Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/148129
Authors: 
van Oordt, Maarten R. C.
Chen Zhou
Year of Publication: 
2016
Series/Report no.: 
Bank of Canada Staff Working Paper 2016-22
Abstract: 
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.
Subjects: 
Econometric and statistical methods
Financial markets
JEL: 
C14
G01
Document Type: 
Working Paper

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