Estimating systematic risk under extremely adverse market conditions / by Maarten R.C. van Oordt and Chen Zhou.: FB3-5/2016-22E-PDF

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.

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Publication information
Department/Agency Bank of Canada.
Title Estimating systematic risk under extremely adverse market conditions / by Maarten R.C. van Oordt and Chen Zhou.
Series title Staff Working Paper, 1701-9397 ; 2016-22
Publication type Series - View Master Record
Language [English]
Format Electronic
Electronic document
Note(s) "May 2016."
Includes bibliographical references (p. 34-37).
Publishing information [Ottawa] : Bank of Canada, 2016.
Author / Contributor Van Oordt, Maarten R. C.
Zhou, Chen.
Description iii, 41 p.
Catalogue number
  • FB3-5/2016-22E-PDF
Subject terms Markets
Financial crisis
Statistical analysis
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