Evidence map›Paper›PMID 40690468›Full record

ArticlePloS one2025

A two-stage framework for enhancing crsyptocurrency portfolio performance: Integrating credibilistic CVaR criterion with a novel asset preselection approach.

Hossein Ghanbari, Sina Tavakoli, Mostafa Shabani, Emran Mohammadi, Seyed Jafar Sadjadi, Ronald Ravinesh Kumar

Abstract read
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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hossein GhanbariDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.ORCID https://orcid.org/0000-0002-7815-155X
Sina TavakoliDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
Mostafa ShabaniDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.ORCID https://orcid.org/0009-0003-2766-4245
Emran MohammadiDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.ORCID https://orcid.org/0000-0001-9965-1118
Seyed Jafar SadjadiDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.
Ronald Ravinesh KumarDepartment of Economics and Finance, The Business School, RMIT University, Saigon South Campus, Ho Chi Minh City, Vietnam.ORCID https://orcid.org/0000-0001-9658-4896

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In an increasingly diverse investment landscape, the cryptocurrency market has emerged as a compelling option, offering the potential for high returns, diversification opportunities, and significant liquidity. However, the inherent volatility and regulatory uncertainties of this market present substantial risks, underscoring the need for a well-structured investment strategy. Among the various strategies available, portfolio optimization has become a dynamic and evolving area of focus in finance. Despite advancements in financial modeling, traditional portfolio optimization models often fall short, as uncertainty remains a fundamental characteristic of capital markets. To address this challenge, this paper integrates credibility theory with the Conditional Value-at-Risk (CVaR) framework, harnessing their combined strengths in modeling downside risk and managing uncertainty. Nevertheless, relying solely on this model may not be sufficient for achieving optimal investment outcomes, as portfolio optimization models often neglect the crucial step of selecting high-quality assets. This highlights the essential need for a robust pre-selection process. To tackle this issue, this paper introduces a novel pre-selection framework based on Multi-Attribute Decision Making (MADM) methods. Acknowledging that different MADM approaches can yield varying results-which creates uncertainty regarding the most reliable method-this research proposes a systematic framework for asset evaluation. By considering these factors, this paper proposes a two-stage framework for enhancing cryptocurrency portfolio performance. Stage 1, involves establishing comprehensive performance criteria for cryptocurrencies and employing a novel method for asset pre-selection. Stage 2 focuses on optimizing the selected assets using a credibilistic CVaR model, while considering practical constraints from real-world investment scenarios. The results of this two-stage framework demonstrate its effectiveness in constructing well-diversified and efficient portfolios, addressing both the challenges of asset pre-selection and the complexities associated with uncertainty. By integrating these methodologies, investors can navigate the risks associated with cryptocurrency investments more effectively while maximizing potential returns.

Indexed as

InvestmentsModels, EconomicHumansUncertainty

Identifiers

PMID40690468
PMCPMC12279154

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.