@ARTICLE{26583204_243261798_2018, 
	author = {Maria Shtefan and Julia Elizarova}, 
	keywords = {, investment project, automation of management decisions, integral indicator, efficiency evaluation, risk evaluationprincipal component analysis},
	title = {<p class="text">Investment project efficiency and risk evaluation:&nbsp;an integrated approach</p>},
	journal = {},
	year = {2018},
	number = {4 (46)},
	pages = {54-65},
	url = {https://bijournal.hse.ru/en/2018--4 (46)/243261798.html},
	publisher = {},
	abstract = {&nbsp; &nbsp; &nbsp; While evaluating and selecting investment projects, modern companies are confronted with the problem of setting priorities between profitability and riskiness of these projects. Choice of a project on the basis of its profitability significantly increases risks of financial and economic activities and decreases the certainty of achieving the planned financial result. On the other hand, attempts to decrease investment projects risks may not allow one to achieve the desired profitability level. Therefore, it is vital to develop integrated multi-criteria indicators for this purpose.&nbsp; &nbsp; &nbsp; This article is the result of the authors&rsquo; development of an integral indicator for evaluating investment project efficiency and risks. The developed integral indicator has a matrix form. To compile the integral indicator, three groups of criteria are used: quantitative efficiency criteria, qualitative efficiency criteria and risk evaluation criteria. We propose to divide the qualitative and quantitative criteria into: 1) those defining the commercial (economic) efficiency of projects, 2)&nbsp;those defining their budgetary efficiency; 3) those defining their social efficiency. According to the authors, the list of criteria that define associated risks should include macroeconomic indicators and industry affiliation indicators that provide a comprehensive evaluation of the external economic situation on the corresponding market.&nbsp; &nbsp; &nbsp; While evaluating efficiency and riskiness of the given projects, the integral indicator developed by the authors is converted from matrix form into a quantitative indicator that is easy to interpret. The authors propose to use principal component analysis and heuristic methods (including ranking method and hierarchy analysis method) for this purpose.&nbsp; &nbsp; &nbsp; The results of this research can be used by companies to select investment projects.},
	annote = {&nbsp; &nbsp; &nbsp; While evaluating and selecting investment projects, modern companies are confronted with the problem of setting priorities between profitability and riskiness of these projects. Choice of a project on the basis of its profitability significantly increases risks of financial and economic activities and decreases the certainty of achieving the planned financial result. On the other hand, attempts to decrease investment projects risks may not allow one to achieve the desired profitability level. Therefore, it is vital to develop integrated multi-criteria indicators for this purpose.&nbsp; &nbsp; &nbsp; This article is the result of the authors&rsquo; development of an integral indicator for evaluating investment project efficiency and risks. The developed integral indicator has a matrix form. To compile the integral indicator, three groups of criteria are used: quantitative efficiency criteria, qualitative efficiency criteria and risk evaluation criteria. We propose to divide the qualitative and quantitative criteria into: 1) those defining the commercial (economic) efficiency of projects, 2)&nbsp;those defining their budgetary efficiency; 3) those defining their social efficiency. According to the authors, the list of criteria that define associated risks should include macroeconomic indicators and industry affiliation indicators that provide a comprehensive evaluation of the external economic situation on the corresponding market.&nbsp; &nbsp; &nbsp; While evaluating efficiency and riskiness of the given projects, the integral indicator developed by the authors is converted from matrix form into a quantitative indicator that is easy to interpret. The authors propose to use principal component analysis and heuristic methods (including ranking method and hierarchy analysis method) for this purpose.&nbsp; &nbsp; &nbsp; The results of this research can be used by companies to select investment projects.}
}