Arbeitspapier
Estimating systematic risk under extremely adverse market conditions
This paper considers the problem of estimating a linear model between two heavy-tailed variables if the explanatory variable has an extremely low (or high) value. We propose an estimator for the model coefficient by exploiting the tail dependence between the two variables and prove its asymptotic properties. Simulations show that our estimation method yields a lower mean squared error than regressions conditional on tail observations. In an empirical application we illustrate the better performance of our approach relative to the conditional regression approach in projecting the losses of industry-specific stock portfolios in the event of a market crash.
- Language
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Englisch
- Bibliographic citation
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Series: Bank of Canada Staff Working Paper ; No. 2016-22
- Classification
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Wirtschaft
Semiparametric and Nonparametric Methods: General
Financial Crises
- Subject
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Econometric and statistical methods
Financial markets
- Event
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Geistige Schöpfung
- (who)
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van Oordt, Maarten R. C.
Chen Zhou
- Event
-
Veröffentlichung
- (who)
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Bank of Canada
- (where)
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Ottawa
- (when)
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2016
- DOI
-
doi:10.34989/swp-2016-22
- Handle
- Last update
-
10.03.2025, 11:41 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
- Arbeitspapier
Associated
- van Oordt, Maarten R. C.
- Chen Zhou
- Bank of Canada
Time of origin
- 2016
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