Authors: Peter Kwasi Sarpong1, Iones Osei2, Samuel Amoako3
Email: kp.sarp@yahoo.co.uk, oseijones2013@gmail.com, Samkamoako2016@gmail.com
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: Value at Risk, Risk Approach, Risk Simulation