EconPapers    
Economics at your fingertips  
 

Tail Index Estimation: Quantile-Driven Threshold Selection

Jon Danielsson (), Lerby Ergun, Laurens de Haan and Casper de Vries ()

Staff Working Papers from Bank of Canada

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.

Keywords: Econometric and statistical methods; Financial stability (search for similar items in EconPapers)
JEL-codes: C01 C14 C58 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2019-08
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed

Downloads: (external link)
https://www.bankofcanada.ca/wp-content/uploads/2019/08/swp2019-28.pdf Full text (application/pdf)

Related works:
Working Paper: Tail index estimation: quantile driven threshold selection (2016) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:19-28

Access Statistics for this paper

More papers in Staff Working Papers from Bank of Canada 234 Wellington Street, Ottawa, Ontario, K1A 0G9, Canada. Contact information at EDIRC.
Bibliographic data for series maintained by ().

 
Page updated 2023-01-25
Handle: RePEc:bca:bocawp:19-28