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Factor Model Estimation for High-Dimensional Time Series with Heteroskedastic Noise

Zhao, Da et al.
arXiv (All) · Papers
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methodology
Factor modeling provides a framework for extracting common components from high-dimensional time series. We develop an estimator of the factor loading space that combines contemporaneous covariance with lagged autocovariance information. Under cross-sectionally heteroskedastic white noise, the conte
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