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Text Mining for U.S. Pension De-Risking Analysis

Author

Listed:
  • Limin Zhang

    (Department of Accounting and Information Systems, College of Business, North Dakota State University, Fargo, ND 58108, USA)

  • Ruilin Tian

    (Department of Transportation, Logistics, & Finance, College of Business, North Dakota State University, Fargo, ND 58108, USA)

  • Jun Chen

    (Department of Transportation, Logistics, & Finance, College of Business, North Dakota State University, Fargo, ND 58108, USA)

Abstract

In the past 30 years, as sponsors of defined benefit (DB) pension plans were facing more severe underfunding challenges, pension de-risking strategies have become prevalent for firms with DB plans to reduce pension-related risks. However, it remains unclear how pension de-risking activities affect firms’ performance, partially due to the lack of de-risking data. In this study, we develop a multi-phase methodology to build a de-risking database for the purpose of investigating impacts of firms’ pension risk transfer activities. We extract company filings between 1993 and 2018 from the SEC EDGAR database to identify different “de-risking” strategies that US-based companies have used. A combination of text mining, machine learning, and natural language processing methods is applied to the textual data for automated identification and classification of de-risking strategies. The contribution of this study is three-fold: (1) the design of a multi-phase methodology that identifies and extracts hidden information from a large amount of textual data; (2) the development of a comprehensive database for pension de-risking activities of US-based companies; and (3) valuable insights to companies with DB plans, pensioners, and practitioners in pension de-risking markets through empirical analysis.

Suggested Citation

  • Limin Zhang & Ruilin Tian & Jun Chen, 2022. "Text Mining for U.S. Pension De-Risking Analysis," Risks, MDPI, vol. 10(2), pages 1-18, February.
    • Handle: RePEc:gam:jrisks:v:10:y:2022:i:2:p:41-:d:749511
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    References listed on IDEAS

    as
    1. Atanasova, Christina & Hrazdil, Karel, 2010. "Why do healthy firms freeze their defined-benefit pension plans?," Global Finance Journal, Elsevier, vol. 21(3), pages 293-303.
    2. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    3. Vafeas, Nikos & Vlittis, Adamos, 2018. "Independent directors and defined benefit pension plan freezes," Journal of Corporate Finance, Elsevier, vol. 50(C), pages 505-518.
    4. Comprix, Joseph & Muller, Karl A., 2011. "Pension plan accounting estimates and the freezing of defined benefit pension plans," Journal of Accounting and Economics, Elsevier, vol. 51(1), pages 115-133.
    5. Choy, Helen & Lin, Juichia & Officer, Micah S., 2014. "Does freezing a defined benefit pension plan affect firm risk?," Journal of Accounting and Economics, Elsevier, vol. 57(1), pages 1-21.
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