了两个模型的估计量：准最大似然估计器（QML just just识别），以及基于预期最大化（EM）算法（QML-ALL-RES）的改进估计量。在较大的近似因子模型设置下，我们的估计器是一致且渐近正常的。特别是，QML全元素的渐近分布与不可行的OLS估计器的渐近分布相同，这些估计值将因素处理为已知的因素，并利用了对模型参数的所有限制。我们将该模型应用于42个发达和新兴市场的MSCI权益指数，并发现当CBOE波动性指数（VIX）较高时，大多数市场都更加集成。
We propose a confirmatory dynamic factor model for a large number of stocks whose returns are observed daily across multiple time zones. The model has a global factor and a continental factor that both drive the individual stock return series. We propose two estimators of the model: a quasi-maximum likelihood estimator (QML-just-identified), and an improved estimator based on an Expectation Maximization (EM) algorithm (QML-all-res). Our estimators are consistent and asymptotically normal under the large approximate factor model setting. In particular, the asymptotic distributions of QML-all-res are the same as those of the infeasible OLS estimators that treat factors as known and utilize all the restrictions on the parameters of the model. We apply the model to MSCI equity indices of 42 developed and emerging markets, and find that most markets are more integrated when the CBOE Volatility Index (VIX) is high.
