Risk analysis in investment appraisal based on the Monte Carlo simulation technique
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DOI: 10.1007/s100510170238
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Cited by:
- Yonggu Kim & Eul-Bum Lee, 2018. "A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk," Sustainability, MDPI, vol. 10(3), pages 1-24, March.
- Klein, Martin & Deissenroth, Marc, 2017.
"When do households invest in solar photovoltaics? An application of prospect theory,"
Energy Policy, Elsevier, vol. 109(C), pages 270-278.
- Martin Klein & Marc Deissenroth, 2018. "When Do Households Invest in Solar Photovoltaics? An Application of Prospect Theory," Papers 1808.05572, arXiv.org.
- Georgios Tziralis & Konstantinos Kirytopoulos & Athanasios Rentizelas & Ilias Tatsiopoulos, 2009. "Holistic investment assessment: optimization, risk appraisal and decision making," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 30(6), pages 393-403.
- Andres Soage & Ruben Juanes & Ignasi Colominas & Luis Cueto-Felgueroso, 2024. "Optimization of Financial Indicators in Shale-Gas Wells Combining Numerical Decline Curve Analysis and Economic Data Analysis," Energies, MDPI, vol. 17(4), pages 1-25, February.
- Knoope, M.M.J. & RamÃrez, A. & Faaij, A.P.C., 2015. "The influence of uncertainty in the development of a CO2 infrastructure network," Applied Energy, Elsevier, vol. 158(C), pages 332-347.
- Padi, Richard Kingsley & Douglas, Sean & Murphy, Fionnuala, 2023. "Techno-economic potentials of integrating decentralised biomethane production systems into existing natural gas grids," Energy, Elsevier, vol. 283(C).
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Keywords
PACS. 02.70.Lq Monte Carlo and statistical methods;Statistics
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