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Hierarchical Graphical Models, With Application to Systemic Risk

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  • Daniel Felix Ahelegbey

    (Department of Economics, University Of Venice C� Foscari)

  • Paolo Giudici

    (Department of Economics, University Of Pavia)

Abstract

The latest financial crisis has stressed the need of understanding the world financial system as a network of interconnected institutions, where financial linkages play a fundamental role in the spread of systemic risks. In this paper we propose to enrich the topological perspective of network models with a more structured statistical framework, that of Bayesian graphical Gaussian models. From a statistical viewpoint, we propose a new class of hierarchical Bayesian graphical models, that can split correlations between institutions into country specific and idiosyncratic ones, in a way that parallels the decomposition of returns in the well-known Capital Asset Pricing Model. From a financial economics viewpoint, we suggest a way to model systemic risk that can explicitly take into account frictions between different financial markets, particularly suited to study the on-going banking union process in Europe. From a computational viewpoint, we develop a novel Markov Chain Monte Carlo algorithmbased on Bayes factor thresholding.

Suggested Citation

  • Daniel Felix Ahelegbey & Paolo Giudici, 2014. "Hierarchical Graphical Models, With Application to Systemic Risk," Working Papers 2014:01, Department of Economics, University of Venice "Ca' Foscari".
  • Handle: RePEc:ven:wpaper:2014:01
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    Cited by:

    1. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
    2. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    3. 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.
    4. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    5. Monica Billio & Roberto Casarin & Matteo Iacopini, 2024. "Bayesian Markov-Switching Tensor Regression for Time-Varying Networks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(545), pages 109-121, January.
    6. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.
    7. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    8. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
    9. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    10. Fianu, Emmanuel Senyo & Ahelegbey, Daniel Felix & Grossi, Luigi, 2022. "Modeling risk contagion in the Italian zonal electricity market," European Journal of Operational Research, Elsevier, vol. 298(2), pages 656-679.
    11. Joshua C. C. Chan, 2019. "Large Bayesian vector autoregressions," CAMA Working Papers 2019-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    12. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    13. Casarin, Roberto & Costola, Michele & Yenerdag, Erdem, 2018. "Financial bridges and network communities," SAFE Working Paper Series 208, Leibniz Institute for Financial Research SAFE, revised 2018.
    14. Nikolay Arefiev, 2016. "Identification of Monetary Policy Shocks within a Svar Using Restrictions Consistent with a DSGE Model," HSE Working papers WP BRP 125/EC/2016, National Research University Higher School of Economics.
    15. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.
    16. 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.
    17. Buse, Rebekka & Schienle, Melanie & Urban, Jörg, 2019. "Effectiveness of policy and regulation in European sovereign credit risk markets: A network analysis," Working Paper Series in Economics 125, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    18. Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Market Risk, Connectedness and Turbulence: A Comparison of 21st Century Financial Crises," DEM Working Papers Series 188, University of Pavia, Department of Economics and Management.
    19. Nikolay Arefiev, 2016. "Graphical Interpretations of Rank Conditions For Identification of Linear Gaussian Models," HSE Working papers WP BRP 124/EC/2016, National Research University Higher School of Economics.
    20. Urbi Garay & Enrique Ter Horst & German Molina & Abel Rodriguez, 2016. "Bayesian Nonparametric Measurement of Factor Betas and Clustering with Application to Hedge Fund Returns," Econometrics, MDPI, vol. 4(1), pages 1-23, March.
    21. Roberto Casarin & Domenico Sartore & Marco Tronzano, 2018. "A Bayesian Markov-Switching Correlation Model for Contagion Analysis on Exchange Rate Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 101-114, January.
    22. Carota, Cinzia & Durio, Alessandra & Guerzoni, Marco, 2014. "An Application of Graphical Models to the Innobarometer Survey: A Map of Firms’ Innovative Behaviour," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201444, University of Turin.
    23. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    24. Daniel Felix Ahelegbey, 2015. "The Econometrics of Networks: A Review," Working Papers 2015:13, Department of Economics, University of Venice "Ca' Foscari".
    25. Daniel Felix Ahelegbey & Luis Carvalho & Eric D. Kolaczyk, 2020. "A Bayesian Covariance Graph And Latent Position Model For Multivariate Financial Time Series," DEM Working Papers Series 181, University of Pavia, Department of Economics and Management.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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