Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company
The 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 clas...
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Online Access: | https://acta.mendelu.cz/65/5/1687/ |
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doaj-10515962f5ae4a66a61a7a593c8237422020-11-25T01:43:57ZengMendel University PressActa Universitatis Agriculturae et Silviculturae Mendelianae Brunensis1211-85162464-83102017-01-016551687169410.11118/actaun201765051687Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed CompanyTomáš Konderla0Václav Klepáč1Department of Statistics and Operation analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech RepublicDepartment of Statistics and Operation analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech RepublicThe 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.https://acta.mendelu.cz/65/5/1687/Hidden Markov modelChristoffersen duration testKupiec testValue at RiskARMA-GARCH-GJR |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tomáš Konderla Václav Klepáč |
spellingShingle |
Tomáš Konderla Václav Klepáč Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis Hidden Markov model Christoffersen duration test Kupiec test Value at Risk ARMA-GARCH-GJR |
author_facet |
Tomáš Konderla Václav Klepáč |
author_sort |
Tomáš Konderla |
title |
Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company |
title_short |
Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company |
title_full |
Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company |
title_fullStr |
Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company |
title_full_unstemmed |
Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company |
title_sort |
using hmm approach for assessing quality of value at risk estimation: evidence from pse listed company |
publisher |
Mendel University Press |
series |
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis |
issn |
1211-8516 2464-8310 |
publishDate |
2017-01-01 |
description |
The 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. |
topic |
Hidden Markov model Christoffersen duration test Kupiec test Value at Risk ARMA-GARCH-GJR |
url |
https://acta.mendelu.cz/65/5/1687/ |
work_keys_str_mv |
AT tomaskonderla usinghmmapproachforassessingqualityofvalueatriskestimationevidencefrompselistedcompany AT vaclavklepac usinghmmapproachforassessingqualityofvalueatriskestimationevidencefrompselistedcompany |
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