EconPapers    
Economics at your fingertips  
 

Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review

Marco Bee and Luca Trapin ()

Risks, 2018, vol. 6, issue 2, 1-16

Abstract: One of the key components of financial risk management is risk measurement. This typically requires modeling, estimating and forecasting tail-related quantities of the asset returns’ conditional distribution. Recent advances in the financial econometrics literature have developed several models based on Extreme Value Theory (EVT) to carry out these tasks. The purpose of this paper is to review these methods.

Keywords: Extreme Value Theory; volatility; risk; quantile (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 M2 M4 K2 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
https://www.mdpi.com/2227-9091/6/2/45/pdf (application/pdf)
https://www.mdpi.com/2227-9091/6/2/45/ (text/html)

Related works:
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:gam:jrisks:v:6:y:2018:i:2:p:45-:d:142858

Access Statistics for this article

Risks is currently edited by Prof. Dr. J. David Cummins

More articles in Risks from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

 
Page updated 2019-08-29
Handle: RePEc:gam:jrisks:v:6:y:2018:i:2:p:45-:d:142858