Backtesting VaR Estimation under GARCH and GJR-GARCH Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F13%3A86087388" target="_blank" >RIV/61989100:27510/13:86087388 - isvavai.cz</a>

Výsledek na webu

<a href="http://msed.vse.cz/files/2013/191-Kresta-Ales-paper.pdf" target="_blank" >http://msed.vse.cz/files/2013/191-Kresta-Ales-paper.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Backtesting VaR Estimation under GARCH and GJR-GARCH Models

Popis výsledku v původním jazyce

The important and no less interesting part of financial risk management is the risk modelling. Commonly utilized measure of risk (not only by banks and insurance companies) is Value at Risk. Since the financial time series are typical by non-constant volatility over time, it is crucial for Value at Risk calculation to model the standard deviation of returns correctly. In the paper we assume (relatively simple) models based on GARCH and GJR-GARCH models with Student distributions of innovations. These models are back-tested assuming the investment into Prague stock market index. The period utilized for back-testing is from 1993 till 2012, i.e. 4,627 daily values. The evaluation is made by means of the detected number of exceptions, i.e. the cases in which the observed losses were bigger than estimated Value at Risk on a given probability level. Also well-known statistical tests due to Kupiec and Christoffersen are utilized. According to results the assumed models are not accurate ? the

Název v anglickém jazyce

Backtesting VaR Estimation under GARCH and GJR-GARCH Models

Popis výsledku anglicky

The important and no less interesting part of financial risk management is the risk modelling. Commonly utilized measure of risk (not only by banks and insurance companies) is Value at Risk. Since the financial time series are typical by non-constant volatility over time, it is crucial for Value at Risk calculation to model the standard deviation of returns correctly. In the paper we assume (relatively simple) models based on GARCH and GJR-GARCH models with Student distributions of innovations. These models are back-tested assuming the investment into Prague stock market index. The period utilized for back-testing is from 1993 till 2012, i.e. 4,627 daily values. The evaluation is made by means of the detected number of exceptions, i.e. the cases in which the observed losses were bigger than estimated Value at Risk on a given probability level. Also well-known statistical tests due to Kupiec and Christoffersen are utilized. According to results the assumed models are not accurate ? the

Druh

D - Stať ve sborníku

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

The 7th International Days of Statistics and Economics : conference proceedings : September 19-21, 2013, Prague, Czech Republic

ISBN

978-80-86175-87-4

ISSN

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e-ISSN

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Počet stran výsledku

11

Strana od-do

700-710

Název nakladatele

Melandrium

Místo vydání

Slaný

Místo konání akce

Praha

Datum konání akce

19. 9. 2013

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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