arXiv 7 Jul 2021 · Econometrics · publishedJournal of Econometrics (2023) · 3 citations (OpenAlex)
arXiv:2107.03366 · PDF · DOI · OpenAlex · Extracted main text
A factor copula model is proposed in which factors are either simulable or estimable from exogenous information. Point estimation and inference are based on a simulated methods of moments (SMM) approach with non-overlapping simulation draws. Consistency and limiting normality of the estimator is established and the validity of bootstrap standard errors is shown. Doing so, previous results from the literature are verified under low-level conditions imposed on the individual components of the factor structure. Monte Carlo evidence confirms the accuracy of the asymptotic theory in finite samples and an empirical application illustrates the usefulness of the model to explain the cross-sectional dependence between stock returns.
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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 | Oh, D. H., and A. J. Patton (2013) Simulated method of moments estimation for copula-based multivariate models | 1.000 | 17 | 6 | 100% |
| 2 | Oh, D. H., and A. J. Patton (2017) Modeling dependence in high dimensions with factor copulas | 1.000 | 7 | 3 | 100% |
| 3 | Newey, W. K., and D. McFadden (1994) Large sample estimation and hypothesis testing | 0.874 | 5 | 2 | 100% |
| 4 | Opschoor, A., Lucas, A, Barra, I., and D. van Dijk (2020) Closed-form multi-factor copula models with observation-driven dynamic factor loadings | 0.874 | 5 | 2 | 100% |
| 5 | Andrews, D. W. K., and D. Pollard (1994) An introduction to functional central limit theorems for dependent stochastic processes | 0.843 | 5 | 3 | 60% |
| 6 | Neumeyer, N., M. Omelka, and $S$. Hudecová (2019) A copula approach for dependence modeling in multivariate nonparametric time series | 0.843 | 5 | 3 | 60% |
| 7 | Oh, D. H., and A. J. Patton (2018) Time-varying systemic risk: evidence from a dynamic copula model of CDS spreads | 0.811 | 4 | 2 | 100% |
| 8 | Fermanian, J.-D., D. Radulović, and M. H. Wegkamp (2004) Weak convergence of empirical copula processes | 0.737 | 5 | 2 | 60% |
| 9 | Berghaus, B., A. Bücher, and S. Volgushev (2017) Weak convergence of the empirical copula process with respect to weighted metrics | 0.737 | 4 | 3 | 50% |
| 10 | Bücher, A., and S. Volgushev (2013) Empirical and sequential empirical copula processes under serial dependence | 0.737 | 4 | 3 | 50% |
Showing the top 10 of 106 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Local Gaussian copula inference with structural breaks: testing dependence predictability | 0.843 | 4 | 4 |
| 2 | 2cmLeast squares estimation in nonstationary nonlinear cohort panels with learning from experience | 0.405 | 1 | 1 |