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Form 10-Q Itemization

Author

Listed:
  • Yanci Zhang
  • Tianming Du
  • Yujie Sun
  • Lawrence Donohue
  • Rui Dai

Abstract

The quarterly financial statement, or Form 10-Q, is one of the most frequently required filings for US public companies to disclose financial and other important business information. Due to the massive volume of 10-Q filings and the enormous variations in the reporting format, it has been a long-standing challenge to retrieve item-specific information from 10-Q filings that lack machine-readable hierarchy. This paper presents a solution for itemizing 10-Q files by complementing a rule-based algorithm with a Convolutional Neural Network (CNN) image classifier. This solution demonstrates a pipeline that can be generalized to a rapid data retrieval solution among a large volume of textual data using only typographic items. The extracted textual data can be used as unlabeled content-specific data to train transformer models (e.g., BERT) or fit into various field-focus natural language processing (NLP) applications.

Suggested Citation

  • Yanci Zhang & Tianming Du & Yujie Sun & Lawrence Donohue & Rui Dai, 2021. "Form 10-Q Itemization," Papers 2104.11783, arXiv.org, revised Oct 2021.
    • Handle: RePEc:arx:papers:2104.11783
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    File URL: http://arxiv.org/pdf/2104.11783
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    References listed on IDEAS

    as
    1. Dyer, Travis & Lang, Mark & Stice-Lawrence, Lorien, 2017. "The evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation," Journal of Accounting and Economics, Elsevier, vol. 64(2), pages 221-245.
    2. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
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    Cited by:

    1. Yanci Zhang & Yutong Lu & Haitao Mao & Jiawei Huang & Cien Zhang & Xinyi Li & Rui Dai, 2023. "Company Competition Graph," Papers 2304.00323, arXiv.org.
    2. Yanci Zhang & Mengjia Xia & Mingyang Li & Haitao Mao & Yutong Lu & Yupeng Lan & Jinlin Ye & Rui Dai, 2023. "Form 10-K Itemization," Papers 2303.04688, arXiv.org.
    3. Liao Zhu & Haoxuan Wu & Martin T. Wells, 2021. "A News-based Machine Learning Model for Adaptive Asset Pricing," Papers 2106.07103, arXiv.org.
    4. Liao Zhu, 2021. "The Adaptive Multi-Factor Model and the Financial Market," Papers 2107.14410, arXiv.org, revised Aug 2021.
    5. Liao Zhu & Ningning Sun & Martin T. Wells, 2022. "Clustering Structure of Microstructure Measures," Applied Economics and Finance, Redfame publishing, vol. 9(1), pages 85-95, December.

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