A novel approach to multi-objective portfolio selection: modeling emerging financial markets using satisfaction functions and fuzzy values

Generally, selecting an investment portfolio with appropriate returns that is also secure and auditable has been one of the issues raised in recent decades. For this purpose, the present research proposes an appropriate approach using ideal and anti-ideal values, ideal values, as well as maximum deviations of each objective, considering the sample in the examined market, fuzzy goals, interval fuzzy values for each asset, and their combination with satisfaction functions, fuzzy ideal planning, and weighting objectives using expert decision-makers' opinions, as well as the development of fuzzy basic weighting method. It seeks to select an investment portfolio in the digital currency market.

In this research, a new approach to selecting an investment portfolio based on uncertain data and multi-objective uncertain planning is proposed, and ultimately, the proposed approach is implemented in the digital currency market for portfolio selection.

The results of the present study show that the proposed model of investment portfolio compared to the base model not only led to higher returns but also had higher audibility and better risk control. In other words, the proposed model outperformed the base model in all the objectives under study.

Originality/Value:

 As distinguishing features of the proposed model of this research, one can mention: 1) constructing and using fuzzy distribution functions and calculating ideal values and expected ranges for all desired objectives considering the conditions of the examined market research using simple mathematical modeling, 2) utilizing the experience of financial market experts in planning model for selecting suitable investment portfolios in emerging financial markets, 3) presenting an approach to calculating portfolio risk in conditions of information scarcity in the problem environment using fuzzy theory, 4) development of the fuzzy benchmark-criterion method for weighting the objectives under study in the problem considering the expertise of financial market experts, and 5) simple modeling, considering interval fuzzy values in the model, and being usable for all individuals with different levels of investment knowledge.