Open AccessAn Experimental Study with Objectives Functions for Portfolio Optimization Problem
Author(s) -
Darsha Panwar
Publication year - 2022
Publication title -
international journal of research in advent technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9637
DOI - 10.32622/ijrat.912202103
Subject(s) - portfolio optimization , mathematical optimization , portfolio , computer science , multi objective optimization , optimization problem , mathematics , economics , financial economics
This paper presents an experimental study with the objective’s functions of a portfolio optimization problem. This study is done by three optimization problems with a different number of objectives. A hybrid approach has been adopted for this which is a combination of a few methods, such as investor topology, cluster analysis, analytical hierarchy process (AHP), and optimization techniques. Teaching-learning-based optimization (TLBO), biogeography-based optimization (BBO), and fuzzy multi-objective linear programming (FMOLP) are compared in this paper for portfolio optimization. From this research, the conclusion comes that there should not be more options in the objective functions, otherwise the motive of the portfolio becomes misleading, but many more parameters can be used for stock valuation.