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The Dynamic, the Static, and the Weak: Factor Models and the Analysis of High‐Dimensional Time Series

Matteo Barigozzi & Marc Hallin

Journal of Time Series Analysis2025https://doi.org/10.1111/jtsa.12837article
AJG 3ABDC A
Weight
0.48

What the paper says

Several fundamental and closely interconnected issues related to factor models are reviewed and discussed: dynamic versus static loadings, rate‐strong versus rate‐weak factors, the concept of weakly common component recently introduced by Gersing, the irrelevance of cross‐sectional ordering and the assumption of cross‐sectional exchangeability, the impact of undetected strong factors, and the problem of combining common and idiosyncratic forecasts. Conclusions all point to the advantages of the General Dynamic Factor Model approach of Forni, Hallin, Lippi, and Reichlin over the widely used Static Approximate Factor Model introduced by Chamberlain and Rothschild.

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https://doi.org/https://doi.org/10.1111/jtsa.12837

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@article{matteo2025,
  title        = {{The Dynamic, the Static, and the Weak: Factor Models and the Analysis of High‐Dimensional Time Series}},
  author       = {Matteo Barigozzi & Marc Hallin},
  journal      = {Journal of Time Series Analysis},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1111/jtsa.12837},
}

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.63 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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