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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10088

Title: Performance Measure of Value at Risk Using Monte Carlo Approach and Historical Simulation
Authors: Osei, Jones
Issue Date: 20-Jan-2017
Abstract: Value 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.
Description: A 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, 2016
URI: http://hdl.handle.net/123456789/10088
Appears in Collections:College of Science

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