{
  "abstract": "ESG ratings are noisy measurements and may also be exposed to systematic credibility concerns. We study an ambiguity-averse insurer that chooses proportional reinsurance and green and brown stock positions while learning a hidden green-quality factor from stock returns and an ESG rating signal. Signal volatility represents ordinary rating uncertainty. A worst-case distortion of the rating innovation represents ambiguity about the observation model, whereas a separate out-of-model drift gtrue is used only in stress tests for systematic rating bias. This distinction prevents robust-control ambiguity from being interpreted as observed greenwashing itself. We derive the reference Kalman–Bucy filter and the separated robust control problem. Shared stock-return shocks produce a mixed wealth-belief derivative and a filtering-hedging demand. Under CARA utility, the value function is exponential-quadratic, stock feedback follows a Riccati-type system, and retention is projected onto q∈[0,1]. The verification result is conditional on explicit admissibility and integrability conditions. Primary numerical experiments with illustrative parameters identify the model mechanisms but do not constitute empirical calibration. Independent numerical checks add Monte Carlo intervals, static and insurance-only benchmarks, original-scale plots, and a 40-design parameter-uncertainty analysis. The learning-strategy intervals overlap substantially, and rating-innovation ambiguity effects are small in CE and warning probability. Tail-risk changes are more directionally consistent across the tested parameter region, but their magnitudes remain small. The numerical evidence therefore supports mechanism existence and conditional downside sensitivity, not universal or quantitatively calibrated economic relevance.",
  "abstract_shown": true,
  "affiliations": [
    "School of Mathematics and Statistics, Zhaotong University, Zhaotong, Yunnan, China.",
    "School of Mathematics and Statistics, Leshan Normal University, Leshan, Sichuan, China."
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jing Fu"
    },
    {
      "affs": [
        0
      ],
      "name": "Guiling Zhu"
    },
    {
      "affs": [
        1
      ],
      "name": "Guoyong Zhou",
      "orcid": "0000-0003-1785-1322"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ckap8x56b7fkf.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0354616",
  "fulltext_url": "https://europepmc.org/articles/PMC13726995",
  "id": "ckap8x56b7fkf",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0354616",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Biology and Life Sciences"
    ],
    [
      "heading",
      "Brownian Motion"
    ],
    [
      "heading",
      "Cell Biology"
    ],
    [
      "heading",
      "Cell Signaling"
    ],
    [
      "heading",
      "Classical Mechanics"
    ],
    [
      "heading",
      "Computer and Information Sciences"
    ],
    [
      "heading",
      "Continuum Mechanics"
    ],
    [
      "heading",
      "Control Engineering"
    ],
    [
      "heading",
      "Control Theory"
    ],
    [
      "heading",
      "Economics"
    ],
    [
      "heading",
      "Engineering and Technology"
    ],
    [
      "heading",
      "Finance"
    ],
    [
      "heading",
      "Financial Markets"
    ],
    [
      "heading",
      "Fluid Dynamics"
    ],
    [
      "heading",
      "Fluid Mechanics"
    ],
    [
      "heading",
      "Industrial Engineering"
    ],
    [
      "heading",
      "Insurance"
    ],
    [
      "heading",
      "Management Engineering"
    ],
    [
      "heading",
      "Mathematical and statistical techniques"
    ],
    [
      "heading",
      "Mathematics"
    ],
    [
      "heading",
      "Monte Carlo method"
    ],
    [
      "heading",
      "Physical Sciences"
    ],
    [
      "heading",
      "Physical sciences"
    ],
    [
      "heading",
      "Physics"
    ],
    [
      "heading",
      "Probability Theory"
    ],
    [
      "heading",
      "Research Article"
    ],
    [
      "heading",
      "Research and analysis methods"
    ],
    [
      "heading",
      "Risk Management"
    ],
    [
      "heading",
      "Signal Transduction"
    ],
    [
      "heading",
      "Signaling Cascades"
    ],
    [
      "heading",
      "Social Sciences"
    ],
    [
      "heading",
      "Statistical methods"
    ],
    [
      "heading",
      "Statistics"
    ],
    [
      "heading",
      "Stochastic Processes"
    ],
    [
      "heading",
      "Stress Signaling Cascade"
    ],
    [
      "heading",
      "Systems Science"
    ],
    [
      "openalex",
      "2002|Insurance and Financial Risk Management"
    ],
    [
      "plos",
      "/Biology and life sciences/Cell biology/Signal transduction/Cell signaling/Signaling cascades/Stress signaling cascade"
    ],
    [
      "plos",
      "/Computer and information sciences/Systems science/Control theory"
    ],
    [
      "plos",
      "/Engineering and technology/Industrial engineering/Control engineering/Control theory"
    ],
    [
      "plos",
      "/Engineering and technology/Management engineering/Risk management/Insurance"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Probability theory"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Probability theory/Stochastic processes/Brownian motion"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Monte Carlo method"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Systems science/Control theory"
    ],
    [
      "plos",
      "/Physical sciences/Physics/Classical mechanics/Continuum mechanics/Fluid mechanics/Fluid dynamics/Brownian motion"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Monte Carlo method"
    ],
    [
      "plos",
      "/Social sciences/Economics/Finance"
    ],
    [
      "plos",
      "/Social sciences/Economics/Financial markets"
    ]
  ],
  "openalex": "W7225097082",
  "pdf_url": "https://europepmc.org/articles/PMC13726995?pdf=render",
  "pmcid": "PMC13726995",
  "pmid": "42970604",
  "published": "2026-11-02",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/ckap8x56b7fkf.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T12:20:16Z",
      "native_id": "10.1371/journal.pone.0354616",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0354616"
    },
    {
      "first_seen": "2026-11-04T15:20:43Z",
      "native_id": "MED:42970604",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42970604"
    },
    {
      "first_seen": "2026-11-05T12:23:12Z",
      "native_id": "PMC13726995",
      "source": "pmc",
      "url": "https://doi.org/10.1371/journal.pone.0354616"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:cell biology",
      "subfield": "cell-biology"
    },
    {
      "field": "mathematics",
      "origin": "plos:probability theory",
      "subfield": "probability"
    },
    {
      "field": "mathematics",
      "origin": "plos:statistical methods",
      "subfield": "statistics"
    },
    {
      "field": "physics",
      "origin": "heading:Fluid Dynamics",
      "subfield": "fluid-dynamics"
    }
  ],
  "title": "Robust optimal reinsurance and ESG investment under rating-innovation ambiguity and ESG rating uncertainty",
  "title_text": "Robust optimal reinsurance and ESG investment under rating-innovation ambiguity and ESG rating uncertainty",
  "type": "peer-reviewed",
  "updated_at": "2026-11-06T12:22:48Z",
  "url": "https://research.draconitic.com/paper/ckap8x56b7fkf",
  "venue": "PLOS One",
  "versions": []
}