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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Bank of Canada Staff Working Paper ; No. 2016-22
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Financial Crises
- Thema
-
Econometric and statistical methods
Financial markets
- Ereignis
-
Geistige Schöpfung
- (wer)
-
van Oordt, Maarten R. C.
Chen Zhou
- Ereignis
-
Veröffentlichung
- (wer)
-
Bank of Canada
- (wo)
-
Ottawa
- (wann)
-
2016
- DOI
-
doi:10.34989/swp-2016-22
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- van Oordt, Maarten R. C.
- Chen Zhou
- Bank of Canada
Entstanden
- 2016
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