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Randomized estimation of the net present value of a housing development allows for the assessment of the efficiency of projects in random implementation conditions. The efficiency of a project is estimated on the basis of primary input data, usually used in project planning. For this purpose, random disturbances are identified that may randomly affect the course and results of the project. The probability and severity of disturbances are determined. The primary initial data is then randomized, and a randomized probabilistic index of the project’s net present value is calculated, the value of which indicates whether the project is profitable or whether implementation should be stopped. Based on this data, the expected total revenue, the expected total cost, the expected gross profit, and the net present value of the randomized performance of the project are calculated. The values of these are estimated for expected, favorable, and unfavorable conditions of implementation. Finally, the risks for the total revenue and total cost of the project are calculated and plotted for comparative revenue values in the range [1, 0] and cost in the range [0, 1]. Their analysis makes it possible to make the right investment decisions before starting the investment at the preparation stage.
Randomized estimation of the net present value of a housing development allows for the assessment of the efficiency of projects in random implementation conditions. The efficiency of a project is estimated on the basis of primary input data, usually used in project planning. For this purpose, random disturbances are identified that may randomly affect the course and results of the project. The probability and severity of disturbances are determined. The primary initial data is then randomized, and a randomized probabilistic index of the project’s net present value is calculated, the value of which indicates whether the project is profitable or whether implementation should be stopped. Based on this data, the expected total revenue, the expected total cost, the expected gross profit, and the net present value of the randomized performance of the project are calculated. The values of these are estimated for expected, favorable, and unfavorable conditions of implementation. Finally, the risks for the total revenue and total cost of the project are calculated and plotted for comparative revenue values in the range [1, 0] and cost in the range [0, 1]. Their analysis makes it possible to make the right investment decisions before starting the investment at the preparation stage.
This article presents an analysis of the volatility of construction project implementation costs, with a particular focus on medium- and long-term projects. Inherent fluctuations in the prices of construction inputs require contractors to use advanced methods of calculating bid prices and formulating base budgets, in accordance with best practices in cost risk management. The article presents an algorithm for determining the contract risk buffer resulting from the increase in the cost of construction work, taking into account the key determinants of risk and their impact on final investment costs. It also discusses legal issues, such as the allocation of risk between contracting parties, and economic aspects related to the construction sector, including the improvement of forecasting tools in the area of investment costs. In addition, the analysis covers issues related to the management of construction projects, the organization of construction processes and the complexity of project structures. The multi-criteria approach used enables a comprehensive assessment of the risks involved in estimating the cost of construction projects.
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