arXiv 15 Jul 2024 · Econometrics · publishedJournal of Time Series Analysis (2025) · 5 citations (OpenAlex)
arXiv:2407.10653 · PDF · DOI · OpenAlex · Extracted main text
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 et al. (2023), 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 et al. (2000) over the widely used Static Approximate Factor Model introduced by Chamberlain and Rothschild (1983).
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chamberlain, G. and M. Rothschild (1983) Arbitrage, factor structure, and mean-variance analysis on large asset markets | 1.000 | 13 | 8 | 100% |
| 2 | Forni, M., M. Hallin, M. Lippi, and L. Reichlin (2000) The generalized dynamic-factor model: Identification and estimation | 1.000 | 10 | 4 | 100% |
| 3 | Chamberlain, G (1983) Funds, factors and diversification in arbitrage pricing models | 1.000 | 8 | 6 | 100% |
| 4 | Stock, J. H. and M. W. Watson (2002) Forecasting using principal components from a large number of predictors | 1.000 | 6 | 5 | 100% |
| 5 | Onatski, A (2012) Asymptotics of the principal components estimator of large factor models with weakly influential factors | 1.000 | 6 | 4 | 100% |
| 6 | Gersing, P., C. Rust, and M. Deistler (2023) Weak factors are everywhere | 1.000 | 6 | 3 | 100% |
| 7 | Bai, J (2003) Inferential theory for factor models of large dimensions | 1.000 | 5 | 5 | 100% |
| 8 | Bai, J. and S. Ng (2002) Determining the number of factors in approximate factor models | 1.000 | 5 | 4 | 100% |
| 9 | Hallin, M. and R. Liska (2007) The generalized dynamic factor model:\ determining the number of factors self | 0.874 | 8 | 2 | 100% |
| 10 | Forni, M. and M. Lippi (2001) The generalized dynamic factor model: representation theory | 0.874 | 7 | 2 | 100% |
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