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Bayesian nonparametric sparse VAR models

Citations

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Cited by:

  1. Matteo Iacopini & Luca Rossini, 2019. "Bayesian nonparametric graphical models for time-varying parameters VAR," Papers 1906.02140, arXiv.org.
  2. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
  3. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2023. "Bayesian Modeling of Time-Varying Parameters Using Regression Trees," Working Papers 23-05, Federal Reserve Bank of Cleveland.
  4. Ahelegbey, Daniel Felix & Billio, Monica & Casarin, Roberto, 2024. "Modeling Turning Points in the Global Equity Market," Econometrics and Statistics, Elsevier, vol. 30(C), pages 60-75.
  5. Billio, Monica & Casarin, Roberto & Costola, Michele & Iacopini, Matteo, 2024. "COVID-19 spreading in financial networks: A semiparametric matrix regression model," Econometrics and Statistics, Elsevier, vol. 29(C), pages 113-131.
  6. Daniel Felix Ahelegbey, 2025. "Inference of Impulse Responses via Bayesian Graphical Structural VAR Models," Econometrics, MDPI, vol. 13(2), pages 1-20, April.
  7. Nan Zhang & Daniel J. Graham & Daniel Hörcher & Prateek Bansal, 2021. "A causal inference approach to measure the vulnerability of urban metro systems," Transportation, Springer, vol. 48(6), pages 3269-3300, December.
  8. Minkun Kim & David Lindberg & Martin Crane & Marija Bezbradica, 2023. "Dirichlet Process Log Skew-Normal Mixture with a Missing-at-Random-Covariate in Insurance Claim Analysis," Econometrics, MDPI, vol. 11(4), pages 1-32, October.
  9. Monica Billio & Roberto Casarin & Michele Costola & Lorenzo Frattarolo, 2019. "Opinion Dynamics and Disagreements on Financial Networks," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(4), pages 24-51, December.
  10. Casarin, Roberto & Grassi, Stefano & Ravazzolo, Francesco & van Dijk, Herman K., 2023. "A flexible predictive density combination for large financial data sets in regular and crisis periods," Journal of Econometrics, Elsevier, vol. 237(2).
  11. Baltodano López, Ovielt & Billio, Monica & Casarin, Roberto & Costola, Michele, 2025. "Compounding geopolitical and energy risks: A clustered stochastic multi-COVOL model," Energy Economics, Elsevier, vol. 149(C).
  12. Marco Tronzano, 2023. "Safe-Haven Currencies as Defensive Assets in Global Stocks Portfolios: A Reassessment of the Empirical Evidence (1999–2022)," JRFM, MDPI, vol. 16(5), pages 1-23, May.
  13. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
  14. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  15. Daniel Felix Ahelegbey & Roberto Casarin & Emmanuel Senyo Fianu & Luigi Grossi, 2025. "Structural changes in contagion channels: the impact of COVID-19 on the Italian electricity market," Annals of Operations Research, Springer, vol. 345(2), pages 1035-1060, February.
  16. Camehl, Annika & von Schweinitz, Gregor, 2026. "What explains international interest rate co-movement?," IWH Discussion Papers 3/2023, Halle Institute for Economic Research (IWH), revised 2026.
  17. Florian Huber & Gary Koop & Massimiliano Marcellino & Tobias Scheckel, 2024. "Bayesian modelling of VAR precision matrices using stochastic block networks," Papers 2407.16349, arXiv.org.
  18. Simon Beyeler & Sylvia Kaufmann, 2021. "Reduced‐form factor augmented VAR—Exploiting sparsity to include meaningful factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 989-1012, November.
  19. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore & Wing-Keung Wong, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
  20. Hu, Guanyu, 2021. "Spatially varying sparsity in dynamic regression models," Econometrics and Statistics, Elsevier, vol. 17(C), pages 23-34.
  21. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
  22. Florian Huber & Luca Rossini, 2020. "Inference in Bayesian Additive Vector Autoregressive Tree Models," Papers 2006.16333, arXiv.org, revised Mar 2021.
  23. Bernardi, Mauro & Costola, Michele, 2019. "High-dimensional sparse financial networks through a regularised regression model," SAFE Working Paper Series 244, Leibniz Institute for Financial Research SAFE.
  24. Andrea Bucci & Giulio Palomba & Marco Tedeschi, 2026. "Matrix-valued AutoRegressive (MAR) models in gretl," Computational Statistics, Springer, vol. 41(3), pages 1-31, April.
  25. Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  26. Zhang, Xingmin & Zhang, Shuai, 2021. "Optimal time-varying tail risk network with a rolling window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
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