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While existing studies mostly examine firm-level effects, their market-level implications in multi-agent systems remain insufficiently explored. This paper develops a dual-market dynamic ESG fund model, integrating agent-based simulation with empirical game-theoretic analysis, to study how upgrade costs, investor valuation preferences, and disclosure regimes jointly shape firms\u2019 green transition incentives in the EU and China. The results show that both transition costs and valuation gaps strongly influence strategic upgrading behaviour and equilibrium outcomes: Strict disclosure sharpens differentiation but may suppress upgrading due to high costs; lax disclosure facilitates initial transitions by polluting firms; and hybrid disclosure, combining lax and strict phases, generates stronger incentives across different firm types. Cross-market comparison further indicates that the EU\u2019s mature regulatory environment is better suited to strict disclosure, whereas China\u2019s emerging market benefits more from a lax form to accelerate early-stage transitions. This study provides a reference for regulators in selecting appropriate disclosure forms at different levels of market maturity and offers methodological support for the sustainable development of green finance markets.<\/jats:p>","DOI":"10.1007\/s10458-026-09734-y","type":"journal-article","created":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T09:02:50Z","timestamp":1770454970000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Green disclosure policies and market dynamics: evidence from agent-based ESG models"],"prefix":"10.1007","volume":"40","author":[{"given":"Lingxiao","family":"Zhao","sequence":"first","affiliation":[]},{"given":"Maria","family":"Polukarov","sequence":"additional","affiliation":[]},{"given":"Carmine","family":"Ventre","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,2,7]]},"reference":[{"key":"9734_CR1","unstructured":"World Bank Group (2019). 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