Keywords: investment appraisal, genetic algorithms, GA, Monte Carlo simulation, MCS, risk assessment, project management, uncertainty, investment decisions
Incorporating uncertainty in optimal investment decisions
Investment decisions are now more crucial than ever. The investors are in need of sound arguments, which will be able to shape the investment specifications and appraise their uncertain nature. This paper proposes an innovative approach that merges optimisation and risk analysis in one single method. The two-step investment appraisal approach reaches an optimum through a Genetic Algorithm optimisation and then assesses the environment's risk through a Monte Carlo simulation. The approach, thus, offers the best investment characteristics, as well as information about its implied risk. The use of the method is illustrated through an extensive Case Study.