Performance Measure of Value at Risk Using Monte Carlo Approach and Historical Simulation

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dc.contributor.authorOsei, Jones
dc.date.accessioned2017-01-20T11:35:24Z
dc.date.accessioned2023-04-18T22:26:06Z
dc.date.available2017-01-20T11:35:24Z
dc.date.available2023-04-18T22:26:06Z
dc.date.issuedOCTOBER, 2016
dc.descriptionA thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the Degree of Master of Philosophy in Applied Mathematics, en_US
dc.description.abstractValue at risk (VaR) is a management tool for measuring and controlling risk. Individual and institutional investors rely their investment decisions increasingly on the risk inherent in a security. In this theses, calculating of VaR are implemented using Historical Simulation and Monte Carlo approach on stock portfolio. Di erent Values of con dence levels are also used for each of the method. The study is conducted on six fundamentally di erent stocks. Data on daily prices on collected for a period of eight years (2007-2014) for all stocks assets and their corresponding log returns calculated. From our analysis, Monte-carlo Simulation had an optimal values of VaR as compared to Historical simulation in both the VaR 95% and VaR 99% con dence levels. Nonetheless, the VaR 95% has the highest simulation time.en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/10088
dc.language.isoenen_US
dc.titlePerformance Measure of Value at Risk Using Monte Carlo Approach and Historical Simulationen_US
dc.typeThesisen_US
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