Fuzzy-Monte Carlo Simulation For Risk Analysis Investment Project Evaluation

Loading...
Thumbnail Image
Date
2011-08
Authors
Hamundu, Ferdinand Murni
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
For a long time, incorporating risk management into the investment project plan has been a popular method in order to mitigate a risk of the investment. However, the problem still exists in risk analysis, such as the difficulties to involve the non-financial risks in an economic model for evaluating the investment project. One of the solutions for modeling of imprecise and the qualitative knowledge is employing fuzzy logic. Therefore, this thesis proposes Fuzzy-Monte Carlo Simulation that is able to bridging the financial and non-financial risk for estimating the probability of Cumulative Cash Flow (CCF), Net Present Value (NPV) and Internal Rate of Return (IRR). In order to realize the proposed solution, this thesis performs two methods. Firstly, the qualitative risk analysis for identifying significant risks by using Analytic Hierarchy Process (AHP). Secondly, the quantitative risk analysis to discover the impact of the significant risks to the investment project output by using Fuzzy-Monte Carlo Simulation. The fuzzy inference system output and historical data of financial risks are assigned in appropriate of probability distribution before simulation. The simulation conducted several scenarios of risk involvement in an economic model of the case study project for validating our approach. The simulation result shows the certainty of loss with a range of loss USD0-6,792,500 as actual data of CCF in year 2008 is 75%. Furthermore, the NPV and IRR estimation and also recommendation for the risk response planning is presented. The results of the proposed solution validate the objective of this work to bridging the financial and non financial risk for risk analysis in investment project evaluation.
Description
Keywords
Fuzzy-Monte Carlo simulation for , risk analysis investment project
Citation