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The Bias Analysis of Oil and Gas Companies’ Credit Ratings Based on Textual Risk Disclosures

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  • Lu Wei

    (School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, China)

  • Chen Han

    (School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, China)

  • Yinhong Yao

    (School of Management and Engineering, Capital University of Economics and Business, Beijing 100070, China)

Abstract

Credit rating bias would affect the capital funding of oil and gas companies, and thus influence the development of the whole economy. Credit rating bias has been mostly analyzed based on different quantitative data sources, and inconsistent results have been obtained. This study first analyzes credit rating bias from the perspective of qualitative textual risk disclosures. By comparing the external credit rating with the internal risk perception expressed in the textual risk disclosures of Form 10-K filings, we can study the consistency of risk assessment of the company by the company’s management and the third-party rating agency. To be specific, four internal textual risk measures and one external risk measure are constructed to quantify the internal risk perception and external risk assessment on oil and gas companies. Then, Spearman’s rho is applied to measure the direction and magnitude of credit rating bias. In the experiment, based on the 357 samples of 174 U.S. oil and gas companies, ranging from 2009 to 2018, we find that the credit ratings mostly overestimate the internal risks perceived by the company managers, and the bias is becoming larger with the credit ratings downgraded from AAA to D.

Suggested Citation

  • Lu Wei & Chen Han & Yinhong Yao, 2022. "The Bias Analysis of Oil and Gas Companies’ Credit Ratings Based on Textual Risk Disclosures," Energies, MDPI, vol. 15(7), pages 1-12, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2390-:d:778908
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    References listed on IDEAS

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