← 論文一覧に戻る

MULTICRITERIA ANALYSIS IN ESG-ORIENTED PORTFOLIO OPTIMIZATION

ESG指向ポートフォリオ最適化における多基準分析 (AI 翻訳)

Камар Кожахметова, D. Rakhmatullayeva, K. Ruziev

Bulletin📚 査読済 / ジャーナル2026-06-30#ESG経営インパクト: 資金調達対象セクター: finance
DOI: 10.32014/2026.2518-1467.1224
原典: https://journals.nauka-nanrk.kz/bulletin-science/article/download/8640/5644
📄 PDF

🤖 gxceed AI 要約

日本語

本稿は、ESG指向ポートフォリオ最適化における多基準分析(MCA)の方法論的役割を体系的にレビューする。従来のリスク・リターンに加え、ESG指標を統合するためのTOPSIS、PROMETHEE、AHP等の手法を比較し、それらが持続可能な投資判断の透明性と説明可能性を高めることを示す。MCAは古典的ポートフォリオ理論の拡張として機能し、財務的合理性とESG優先事項のバランスを可能にする。

English

This paper systematically reviews the role of multicriteria analysis (MCA) in ESG-oriented portfolio optimization. It compares methods like TOPSIS, PROMETHEE, VIKOR, AHP, Entropy, and CRITIC for integrating ESG criteria into investment decisions. The review finds that MCA enhances transparency and explainability in portfolio selection, serving as a methodological extension of classical portfolio theory for sustainable finance.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本ではSSBJ基準や統合報告書の普及に伴い、ESG統合投資の重要性が高まっている。本レビューは、ポートフォリオ最適化における多基準分析の実践的枠組みを提供し、日本の運用機関や企業のサステナビリティ担当者にとって有用である。

In the global GX context

As TCFD, ISSB, and CSRD drive ESG disclosure globally, asset managers require robust tools to incorporate non-financial data. This review surveys MCDA methods that operationalize ESG integration in portfolio optimization, offering transparent alternatives to black-box models.

👥 読者別の含意

🔬研究者:This review provides a structured taxonomy of MCDA methods for ESG portfolio optimization, useful for researchers developing multi-criteria decision frameworks.

🏢実務担当者:Asset managers can leverage the reviewed MCDA methods (e.g., TOPSIS, AHP) to build transparent ESG-integrated portfolios that align with client sustainability preferences.

📄 Abstract(原文)

The article discusses multicriteria analysis as a methodological tool for integrating financial and non-financial ESG criteria in portfolio optimization tasks. The relevance of the study is due to the fact that the classical model of portfolio selection based on the ratio of return and risk no longer fully reflects the current requirements of sustainable investment. As the importance of environmental, social, and managerial factors increases, investment decisions become multidimensional, requiring the use of methods that can combine diverse indicators into a single analytical system. The purpose of the article is to systematize scientific approaches to the use of multi-criteria analysis in ESG-oriented portfolio optimization. The research methodology is based on a review and comparative analysis of scientific literature on portfolio theory, MCDA/MCDM methods, socially responsible investment, and ESG integration. Special attention is given to the functions of multi-criteria analysis, including the normalization of financial and ESG indicators, the determination of criterion weights, the ranking of assets, the formation of integrated assessments, and the search for a balance between profitability, risk, and sustainability. The review results show that multi-criteria analysis expands the traditional portfolio optimization model and allows taking into account not only financial efficiency, but also long-term non-financial risks of companies. It has been established that MCA can be applied at various stages of the investment process: in the preliminary ESG screening, building ESG scoring, ranking assets and inclusion of ESG criteria in optimization models. It is shown that the TOPSIS, PROMETHEE, VIKOR, AHP, Entropy, CRITIC methods and their hybrid combinations provide a more transparent and explainable portfolio selection procedure. It is concluded that multi-criteria analysis is not an alternative to classical portfolio theory, but rather a methodological extension of it in the context of sustainable finance. Its application allows for the formation of more balanced investment decisions that combine financial rationality, ESG priorities, and investor preferences.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。