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Full Length Research Paper
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Decision-support analysis for risk management
Hülya Demir1* and Bülent
Bostanci2
1Yildiz Technical University, Department of Surveying
Engineering, Istanbul, Turkey.
2Kayseri
Erciyes University, Department of Surveying Engineering,
Kayseri, Turkey
*Corresponding author. E-mail:
hudemir@yildiz.edu.tr.
Accepted 1 June, 2010 |
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Abstract |
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Generally, a project is an investment suggestion, which requires
making a series of investment expenditures (cash outflow) in a
planned manner to obtain more cash inflow in the future.
Therefore, the basic objective of project appraisal should be to
make prior decisions on the feasibility of investment advice.
The results of project feasibility can be classified into two
categories: uncertainty and risk. Risks related to investment
and financial markets are also closely related with the audit
and supervision authorities. One of the main objectives of
regulatory and control authorities is to achieve economic
stability in the market and to minimize systematic risks. This
requires that all institutions define the risks they will
encounter, measure these risks via risk analysis techniques and
assess the potential impacts of these risks on the institution.
Today, projects within the housing sector -which has been
heavily hit by the recent economic crisis- are one of the areas
subject to risk analysis. This article aims to determine and
discuss risks factors within the housing project development
process by applying discounted cash flow analysis (DCF), Monte
Carlo Simulation (MCS) and sensitivity analysis to a housing
sector with an integrated approach. Two different discounted
cash flow models were developed as part of a scenario analyzing
a housing development project. These models were subjected to
risk analysis based on MCS, one of the many methods analyzing
risk distribution. Thus, data from the probability distributions
are envisaged to strengthen the trust of the manager in the
value and acceptance of the project, and to concretize the
attitude to risk of the decision making group. In conclusion,
the study defined important variables for efficient risk
management of housing development projects and developed a
risk-decision support model, which incorporates scenario
analysis and MCS.
Key words:
Risk analysis, decision-support analysis, risk management, Monte
Carlo simulation, discounted cash flow analysis (DCF). |
