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008160510s2016    oncd    ob   f000 0 eng d
040 |aCaOODSP|beng
041 |aeng|bfre
043 |an-cn---
0861 |aFB3-5/2016-22E-PDF
1001 |aVan Oordt, Maarten R. C.
24510|aEstimating systematic risk under extremely adverse market conditions |h[electronic resource] / |cby Maarten R.C. van Oordt and Chen Zhou.
260 |a[Ottawa] : |bBank of Canada, |c2016.
300 |aiii, 41 p.
4901 |aStaff Working Paper, |x1701-9397 ; |v2016-22
500 |a"May 2016."
504 |aIncludes bibliographical references (p. 34-37).
5203 |aThis 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.
69207|2gccst|aMarkets
69207|2gccst|aFinancial crisis
69207|2gccst|aStatistical analysis
7001 |aZhou, Chen.
7102 |aBank of Canada.
830#0|aStaff working paper (Bank of Canada)|x1701-9397 ; |v2016-22|w(CaOODSP)9.806221
85640|qPDF|s496 KB|uhttps://publications.gc.ca/collections/collection_2016/banque-bank-canada/FB3-5-2016-22-eng.pdf