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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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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.descriptionVolume :1 No:1en_US
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.typeArticleen_US
dspace.entity.typePublication

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