A Data-Driven Design of the Optimal Investment Portfolio for the Industry in a two-level Game using the Markowitz Model by Meta-heuristic Algorithms: Economic Analysis of Condition Monitoring System

Memarpour, Mehdi; Hafezalkotob, Ashkan; Khalilzadeh, Mohammad; Saghaei, Abbas; Soltani, Roya

doi:10.24200/sci.2022.55048.4047

Cited by 2 publications

(1 citation statement)

References 30 publications

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“…Memarpour et al [24] created the optimal portfolios of two players in the banking system in twolevel game, based on the Markowitz model. Optimal investment portfolios of the players were first determined using GAMS and genetic algorithm.…”

Section: Portfolio Optimizationmentioning

confidence: 99%

Comprehensive Process of Multiportfolio Selection and Ordering

Khalil Moghadam,

Mokhatab Rafiei,

Rastegar

2023

Scientia Iranica

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Portfolio optimization studies have traditionally assumed that portfolio managers manage only one portfolio. However, in reality, managers often manage multiple portfolios that can impact each other. This creates a need for fairness to all customers, which has led to the emergence of a new topic called "multiportfolio optimization". Previous studies have paid little attention to this issue, and the models used were not developed using real stock market data. These models were also limited to the selection phase and did not consider the ordering phase.This research provides a comprehensive process for addressing the multiportfolio problem, covering all sections from selection to ordering. It also implements the process using real stock market data. During this process, the market impact function is estimated using the I-STAR model for different stocks. The proposed model for market impact costs includes both permanent and temporary sections. The proposed models were tested using the Tehran Stock Exchange data in 2019.A comparison of the MPO model output with classical models indicates that the proposed model improves utility by an average of 15%. In the next phase, comparing the proposed ordering model with other models shows a reduction in market impact costs by an average of 26%.

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Section: Portfolio Optimizationmentioning

confidence: 99%