A quantifying method of microinvestment optimum

Albu, Lucian-Liviu and Camasoiu, Ion and Georgescu, George (1985): A quantifying method of microinvestment optimum. Published in: Revue Roumaine des Sciences Economiques , Vol. 29, No. 1 : pp. 45-54.

Abstract

Amid the controversies around the optimisation criteria and the objective functions when applying mathematical methods in economics, we proposed a method of quantifying a multi-criteria optimum, called critical distance method. The demonstration of this method is exemplified by assessing the investment optimum at microeconomic level (project or company portfolio choice). A hyperbolic paraboloid function of three variables (the recovery time, the investment value and the unit cost) representing a surface of the second degree has been defined. The intersection of the hyperbolic parabola planes identifies the point where the three considered variables have the same value, signifying an equal importance attached to them and revealing the optimum level of their interaction. The distance from this critical point to the origin represents, in fact, the criterion according to which one could choose the most efficient investment alternative. In our opinion, the proposed method could be extended to the study of any economic process.

• Item Type: MPRA Paper
• Language: English
• Keywords: microeconomic optimum; critical distance method; portfolio choice; investment alternatives; multi-criteria optimum
• Subjects: B - History of Economic Thought, Methodology, and Heterodox Approaches > B2 - History of Economic Thought since 1925 > B21 - Microeconomics; G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions; B - History of Economic Thought, Methodology, and Heterodox Approaches > B2 - History of Economic Thought since 1925 > B23 - Econometrics ; Quantitative and Mathematical Studies; C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis

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