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Iman van Lelyveld

14 July 2017
Capturing financial network linkages and contagion in stress test models are important goals for banking supervisors and central banks responsible for micro- and macroprudential policy. However, granular data on financial networks is often lacking, and instead the networks must be reconstructed from partial data. In this paper, we conduct a horse race of network reconstruction methods using network data obtained from 25 different markets spanning 13 jurisdictions. Our contribution is two-fold: first, we collate and analyze data on a wide range of financial networks. And second, we rank the methods in terms of their ability to reconstruct the structures of links and exposures in networks.
JEL Code
G20 : Financial Economics→Financial Institutions and Services→General
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
15 May 2019
This paper revisits the credit spread puzzle for banks from the perspective of information contagion. The puzzle consists of two stylized facts: Structural determinants of credit risk not only have low explanatory power but also fail to capture common factors in the residuals. We reproduce the puzzle for European bank credit spreads and hypothesize that the puzzle exists because structural models ignore contagion effects. We therefore extend the structural approach to include information contagion through bank business model similarities. To capture this channel, we propose an intuitive measure for portfolio overlap and apply it to the complete asset holdings of the largest banks in the Eurozone. Incorporating this unique network information into the structural model increases explanatory power and removes a systemic common factor from the residuals. Furthermore, neglecting the network likely overstates the importance of structural determinants.
JEL Code
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
C38 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Classification Methods, Cluster Analysis, Principal Components, Factor Models