ECONOMICS, MANAGEMENT AND ORGANIZATION OF CONSTRUCTION PROCESSES

Quantitative assessment of risks for an investment project in the construction industry

Vestnik MGSU 3/2013
  • Skiba Alisa Anatol’evna - Moscow State University of Civil Engineering (MGSU) postgraduate student, Department of Information Systems, Technologies and Automation in Construction, Moscow State University of Civil Engineering (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337; This e-mail address is being protected from spambots. You need JavaScript enabled to view it .
  • Ginzburg Aleksandr Vital’evich - Moscow State University of Civil Engineering (MGSU) (National Research University) Doctor of Technical Sciences, Professor, chair, Department of Information Systems, Technologies and Automation in Construction, Moscow State University of Civil Engineering (MGSU) (National Research University), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; This e-mail address is being protected from spambots. You need JavaScript enabled to view it .

Pages 201-206

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.

DOI: 10.22227/1997-0935.2013.3.201-206

References
  1. Kovalev V.V. Finansovyy menedzhment. Teoriya i praktika. [Financial Management. Theory and Practice.] Moscow, Prospekt Publ., 2007, 1,024 p.
  2. Endovitskiy D.A., Gilyarovskaya L.T., editor. Kompleksnyy analiz i kontrol’ investitsionnoy deyatel’nosti: metodologiya i praktika [Comprehensive Analysis and Control over Investment Operations: Methodology and Practice]. Moscow, Finansy i statistika publ., 2001, 400 p.
  3. Vasil’eva T.A., Didenko O.N., Epifanov A.A. Risk-menedzhment innovatsiy [Risk Management of Innovations]. Sumy, Delovye perspektivy publ., 2005, 260 p.
  4. Ermakov C.M. Statisticheskoe modelirovanie [Statistical Modeling]. Moscow, Nauka Publ., 1982, 296 p.
  5. Zade L. Ponyatie lingvisticheskoy peremennoy i ee primenenie k prinyatiyu priblizhennykh resheniy [Notion of a Linguistic Variable and Its Application to Approximate Decision Making]. Moscow, Mir Publ., 1976, 167 p.

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RISK ANALYSIS FOR INVESTMENT PROJECTS IN THE CONSTRUCTION INDUSTRY

Vestnik MGSU 12/2012
  • Skiba Alisa Anatol'evna - Moscow State University of Civil Engineering (MGSU) postgraduate student, Department of Information Systems, Technologies and Automation in Civil Engineering, Moscow State University of Civil Engineering (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; This e-mail address is being protected from spambots. You need JavaScript enabled to view it .
  • Ginzburg Aleksandr Vital'evich - Moscow State University of Civil Engineering (MGSU) Doctor of Technical Sciences, Professor, Professor of Department of Information Systems, Technologies and Automation in Civil Engineering, Moscow State University of Civil Engineering (MGSU), 26 Yaroslavskoe shosse, Moscow, 129337, Russian Federation; This e-mail address is being protected from spambots. You need JavaScript enabled to view it .

Pages 276 - 281

The authors discuss the procedure of measuring and managing risks that investment projects in the construction industry may be exposed to in the process of their implementation.
The qualitative analysis results in description of uncertainties characterizing the project as well as in the breakdown of the reasons for these uncertainties. Risks identified in the course of analysis should be ranked according to their significance and possible losses that they may involve. The main risks need research through the employment of the quantitative analysis to make assessments more accurate.
The authors compare the applied methods used in practice to perform a quantitative analysis of project risks with the new ones based on the fuzzy logic concept. All models are broken down into three groups: stochastic (probabilistic), linguistic (descriptive) and non-stochastic (behavioral).
Aims, advantages and disadvantages of methods are arranged into a table. Some methods can be implemented in combination to assure a reasonable efficiency of decisions.

DOI: 10.22227/1997-0935.2012.12.276 - 281

References
  1. Kachalov P.M. Upravlenie khozyaystvennym riskom [Business Risk Management]. Moscow, Nauka Publ., 2005.
  2. Volkov A.A. Upravlenie i logistika v stroitel’stve: sistemnyy analiz perspektivnykh napravleniy [Management and Logistics in Construction: System Analysis of Prospective Lines of Development]. Vestnik MGSU [Proceedings of Moscow State University of Civil Engineering]. 2007, no. 3, pp. 124—126.
  3. Nedosekin A.O. Prosteyshaya otsenka riska investitsionnogo proekta [The Simplest Assessment of Investment Project Risks]. Sovremennye aspekty ekonomiki [Modern Aspects of the Economy]. No. 11, 2002.
  4. Stepanov I.S. Ekonomika stroitel’stva [Construction Economics]. Moscow, Yurayt Publ., 2005.
  5. Nedosekin A.O. Fondovyy menedzhment v rasplyvchatykh usloviyakh [Stock Management in the Uncertain Environment]. St.Petersburg, Sezam Publ., 2003.
  6. Tepman L.N., Shvandar V.A., editor. Riski v ekonomike [Risks in the Economy]. Moscow, YuNITI Publ., 2007.

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