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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| 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 |
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| Subject terms | Markets Financial crisis Statistical analysis |
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