DEFINING RISK CURVES IN FEASIBILITY ANALYSES OF URBAN REGENERATION PROJECTS WITH MONTE CARLO METHOD
Urban regeneration projects offer numerous community benefits, such as improved housing quality and public spaces, but they also carry risks due to uncertainties in key variables for financial analysis, particularly in Discounted Cash Flow Analysis (DCFA). This research presents a practical tool dev...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
DEI Tipografia del Genio Civile
2024-11-01
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| Series: | Valori e Valutazioni |
| Subjects: | |
| Online Access: | https://siev.org/9-36-2024/ |
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| Summary: | Urban regeneration projects offer numerous community benefits, such as improved housing quality and public spaces, but they also carry risks due to uncertainties in key variables for financial analysis, particularly in Discounted Cash Flow Analysis (DCFA). This research presents a practical tool developed in MS Excel that exploits the Monte Carlo method to quantify the risk of loss of value in these projects. Additionally, innovative Risk Curves are introduced to help investors assess the risks based on specified uncertainties in input variables. Focusing on the urban regeneration of the “Mercato del Carmine” in Lucca (Italy), and following EU project evaluation guidelines, a sensitivity analysis identified critical input variables. The financial sustainability of the project was then assessed using indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PP), and Productivity Index (PI). The DCFA confirmed the economic viability of the project. Monte Carlo simulations revealed key variables contributing to a significant risk of value loss, with results showing S-shaped Risk Curves. These curves indicate an acceptable tolerance for variations up to 10 percent in inputs related to initial investments, operating costs, and revenues, but show increasing risks with higher variations. This study highlights the value of Monte Carlo simulations in understanding the impact of uncertainty on regeneration project outcomes. The Excel-based tool provides decision-makers with a practical and user-friendly solution for making more informed choices regarding investment risks in urban regeneration projects. |
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| ISSN: | 2036-2404 |