Jonas Krampe, Luca Margaritella
arXiv 4 Feb 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2402.02482 · PDF · DOI · OpenAlex · Extracted main text
We propose a novel approach to estimate high-dimensional global bank network connectedness in both the time and frequency domains. By employing a factor model with sparse VAR idiosyncratic components, we decompose system-wide connectedness (SWC) into two key drivers: (i) common component shocks and (ii) idiosyncratic shocks. We also provide bootstrap confidence bands for all SWC measures. Furthermore, spectral density estimation allows us to disentangle SWC into short-, medium-, and long-term frequency responses to these shocks. We apply our methodology to two datasets of daily stock price volatilities for over 90 global banks, spanning the periods 2003-2013 and 2014-2023. Our empirical analysis reveals that SWC spikes during global crises, primarily driven by common component shocks and their short term effects. Conversely, in normal times, SWC is largely influenced by idiosyncratic shocks and medium-term dynamics.
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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 | Krampe, J. & Margaritella, L (2025) Factor models with sparse var idiosyncratic components self | 1.000 | 21 | 6 | 100% |
| 2 | Demirer, M., Diebold, F. X., Liu, L., & Yilmaz, K (2018) Estimating global bank network connectedness | 1.000 | 19 | 3 | 100% |
| 3 | Wu, W. B. & Zaffaroni, P (2018) Asymptotic theory for spectral density estimates of general multivariate time series | 1.000 | 5 | 3 | 100% |
| 4 | Diebold, F. X. & Ylmaz, K (2014) On the network topology of variance decompositions: Measuring the connectedness of financial firms | 0.874 | 7 | 2 | 100% |
| 5 | Cai, T., Liu, W., & Luo, X (2011) A constrained l1 minimization approach to sparse precision matrix estimation | 0.843 | 3 | 3 | 100% |
| 6 | Krampe, J., Paparoditis, E., & Trenkler, C (2023) Structural inference in sparse high-dimensional vector autoregressions self | 0.843 | 3 | 3 | 100% |
| 7 | Barigozzi, M., Hallin, M., Soccorsi, S., & von Sachs, R (2021) Time-varying general dynamic factor models and the measurement of financial connectedness | 0.811 | 4 | 2 | 100% |
| 8 | Acemoglu, D., Ozdaglar, A., & Tahbaz-Salehi, A (2015) Systemic risk and stability in financial networks | 0.737 | 3 | 2 | 100% |
| 9 | Koop, G., Pesaran, M. H., & Potter, S. M (1996) Impulse response analysis in nonlinear multivariate models | 0.737 | 3 | 2 | 100% |
| 10 | Krampe, J. & Paparoditis, E (2021) Sparsity concepts and estimation procedures for high-dimensional vector autoregressive models self | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 40 scored citations.