Artikel
COVID-19 pandemic and financial contagion
The original contribution of this paper is to empirically document the contagion of the Covid-19 on financial markets. We merge databases from Johns Hopkins Coronavirus Center, Oxford-Man Institute Realized Library, NYU Volatility Lab, and St-Louis Federal Reserve Board. We deploy three types of models throughout our experiments: (i) the Susceptible-Infective-Removed (SIR) that predicts the infections' peak on 2020-03-27; (ii) volatility (GARCH), correlation (DCC), and risk-management (Value-at-Risk (VaR)) models that relate how bears painted Wall Street red; and, (iii) data-science trees algorithms with forward prunning, mosaic plots, and Pythagorean forests that crunch the data on confirmed, deaths, and recovered Covid-19 cases and then tie them to high-frequency data for 31 stock markets.
- Language
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Englisch
- Bibliographic citation
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Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 12 ; Pages: 1-25 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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COVID-19
financial contagion
Johns Hopkins repository
Susceptible-Infective-Removed model
tree algorithm
data science
- Event
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Geistige Schöpfung
- (who)
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Chevallier, Julien
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
-
Basel
- (when)
-
2020
- DOI
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doi:10.3390/jrfm13120309
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Chevallier, Julien
- MDPI
Time of origin
- 2020
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