Portfolio design for investment companies through scenario planning

Abstract

Purpose

Scenario planning has significant applications in the field of strategic management and facilitating decision making under uncertainty, and hence this study aims to integrate scenario planning and the preference ranking organisation method for enrichment evaluations (PROMETHEE) method to propose a new methodology to design a portfolio.

Design/methodology/approach

The methodology has been designed in two stages, the first of which identifies the investment environment in Iran and defines possible scenarios for the future based upon the opinion of experts and uncertainties established in the identified environment. In the second stage, the views of experts are elicited on business area performance within each scenario. The business areas are subsequently ranked based on their final performance scores in each scenario area using the PROMETHEE method. Through use of a linear programming model, the percentage of investment in each business area is then determined according to the net flow of the area (i.e. the priority of a certain area relative to others).

Findings

The portfolio design in an Iranian investment company has been considered as a case study. The building industry and cement industry have been selected as preferable strategic business areas based on hypothetical scenarios for investment environment in Iran over five years (2008‐2012) and the strategies of the investment company.

Originality/value

The integration of scenario planning and multi‐criteria decision analysis (MCDA) holds great potential for strategic decision support due to the complementary nature of these two approaches. In this article, the authors provide a methodology to apply scenario planning alongside other MCDA methods to portfolio design, focusing on an innovative use of the PROMETHEE method with scenario planning.

Citation

Hanafizadeh, P., Kazazi, A. and Jalili Bolhasani, A. (2011), "Portfolio design for investment companies through scenario planning", Management Decision, Vol. 49 No. 4, pp. 513-532. https://doi.org/10.1108/00251741111126468