@article{MAKHILLJEAS2017121914874,
    title = {Peculiarities of Modelling of the Enterprise Investment Attractiveness in the
Conditions of Multicollinearity of Predictors},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {19},
    pages = {4922-4926},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.4922.4926},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.4922.4926},
    author = {N.M.,G.M.,M.F.,E.I. and},
    keywords = {Investment attractiveness,principal components regression,return on assets,evaluation,Kazan,Russia},
    abstract = {The study presents an approach to assess the enterprise investment attractiveness based on the
econometric modeling of return on assets. The researchers underline the key role of financial indicators in
assessing investment attractiveness and propose a system of financial ratios of the enterprise-predictors of
return on assets. In the conditions of collinearity of prognostic factors, the researchers offer to implement ridge
regression which enables to obtain better prognostic characteristics to preserve reliability and informational
value of the modelling. The researchers suggest tools to analyze how predictors of return on assets contribute
to the assessment of investment attractiveness whose quality was tested using standard fisher and student
tests and the standard error. The results of the empirical evaluations carried out using the Gretl Software
confirmed their feasibility for potential investors, shareholders and owners in managing the use of capital
effectively.}
    }