On causal networks of financial firms : structural identification via non-parametric heteroskedasticity / by Ruben Hipp.
Material type:
TextSeries: Staff Working Paper (Bank of Canada) ; 2020-42Publisher: [Ottawa] : Bank of Canada = Banque du Canada, 2020Copyright date: ©2020Description: 1 online resource (ii, 40 pages)Content type: - text
- computer
- online resource
- Financial institutions -- Econometric models
- Causation -- Econometric models
- Heteroscedasticity
- Financial institutions
- Econometrics
- Analysis of variance
- Institutions financières -- Modèles économétriques
- Causalité -- Modèles économétriques
- Hétéroscédasticité
- Autoregressive conditional heteroskedasticity
- Causality
- Covariance matrix
- Derivative
- Diagonal matrix
- Financial crisis of 2007-08
- Heteroscedasticity
- Jpmorgan chase
- Likelihood function
- Matrix (mathematics)
- 332.1 15
- cci1icc
Distributed by the Government of Canada Publishing and Depository Services Program (Weekly acquisitions list 2020-44).
"Last updated: October 15, 2020."
Includes bibliographical references.
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"We investigate the causal structure of financial systems by accounting for contemporaneous relationships. To identify structural parameters, we introduce a novel non-parametric approach that exploits the fact that most financial data empirically exhibit heteroskedasticity. The identification works locally and, thus, allows structural matrices to vary smoothly with time. With this causality in hand, we derive a new measure for systemic relevance. An application on volatility spillovers in the US financial market demonstrates the importance of structural parameters in spillover analyses. Finally, we highlight that the COVID-19 period is mostly an aggregate crisis, with financial firms' spillovers edging slightly higher"--Abstract, page ii.
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