Stochastic risk analysis in Monte Carlo simulation: a case study

This paper proposes a model to aid in the decision making to evaluate in Monte Carlo (MC) simulation, some risk analysis measures as the Net Present Value (NPV) through the well known @RISK software. A case study of launching a new product in the Ramdy company is performed to examine quantitative stochastic risks in a decision making process. Real data allows to know the input distributions, then, MC Simulations were performed by generating input Latin Hypercube Samples. Success was measured using NPV output samples. Additional analysis suggested that the growth rate of the second year variable was sensitive to our NPV model.