Do negative ESG news events trigger abnormal trading activity? evidence from the Chinese stock market
ネガティブなESGニュースイベントは異常な取引活動を引き起こすか？中国株式市場からの証拠 (AI 翻訳)
Zilong Yang
🤖 gxceed AI 要約
日本語
本研究は、2015-2023年の中国A株市場で、ネガティブなESGニュースが短期取引に与える影響を分析。BERTベースの分類器で4,873件のイベントを特定し、異常出来高が2.84%ポイント上昇（28.3%増）、取引量35%増、特異的変動性19.6%ポイント上昇を示した。媒介分析で注意チャネル（41%）と信念乖離チャネル（33%）を解明。ガバナンス論争が最も強く、薄いアナリストカバレッジと低い機関所有率で増幅された。
English
This paper examines how negative ESG news affect short-run trading in China's A-share market (2015-2023). Using a BERT classifier, it identifies 4,873 events and finds abnormal turnover +2.84pp (28.3% relative increase), volume +35%, and idiosyncratic volatility +19.6pp in the [-1,+3] window. Mediation analysis reveals attention (41%) and belief-divergence (33%) channels. Governance controversies trigger strongest reactions; effects amplify in firms with low analyst coverage and institutional ownership.
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
中国市場に焦点を当てるが、日本企業の中国現地法人のESGリスク管理や、日本におけるSSBJや有報でのESG開示義務化議論に示唆を与える。特に、ネガティブニュースの市場影響は投資家対応や開示制度設計に重要。
In the global GX context
While set in China, this paper offers global lessons on how ESG controversies affect market quality. It demonstrates the power of NLP for ESG monitoring and causal identification of reaction channels, informing disclosure regulation and investor protection worldwide.
👥 読者別の含意
🔬研究者:Novel application of BERT to classify ESG events with causal evidence on market reaction channels (attention vs. belief divergence).
🏢実務担当者:Highlights that negative ESG news significantly increase stock volatility and turnover, underscoring the need for proactive ESG management to mitigate market disruptions.
🏛政策担当者:Provides empirical support for mandatory ESG disclosure to enhance market transparency and protect investors from information asymmetry.
📄 Abstract（原文）
This paper examines how negative ESG (Environmental, Social, and Governance) news events shape short-run trading dynamics in China's A-share market over 2015–2023. Treating ESG controversies as a distinct category of non-financial risk signal, this research identifies 4,873 firm-level events across six subcategories—environmental violations, industrial accidents, labor disputes, food-safety crises, executive misconduct, and regulatory sanctions—via a BERT-based text classifier. Within the [−1, +3] event window, abnormal turnover averages 2.84 percentage points above benchmark (a 28.3% relative elevation), trading volume expands by roughly 35%, and idiosyncratic volatility rises by 19.6 percentage points. Mediation analysis decomposes the total effect into an investor-attention channel (≈ 41%) and a belief-divergence channel (≈ 33%). Governance controversies generate the strongest reactions; effects are amplified in firms with thin analyst coverage and low institutional ownership. Three identification strategies—instrumental variables, difference-in-differences, and propensity score matching—support a causal interpretation. The findings inform mandatory ESG disclosure policy and institutional investor development in China.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://jaeps.ewapub.com/article/view/35034.pdffirst seen 2026-07-18 08:07:51
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