Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/210768
Authors: 
Daníelsson, Jón
Ergun, Lerby M.
de Haan, Laurens
de Vries, Casper G.
Year of Publication: 
2019
Series/Report no.: 
Bank of Canada Staff Working Paper 2019-28
Abstract: 
The selection of upper order statistics in tail estimation is notoriously difficult. Methods that are based on asymptotic arguments, like minimizing the asymptotic MSE, do not perform well in finite samples. Here, we advance a data-driven method that minimizes the maximum distance between the fitted Pareto type tail and the observed quantile. To analyze the finite sample properties of the metric, we perform rigorous simulation studies. In most cases, the finite sample-based methods perform best. To demonstrate the economic relevance of choosing the proper methodology, we use daily equity return data from the CRSP database and find economically relevant variation between the tail index estimates.
Subjects: 
Financial stability
Econometric and statistical methods
JEL: 
C01
C14
C58
Document Type: 
Working Paper

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