Zobrazit minimální záznam

dc.contributor.authorKonderla, Tomáš
dc.contributor.authorKlepáč, Václav
dc.date.accessioned2022-01-23T01:02:17Z
dc.date.available2022-01-23T01:02:17Z
dc.date.issued2017
dc.identifier43914205
dc.identifier.issn1211-8516 Sherpa/RoMEO, JCR
dc.identifier.urihttps://repozitar.mendelu.cz/xmlui/handle/20.500.12698/1455
dc.description.abstractThe article points out the possibilities of using Hidden Markov model (abbrev. HMM) for estimation of Value at Risk metrics (abbrev. VaR) in sample. For the illustration we use data of the company listed on Prague Stock Exchange in range from January 2011 to June 2016. HMM approach allows us to classify time series into different states based on their development characteristic. Due to a deeper shortage of existing domestic results or comparison studies with advanced volatility governed VaR forecasts we tested HMM with univariate ARMA-GARCH model based VaR estimates. The common testing via Kupiec and Christoffersen procedures offer generalization that HMM model performs better that volatility based VaR estimation technique in terms of accuracy, even with the simpler HMM with normal-mixture distribution against previously used GARCH with many types of non-normal innovations.en
dc.format1687-1694
dc.publisherMendelova univerzita v Brně
dc.relation.ispartofActa Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
dc.relation.urihttps://doi.org/10.11118/actaun201765051687
dc.rightsCC BY-NC-ND 4.0
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectHidden Markov modelen
dc.subjectChristoffersen duration testen
dc.subjectKupiec testen
dc.subjectValue at Risken
dc.subjectARMA-GARCH-GJRen
dc.titleUsing HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Companyen
dc.typeJ_ČLÁNEK
dc.date.updated2022-01-23T01:02:17Z
dc.description.versionOA
local.identifier.doi10.11118/actaun201765051687
local.identifier.scopus2-s2.0-85042848371
local.number5
local.volume65
local.identifier.obd43914205
local.identifier.e-issn2464-8310
local.contributor.affiliationPEF


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Zobrazit minimální záznam

CC BY-NC-ND 4.0
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je CC BY-NC-ND 4.0