New methods risk management of investment projects
The adoption of investment solutions uncertainty factors provide project risk, i.e. the risk of loss of resources, incomplete acquisition of the required income and occurrence unexpected expenses. The presence of different types uncertainty brings us to the need to adapt the indicators of efficiency valuation of investment projects by using of mathematical methods that allow to formalize different types of uncertainty. Among the various methods of modeling under uncertainty it is possible to allocate three basic approaches: probability, fuzzy-set theory and expert estimation. As shown by the world experience, the effectiveness using of methods based on probability, fuzzy sets and expert estimation depends on the level and character of uncertainty associated with a particular tasks. Indeed, increasing uncertainty classical probabilistic description retreat place of subjective probability based on expert estimation, or fuzzy set interval descriptions denote by membership function. This article shows the uniqueness of fuzzy set intervals descriptions based on the principles of fuzzy logic in evaluation the economic efficiency of investment projects compared to older classic method.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 2009 (2009)
Issue (Month): 4 ()
|Contact details of provider:|| Postal: |
Phone: (02) 24 09 51 11
Fax: (02) 24 22 06 57
Web page: http://www.vse.cz/
More information through EDIRC
|Order Information:|| Postal: Redakce Ekonomika a management, Vysoká škola ekonomická v Praze, nám. W. Churchilla 4, 130 67 Praha 3|
Web: http://www.vse.cz/eam/ Email:
When requesting a correction, please mention this item's handle: RePEc:prg:jnleam:v:2009:y:2009:i:4:id:81. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vaclav Subrta)
If references are entirely missing, you can add them using this form.