Design and Explanation of Portfolio Optimization Model Using Similarity and TOPSIS Methods

Abstract

This study examines and optimizes investment portfolios using Similarity and TOPSIS methods. The aim of this study is to identify and rank assets in order to create a diversified and low-risk portfolio that can provide the best possible returns. The Similarity method is used to identify the correlation between assets and find more diversified combinations, while the TOPSIS method ranks assets based on their proximity to the positive ideal by evaluating multiple criteria. This research is applied in nature and is classified as descriptive-survey research in terms of data collection method. The statistical population of the study includes companies listed on the stock exchange during the period from 2011 to 2020. A judgmental sampling method is employed in this research. The results indicate that the combination of these two methods with the Markowitz model can lead to improved portfolio performance and offer better results under different market conditions. This practical approach enables investors to create an optimized portfolio resistant to market fluctuations through detailed analysis based on multiple data points.