Pricing Mechanisms and Development Prospects of Green Financial Derivatives
グリーン金融デリバティブの価格決定メカニズムと発展展望 (AI 翻訳)
Ruixuan Chen, Jiayu Ou, Ziyue Wan
🤖 gxceed AI 要約
日本語
本研究は、ESGリスク指標と気候データを統合したESG-GARCHモデルを用いて、グリーン金融デリバティブ（例：グリーンボンド先物、カーボンリンクオプション）の価格決定枠組みを提案する。EU排出権取引システムの先物データとグリーン指数を用いた分析により、政策不確実性、環境外部性、ESG要因による流動性変動が価格決定の核心課題であることを示す。企業、金融機関、政策立案者への実践的提言を行う。
English
This paper proposes an improved pricing framework for green financial derivatives (e.g., green bond futures, carbon-linked options) using an ESG-GARCH model that integrates ESG risk indicators and climate data. Analyzing data from the EU ETS futures and green indices, it identifies policy uncertainty, environmental externalities, and liquidity fluctuations from ESG factors as core pricing issues. Practical recommendations are provided for businesses, financial institutions, and policymakers.
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
日本の金融機関がグリーンデリバティブ市場の開拓を検討する際に、本論文の分析枠組みは参考となる。特に、SSBJ開示基準や移行ファイナンスとの関連で、ESG要素を価格に組み込む手法は重要である。
In the global GX context
This paper contributes to the global discourse on climate finance by addressing the underdevelopment of green financial derivatives. It extends the conventional pricing models by incorporating ESG and climate data, relevant for ISSB-aligned disclosures and transition finance frameworks.
👥 読者別の含意
🔬研究者:Provides a novel ESG-GARCH pricing model for green derivatives and identifies key factors affecting pricing validity.
🏢実務担当者:Offers insights for financial institutions developing green derivative products to manage climate risk and expand sustainable investment.
🏛政策担当者:Highlights the need for regulatory clarity to reduce policy uncertainty and enhance market credibility.
📄 Abstract（原文）
Nowadays, green finance has become a significant way to guide the direction of investment because of the growing global climate pressures like the aggravation of greenhouse effect and the urgent need for the low-carbon transition. Therefore, tools like green bonds and green loans are widely used. For example, China’s green credit balance was over 35.75 trillion CNY by the third quarter of 2024. However, green financial derivatives are not well developed, such as green bond futures, carbon-linked options, especially in emerging economies. This paper put forward an improved pricing framework which uses an ESG-GARCH model to put ESG risk indicators and climate data together, in order to track the dynamic impact of volatility. This paper also uses a vector automatic progress (VAR) model to analyze the connections between green fusion variables. The study uses data from futures in the EU emissions trading system, risks and climate value of the green index. Analysis shows that policy uncertainty, environmental externalities and cash liquidity fluctuations caused by ESG factors are core issues in pricing. The study ultimately provides practical advice to businesses, financial institutions and policy makers to enhance market development and point out future research directions to improve the accuracy of models and market credibility. This study aims to connect theory and practice and improve the financial system’s ability to manage climate risks and expand sustainable investment.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.54097/nbc91z94first seen 2026-05-05 22:55:39
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。