{
  "abstract": "Forecasts of imbalance prices are essential for participants in short-term electricity markets. This study proposes an approach to integrate trade data from continuous intraday markets into forecasting methods and considers the production of both parametric and non-parametric density forecasts. Extensive feature engineering is required to convert irregular trade data into a suitable tabular structure. Our findings demonstrate that intraday trade data can enhance state-of-the-art forecasts based on quantile regression and LASSO. We also propose a model based on Natural Gradient Boosting to predict the means and variances of a bimodal Gaussian mixture, which offers both improved predictive performance and computational efficiency. In a case study based on multiple years of data from Great Britain, our proposed approach reduced the Pinball Loss of state-of-the-art models by 20% for forecasts made 30 seconds before gate closure, and by 7.5% for forecasts made one hour before delivery.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2611.03331",
  "author_total": 5,
  "authors": [
    {
      "name": "Klimis Stylpnopoulos"
    },
    {
      "name": "Jethro Browell"
    },
    {
      "name": "Janine Illian"
    },
    {
      "name": "Ciaran Gilbert"
    },
    {
      "name": "Wayne Jones"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ahqfkhx28n019.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2611.03331",
  "fulltext_url": null,
  "id": "ahqfkhx28n019",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2611.03331",
  "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.AP"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2611.03331",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-02",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/ahqfkhx28n019.ris",
  "sources": [
    {
      "first_seen": "2026-11-03T12:21:21Z",
      "native_id": "2611.03331",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2611.03331"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Leveraging Continuous Trade Data for Intraday Imbalance Price Forecasting",
  "title_text": "Leveraging Continuous Trade Data for Intraday Imbalance Price Forecasting",
  "type": "preprint",
  "updated_at": "2026-11-05T15:20:35Z",
  "url": "https://research.draconitic.com/paper/ahqfkhx28n019",
  "venue": "arXiv",
  "versions": []
}