A key question at the interface of sustainable finance and market efficiency is whether capital markets discipline firms not only for what they do—emissions, violations, or green investment—but also for how they communicate their environmental positions. Disclosure research suggests that the quality and verifiability of environmental narratives matter for investors, yet the pricing of narrative fuzziness itself remains underexplored. This study examines whether capital markets respond to the way high-polluting firms narrate green constraints in their annual reports. We construct a large-language-model-based fuzzy disclosure index (GFIX) from Chinese MD&A texts. Using only pre-2008 annual reports for scale learning, we train a two-stage comparator–scorer system from sentence-level pairwise judgments and apply it to MD&A sentences from 2008 to 2025. The resulting firm–year GFIX is matched with announcement-quarter stock returns and ownership data for 1016 high-polluting A-share firms. Double/debiased machine learning and panel fixed-effects estimates show that higher GFIX is systematically associated with significantly lower announcement-quarter returns, suggesting that investors treat fuzzy green narratives as a signal of information risk under green transition. The discount is concentrated in high-polluting manufacturing industries and firms with higher non-institutional ownership, while higher GFIX also predicts subsequent declines in institutional ownership. In addition, major Chinese green-regulatory milestones are followed by systematic increases in GFIX. These findings indicate that narrative clarity is an economically meaningful channel through which green transition and environmental regulation are transmitted to asset prices and ownership reallocations. These findings carry direct implications for sustainable finance: disclosure verifiability appears to be a first-order determinant of how green-transition risks are priced, and strengthening the verifiability of mandatory environmental disclosure can lower information risk, reduce the discount applied to opaque narrators, and support the orderly pricing of transition risks, in line with SDG 12 (responsible consumption and production) and SDG 13 (climate action).
Using a panel of 45,385 firm-year observations of Chinese A-share listed firms over 2010-2025, this paper examines whether firm-level artificial intelligence (AI) development affects stock price crash risk. Two-way fixed effects estimates show that a higher level of corporate AI development significantly reduces both t...
Yi-Xuan Li· Advances in Economics, Manag...· 0 citations
This study advances a signal-reweighting perspective by examining whether environmental disclosure changes how investors interpret corporate performance signals in an emerging capital market. The research gap arises because prior studies commonly treat environmental disclosure as a direct determinant of firm value, whi...
Meilani Intan Pertiwi, Wijang Sakitri, Siti Noor Aini Hidayah et al.· Indonesia accounting researc...· 0 citations
This study aims to examine whether corporate social responsibility disclosure (CSRD) is associated with stock liquidity in Vietnam’s prescribed reporting setting.
Using 2,476 firm-year observations for 499 non-financial firms during 2015–2019, the study estimates firm and year fixed-effects models with firm-...
Using a sample of Chinese A-share listed firms from 2021 to 2024, we employ a large language model (LLM) to measure the tone of approximately 20,000 Management Discussion and Analysis (MD&A) sections and examine whether narrative tone signals future audit risk. We document four findings. First, MD&A tone significantly...
Climate policy uncertainty may prompt firms to prepare for regulation while delaying irreversible green investment. We examine whether firm-level exposure is nonlinearly associated with green innovation. Exposure combines a news-based provincial climate policy uncertainty index with transition exposure extracted from a...
This study examines whether text-based climate disclosure is associated with suspected stock market manipulation. Using dataset of China's A-share listed firms from 2010 to 2021, we construct a firm-level measure of reported climate disclosure from annual reports and a suspected manipulation count from opening-price, c...
Yong-Jian Huang, En-En Meng, Yu-Cheng Qian et al.· Journal of Environmental Man...· 1 citation
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