{
  "abstract": "Motivated by evidence that the tails of economic and financial time series need not be stable over time, we develop a framework for studying time-varying tails. We model the extreme value index as a smooth function of time in the locally stationary framework of Zhou and Wu (2009). We estimate it by a ratio-form kernel Hill estimator in which a single intermediate quantile thresholds the whole local window. We establish consistency and asymptotic normality, and we construct uniform confi- dence bands. We also propose a consistent test of tail stability under extremal clustering. Combined with the Weissman extrapolation method, the estimator of the extreme value index yields time- varying extreme Value-at-Risk and Expected Shortfall. In an empirical application, we find the tail of daily loss of S&P 500 is compatible with a constant shape, whereas that of volatility-filtered loss varies significantly.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.06005",
  "author_total": 2,
  "authors": [
    {
      "name": "Shuo Li"
    },
    {
      "name": "Liuhua Peng"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3shgz9cwb06gf.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.06005",
  "fulltext_url": null,
  "id": "3shgz9cwb06gf",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.06005",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.ME"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.06005",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3shgz9cwb06gf.ris",
  "sources": [
    {
      "first_seen": "2026-11-05T15:21:06Z",
      "native_id": "2611.06005",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.06005"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ME",
      "subfield": "statistics"
    }
  ],
  "title": "Time-Varying Tails: Estimation, Inference, and Risk Measurement",
  "title_text": "Time-Varying Tails: Estimation, Inference, and Risk Measurement",
  "type": "preprint",
  "updated_at": "2026-11-09T00:20:32Z",
  "url": "https://research.draconitic.com/paper/3shgz9cwb06gf",
  "venue": "arXiv",
  "versions": []
}