Publication:
Estimation Of The Value-at-risk (VAR) Using The Tarch Model By Considering The Effects Of Long Memory In Stock Investments

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cris.lastimport.scopus2025-11-14T15:37:35Z
dc.contributor.authorNurfadhlina Abdul Halimen_US
dc.contributor.authorAgus Supriatnaen_US
dc.contributor.authorAdhy Prasetyoen_US
dc.date.accessioned2024-05-28T04:28:13Z
dc.date.available2024-05-28T04:28:13Z
dc.date.issued2020
dc.date.submitted16/2/2021
dc.descriptionNon-Indexed Publication
dc.description.abstractValue at Risk (VaR) is one of the standard methods that can be used in measuring risk in stock investments. VaR is defined as the maximum possible loss for a particular position or portfolio in the known confidence level of a specific time horizon. The main topic discussed in this thesis is to estimate VaR using the TARCH (Threshold Autoregressive Conditional Heteroscedasticity) model in a time series by considering the effect of long memory. The TARCH model is applied to the daily log return data of a company's stock in Indonesia to estimate the amount of quantile that will be used in calculating VaR.Based on the analysis, it was found that with a significance level of 95% and assuming an investment of 200,000,000 IDR, the VaR using the TARCH model approach was 5,110,200 IDR per day.en_US
dc.identifier.doihttps://doi.org/10.47194/orics.v1i1.22
dc.identifier.epage42
dc.identifier.issn2722-0974
dc.identifier.issue1
dc.identifier.spage33
dc.identifier.urihttp://iorajournal.org/index.php/Orics/article/view/22
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/5705
dc.identifier.volume1
dc.language.isoen_USen_US
dc.publisherIndonesian Operations Research Association (IORA) Journalen_US
dc.relation.ispartofOperations Research: International Conference Seriesen_US
dc.subjectLong memory, VaR, TARCH modelsen_US
dc.titleEstimation Of The Value-at-risk (VAR) Using The Tarch Model By Considering The Effects Of Long Memory In Stock Investmentsen_US
dc.typetext::journal::journal article
dspace.entity.typePublication

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