Modelling of Investment Portfolio

Pabedinskaitė, Arnoldina Ona

Use this URL to cite this publication: https://hdl.handle.net/20.500.14911/144993

Modelling of Investment Portfolio

Details

Publication Type (CRIS)

Straipsnis recenzuojamoje užsienio tarptautinės konferencijos medžiagoje / Article in peer-reviewed foreign international conference proceedings (P1d)

Publication Type (eLABa)

Straipsnis recenzuotame konferencijos darbų leidinyje / Article published in peer-reviewed conference proceedings (P1d)

Author(s)

Title

Modelling of Investment Portfolio

[en]

A. Pabedinskaitė

Is part of

International scientific dual-conference Towards knowledge-based economy & Enterprise management: diagnostics, strategy, effectiveness, April 12-13, 2007 Riga Latvia: conference proceedings [CD] / Riga Technical University, National technical University of Ukraine Kyiv Polytechnic Institute, International Association of Deans of Economoc faculties of Technical Universities

Published In

Year	Start Page	End Page
2007	1	9

Publisher

Riga : RTU Publishing House, 2007

Extent

p. 1-9

URI

URI
https://hdl.handle.net/20.500.14911/144993

Cited references

Science / Art Area

Socialiniai mokslai / Social sciences (S)

Field of Science / Art

Vadyba / Management (S003)

Keywords (en)

Abstract (en)

The task of selection of an investment portfolio (it may include investments in financial assets, various projects, and manufacturing of new products) is a typical task of decision-making under conditions of uncertainty. An effective method of assessment of the risk level and selection of portfolio of new products under conditions of uncertainty is a direct statistical modelling (Monte Carlo method). In order to assess the influence of such factors as the duration of life cycle, profitability of products and variation of demand for the products, modelling of a seven-year plan of manufacturing five new products has been carried out on an experimental example. The production plan has been developed with the help of a linear programming task having resource and production volume (restricted by the quantity of demand) constraints. Demand for the products has been modelled in the form of joint normal distribution with the given correlation matrix. After obtaining an optimum production plan that would maximise profit, the level of risk of this plan has been assessed.