Semiparametric GARCH Models with Long Memory Applied to Value at Risk and Expected Shortfall

Journal of Risk

35 Pages Posted: 12 Apr 2021 Last revised: 4 Aug 2022

See all articles by Sebastian Letmathe

Sebastian Letmathe

Paderborn University

Yuanhua Feng

University of Paderborn

André Uhde

University of Paderborn - Faculty of Business Administration and Economics - Department of Taxation, Accounting & Finance

Date Written: April 10, 2021

Abstract

In this paper new semiparametric GARCH models with long memory are introduced.
A multiplicative decomposition of the volatility into a conditional and unconditional
component is assumed. The estimation of the latter is carried out by means of a
data-driven local polynomial smoother. Recurring on the revised recommendations
by the Basel Committee to measure market risk in the banks’ trading books, these
new semiparametric GARCH models are applied to obtain rolling one-step ahead
forecasts for the Value at Risk (VaR) and Expected Shortfall (ES) for market risk
assets. Standard regulatory traffic light tests and a newly introduced traffic light test
for the ES are carried out for all models. In addition to that, model performance is
assessed via a recently introduced model selection criterion. The practical relevance
of our proposal is demonstrated by a comparative study. Our results indicate that
semiparametric long memory GARCH models are a meaningful substitute to their
conventional, parametric counterparts.

Keywords: semiparametric, long memory, GARCH models, forecasting, Value at Risk, Expected Shortfall, traffic light test, Basel Committee on Banking Supervision

JEL Classification: C14, C51, C52, G17, G32

Suggested Citation

Letmathe, Sebastian and Feng, Yuanhua and Uhde, André, Semiparametric GARCH Models with Long Memory Applied to Value at Risk and Expected Shortfall (April 10, 2021). Journal of Risk, Available at SSRN: https://ssrn.com/abstract=3823895 or http://dx.doi.org/10.2139/ssrn.3823895

Sebastian Letmathe (Contact Author)

Paderborn University ( email )

Warburger Str. 100
Paderborn, 33098
Germany

Yuanhua Feng

University of Paderborn ( email )

Warburger Str. 100
Paderborn, D-33098
Germany

André Uhde

University of Paderborn - Faculty of Business Administration and Economics - Department of Taxation, Accounting & Finance ( email )

Warburger Str. 100
D-33098 Paderborn
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
64
Abstract Views
311
rank
467,840
PlumX Metrics