APPLICATION OF 4-DIMENSIONAL COPULAS IN CALCULATING VALUE-AT-RISK FOR THE PORTFOLIO OF 4 SP500 COMPANIES

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dc.contributor.authorBolatbekov, Kairzhan
dc.date.accessioned2023-06-05T08:25:39Z
dc.date.available2023-06-05T08:25:39Z
dc.date.issued2023
dc.description.abstractPortfolio risk management is a process aimed at maintaining profit streams and reducing uncertainties in investment decisions. Value-at-Risk (VaR) is a widely used metric to quantify the potential loss of profits. Although historical simulations and Gaussian distribution are common methods for estimating VaR, modelling the joint multivariate distribution of portfolio investments can be challenging. Copula models offer a solution to these challenges for joint distributions. In this study, we calculated VaR and Conditional Value-at-Risk (CVaR) for a portfolio consisting of the four least correlated stocks among the 15 largest companies in the SP 500 using historical simulations and copula models. We evaluated portfolio based on equal weighting. The optimal ARIMA-GARCH model was selected using Akaike Information Criteria (AIC) values. Furthermore, the performance of the VaR estimations was compared and analyzed using goodness-of-fit tests.en_US
dc.identifier.citationBolatbekov, K. (2023). Application of 4-dimensional Copulas In Calculating Value-At-Risk for the Portfolio of 4 SP500 companies. School of Sciences and Humanitiesen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/7184
dc.language.isoenen_US
dc.publisherSchool of Sciences and Humanitiesen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectType of access: Open Accessen_US
dc.subjectVaRen_US
dc.subjectCopulaen_US
dc.subjectARIMA-GARCHen_US
dc.subjectRisk Managementen_US
dc.subjectData Seriesen_US
dc.titleAPPLICATION OF 4-DIMENSIONAL COPULAS IN CALCULATING VALUE-AT-RISK FOR THE PORTFOLIO OF 4 SP500 COMPANIESen_US
dc.typeCapstone Projecten_US
workflow.import.sourcescience

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