quantitative assessment of risks for an investment project in the construction industry Количественная оценка рисков строительно-инвестиционного проекта
Clicks: 292
ID: 231392
2013
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
292 views
36 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #19 of 140 articles by views in PsyCh journal
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 140 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The authors discuss basic methods of statistical surveillance used to assess risks associated with construction investment projects. The methods considered in this article include a sensitivity analysis (based on the assessments of initial parameters of a project and its final characteristics (usually IRR or NPV)), a method of scenarios (based on assessment of the risk of the project failure considered as the total of all probabilities of a negative NPV), a method of discount rate adjustments (based on the adjustment of the discount rate by adding a risk premium calculated by an expert or an in-house specialist), a decision tree method (whereby a project is reduced to development of a hierarchical scheme of all possible actions; results of an investment project have a treeshaped structure), a Monte Carlo method (meaning a special case of simulation). The authors describe their main advantages, disadvantages and problems that accompany their practical application. The authors also describe methods based on the fuzzy logic theory and suggest formalization of inputs and outputs as a fuzzy interval. General milestones include fuzzification, development of fuzzy rules, de-fuzzification, and methods of de-fuzzification (including a method of maximum centre, a method of maximum value, and a centroid method). The authors make their conclusion in respect of the method that may be regarded as the most suitable for investment projects in the construction industry.
Рассмотрены основные статистические методы количественной оценки рисков строительно-инвестиционного проекта, а также методы, основывающиеся на теории нечеткой логики.
Рассмотрены основные статистические методы количественной оценки рисков строительно-инвестиционного проекта, а также методы, основывающиеся на теории нечеткой логики.
| Reference Key |
anatolevna2013vestnikquantitative
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Skiba Alisa Anatol’evna;Ginzburg Aleksandr Vital’evich |
| Journal | PsyCh journal |
| Year | 2013 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.