Estimating Systematic Risk under Extremely Adverse Market Conditions

Maarten R.C. Van Oordt, Chen Zhou*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)
26 Downloads (Pure)


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.

Original languageEnglish
Article numbernbx033
Pages (from-to)432-461
Number of pages30
JournalJournal of Financial Econometrics
Issue number3
Publication statusPublished - 1 Jun 2019

Bibliographical note

Publisher Copyright: © 2018 The Author(s).

Research programs

  • ESE - E&MS


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