Title: A preference ranking model based on both mean-variance analysis and cumulative distribution function using simulation

Authors: Khwazbeen S. Fatah, Peng Shi, Jamal R.M. Ameen, Ronald J. Wiltshire

Addresses: Faculty of Advance Technology, University of Glamorgan, Pontypridd, CF37 1DL, UK. ' Faculty of Advance Technology, University of Glamorgan, Pontypridd, CF37 1DL, UK. ' Faculty of Advance Technology, University of Glamorgan, Pontypridd, CF37 1DL, UK. ' Faculty of Advance Technology, University of Glamorgan, Pontypridd, CF37 1DL, UK

Abstract: In decision-making problems under uncertainty, mean-variance analysis consistent with expected utility theory plays an important role in analysing preferences for different alternatives. In this paper, a new approach for mean-variance analysis based on cumulative distribution functions is proposed. Using simulation, a new algorithm is developed, which generates pairs of random variables to be representative for each pair of uncertain alternatives. The proposed model is concerned with financial investment for risk-averse investors with non-negative lotteries. Furthermore, the proposed technique in this paper can be applies to different distribution functions for lotteries or utility functions.

Keywords: mean variance theory; expected utility theory; cumulative distribution function; simulation; preference ranking; modelling; decision making; uncertainty; financial investment; risk-averse investors; non-negative lotteries; risk aversion.

DOI: 10.1504/IJOR.2009.025199

International Journal of Operational Research, 2009 Vol.5 No.3, pp.311 - 327

Published online: 16 May 2009 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article