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Statements

Subject Item
n2:RIV%2F61989100%3A27510%2F13%3A86086782%21RIV15-MSM-27510___
rdf:type
n15:Vysledek skos:Concept
dcterms:description
Volatility can be defined and measured as a risk of financial instrument over a specified time period. In this paper, we deal with volatility model selection and comparison in a specific framework. In particular, univariate volatility models like traditional ARCH model and its extensions will be object of our interest. Selection of the best suitable model may be usually based on in-sample or out-of-sample criteria. In empirical studies, we usually favour model that can capture real features of the data analysed and, in addition, can provide the most accurate out-of-sample forecast quality. In this paper, we focus just on out-of-sample comparison of linear and nonlinear ARCH family models which may follow two different approaches. In first approach, alternative models are contrasted by different loss functions based directly on variance forecast and Diebold-Mariano type tests. The second approach includes indirect evaluation methods which conside r using of alternative variance forecasts. In our study, we deal with the evaluation of alternative ARCH family models within a VaR framework. Empirical comparison of the methods discussed above will be demonstrated on illustrative example using sample data from U.S. stock market. We consider daily data of S&P500 index in the period of 2007-2012 years which includes the stage of recent global financial crisis of 2008-2009 years. Volatility can be defined and measured as a risk of financial instrument over a specified time period. In this paper, we deal with volatility model selection and comparison in a specific framework. In particular, univariate volatility models like traditional ARCH model and its extensions will be object of our interest. Selection of the best suitable model may be usually based on in-sample or out-of-sample criteria. In empirical studies, we usually favour model that can capture real features of the data analysed and, in addition, can provide the most accurate out-of-sample forecast quality. In this paper, we focus just on out-of-sample comparison of linear and nonlinear ARCH family models which may follow two different approaches. In first approach, alternative models are contrasted by different loss functions based directly on variance forecast and Diebold-Mariano type tests. The second approach includes indirect evaluation methods which conside r using of alternative variance forecasts. In our study, we deal with the evaluation of alternative ARCH family models within a VaR framework. Empirical comparison of the methods discussed above will be demonstrated on illustrative example using sample data from U.S. stock market. We consider daily data of S&P500 index in the period of 2007-2012 years which includes the stage of recent global financial crisis of 2008-2009 years.
dcterms:title
On Conditional Volatility Model Comparison On Conditional Volatility Model Comparison
skos:prefLabel
On Conditional Volatility Model Comparison On Conditional Volatility Model Comparison
skos:notation
RIV/61989100:27510/13:86086782!RIV15-MSM-27510___
n4:aktivita
n17:P
n4:aktivity
P(EE2.3.20.0296), P(GA13-13142S)
n4:dodaniDat
n9:2015
n4:domaciTvurceVysledku
n18:4149971
n4:druhVysledku
n13:D
n4:duvernostUdaju
n21:S
n4:entitaPredkladatele
n14:predkladatel
n4:idSjednocenehoVysledku
93671
n4:idVysledku
RIV/61989100:27510/13:86086782
n4:jazykVysledku
n11:eng
n4:klicovaSlova
conditional volatility, Diebold-Mariano test, MCS approach, out-of-sample forecast, VaR
n4:klicoveSlovo
n5:VaR n5:Diebold-Mariano%20test n5:conditional%20volatility n5:MCS%20approach n5:out-of-sample%20forecast
n4:kontrolniKodProRIV
[6662967331C6]
n4:mistoKonaniAkce
Praha
n4:mistoVydani
Slaný
n4:nazevZdroje
The 7th International Days of Statistics and Economics : conference proceedings : September 19-21, 2013, Prague, Czech Republic
n4:obor
n8:AH
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
1
n4:projekt
n16:EE2.3.20.0296 n16:GA13-13142S
n4:rokUplatneniVysledku
n9:2013
n4:tvurceVysledku
Seďa, Petr
n4:typAkce
n12:EUR
n4:wos
000339103100124
n4:zahajeniAkce
2013-09-19+02:00
s:numberOfPages
10
n20:hasPublisher
Melandrium
n3:isbn
978-80-86175-87-4
n7:organizacniJednotka
27510