Mathematical modeling for a new portfolio selection problem in bubble condition, using a new risk measure

Ghahtarani, Alireza; Sheikhmohammady, Majid; Najafi, Amir Abbas

doi:10.24200/sci.2019.51577.2258

Cited by 4 publications

(2 citation statements)

References 42 publications

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“…The FANP approach was used to rank portfolios in consideration of uncertain conditions and decision-makers' judgments. Ghahtarania et al [23] developed a mathematical model transformed into an integer linear programming. The novelty of the research is risk criteria which is measured based on the difference between fundamental value and the market value of stocks.…”

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%

Comprehensive Process of Multiportfolio Selection and Ordering

Khalil Moghadam,

Mokhatab Rafiei,

Rastegar

2023

Scientia Iranica

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“…Moreover, there is not any systematic way to specify the threshold. Ghahtarani et al (2019) formulation uses the fundamental value of an asset as a threshold of the Omega ratio, which protects the portfolio against bubble conditions in the market. Sharma et al (2017) redefined the Omega ratio by using a loss function instead of the return in it.…”

Section: Robust Omega and Betamentioning

confidence: 99%

Robust Portfolio Selection Problems: A Comprehensive Review

Ghahtarani¹,

Ahmed²,

Ghasemi³

2021

Preprint

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In this paper, we provide a comprehensive review of recent advances in robust portfolio selection problems and their extensions, from both operational research and financial perspectives. A multi-dimensional classification of the models and methods proposed in the literature is presented, based on the types of financial problems, uncertainty sets, robust optimization approaches, and mathematical formulations. Several open questions and potential future research directions are identified.

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