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

^Authors: Jones Osei¹, Peter Kwasi Sarpong², Samuel Amoako³

Mathematics Department, Kwame Nkrumah University of Sciene & Technology

 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 Va R  are implemented using Historical Simulation and Monte Carlo approach on stock portfolio. Different Values of confidence levels are also used for each of the method. The study is conducted on six fundamentally different 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% confidence levels. Nonetheless, the VaR 95% has the highest simulation time.

Keywords: VaR, Historical Simulation and Monte Carlo Simulation

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