IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v80y2019icp452-460.html
   My bibliography  Save this article

Developing a hierarchical system for energy corporate risk factors based on textual risk disclosures

Author

Listed:
  • Wei, Lu
  • Li, Guowen
  • Zhu, Xiaoqian
  • Sun, Xiaolei
  • Li, Jianping

Abstract

Selecting risk factors is essential for measuring energy corporate risk. However, the comprehensive identification of energy corporate risk factors is still a difficult issue. This paper innovatively uses the text mining approach to comprehensively identify energy corporate risk factors from textual risk disclosures reported in financial statements. Based on 131,755 risk factor headings from 3707 Form 10-K filings from 840 U.S. energy corporations over the period 2010–2016, 66 types of risk factors that affect energy corporate risks are identified. Furthermore, we develop a hierarchical system for 66 energy corporate risk factors by dividing energy corporations into nine subsectors. Thus, the hierarchical energy corporate risk factor system provides fundamental support for further energy corporate risk measurement. Researchers can comprehensively and effectively select risk factors in measuring risks of the entire energy industry or each of nine energy subsectors.

Suggested Citation

  • Wei, Lu & Li, Guowen & Zhu, Xiaoqian & Sun, Xiaolei & Li, Jianping, 2019. "Developing a hierarchical system for energy corporate risk factors based on textual risk disclosures," Energy Economics, Elsevier, vol. 80(C), pages 452-460.
    • Handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:452-460
    DOI: 10.1016/j.eneco.2019.01.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319300350
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2019.01.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sadorsky, Perry, 2012. "Modeling renewable energy company risk," Energy Policy, Elsevier, vol. 40(C), pages 39-48.
    2. Boyer, M. Martin & Filion, Didier, 2007. "Common and fundamental factors in stock returns of Canadian oil and gas companies," Energy Economics, Elsevier, vol. 29(3), pages 428-453, May.
    3. Bianconi, Marcelo & Yoshino, Joe A., 2014. "Risk factors and value at risk in publicly traded companies of the nonrenewable energy sector," Energy Economics, Elsevier, vol. 45(C), pages 19-32.
    4. Ramos, Sofia B. & Veiga, Helena, 2011. "Risk factors in oil and gas industry returns: International evidence," Energy Economics, Elsevier, vol. 33(3), pages 525-542, May.
    5. 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.
    6. Gupta, Kartick, 2016. "Oil price shocks, competition, and oil & gas stock returns — Global evidence," Energy Economics, Elsevier, vol. 57(C), pages 140-153.
    7. Sanusi, Muhammad Surajo & Ahmad, Farooq, 2016. "Modelling oil and gas stock returns using multi factor asset pricing model including oil price exposure," Finance Research Letters, Elsevier, vol. 18(C), pages 89-99.
    8. Sunil K. Mohanty & Mohan Nandha, 2011. "Oil Risk Exposure: The Case of the U.S. Oil and Gas Sector," The Financial Review, Eastern Finance Association, vol. 46(1), pages 165-191, February.
    9. Baul, T.K. & Datta, D. & Alam, A., 2018. "A comparative study on household level energy consumption and related emissions from renewable (biomass) and non-renewable energy sources in Bangladesh," Energy Policy, Elsevier, vol. 114(C), pages 598-608.
    10. Miller, Gregory S., 2017. "Discussion of “the evolution of 10-K textual disclosure: Evidence from Latent Dirichlet Allocation”," Journal of Accounting and Economics, Elsevier, vol. 64(2), pages 246-252.
    11. Ellabban, Omar & Abu-Rub, Haitham & Blaabjerg, Frede, 2014. "Renewable energy resources: Current status, future prospects and their enabling technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 748-764.
    12. Ji, Qiang & Bouri, Elie & Roubaud, David, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 1-12.
    13. Sun, Xiaolei & Liu, Chang & Chen, Xiuwen & Li, Jianping, 2017. "Modeling systemic risk of crude oil imports: Case of China’s global oil supply chain," Energy, Elsevier, vol. 121(C), pages 449-465.
    14. Yang Bao & Anindya Datta, 2014. "Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures," Management Science, INFORMS, vol. 60(6), pages 1371-1391, June.
    15. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    16. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    17. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    18. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    19. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Blum, Avinoam & Raviv, Alon, 2023. "The effects of the financial crisis and Basel III on banks’ risk disclosure: A textual analysis," Finance Research Letters, Elsevier, vol. 53(C).
    2. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
    3. Wang, Jun & Sun, Xiaolei & Li, Jianping, 2020. "How do sovereign credit default swap spreads behave under extreme oil price movements? Evidence from G7 and BRICS countries," Finance Research Letters, Elsevier, vol. 34(C).
    4. Li, Jianping & Li, Guowen & Liu, Mingxi & Zhu, Xiaoqian & Wei, Lu, 2022. "A novel text-based framework for forecasting agricultural futures using massive online news headlines," International Journal of Forecasting, Elsevier, vol. 38(1), pages 35-50.
    5. Zhu, Xiaoqian & Wei, Lu & Li, Jianping, 2021. "A two-stage general approach to aggregate multiple bank risks," Finance Research Letters, Elsevier, vol. 40(C).
    6. Li, Guowen & Jing, Zhongbo & Li, Jingyu & Feng, Yuyao, 2023. "Drivers of risk correlation among financial institutions: A study based on a textual risk disclosure perspective," Economic Modelling, Elsevier, vol. 128(C).
    7. Li, Jianping & Li, Jingyu & Zhu, Xiaoqian & Yao, Yinhong & Casu, Barbara, 2020. "Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S," International Review of Financial Analysis, Elsevier, vol. 71(C).
    8. Liu, Mingxi & Li, Guowen & Li, Jianping & Zhu, Xiaoqian & Yao, Yinhong, 2021. "Forecasting the price of Bitcoin using deep learning," Finance Research Letters, Elsevier, vol. 40(C).
    9. 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.
    10. Ji, Qiang & Li, Jianping & Sun, Xiaolei, 2019. "Measuring the interdependence between investor sentiment and crude oil returns: New evidence from the CFTC's disaggregated reports," Finance Research Letters, Elsevier, vol. 30(C), pages 420-425.
    11. Wei, Lu & Miao, Xiyuan & Jing, Haozhe & Liu, Zhidong & Xie, Zezhong, 2023. "Bank risk aggregation based on the triple perspectives of bank managers, credit raters, and financial analysts," Finance Research Letters, Elsevier, vol. 57(C).
    12. Li, Jianping & Feng, Yuyao & Li, Guowen & Sun, Xiaolei, 2020. "Tourism companies' risk exposures on text disclosure," Annals of Tourism Research, Elsevier, vol. 84(C).
    13. Wei, Lu & Jing, Haozhe & Huang, Jie & Deng, Yuqi & Jing, Zhongbo, 2023. "Do textual risk disclosures reveal corporate risk? Evidence from U.S. fintech corporations," Economic Modelling, Elsevier, vol. 127(C).
    14. Düsterhöft, Maximilian & Schiemann, Frank & Walther, Thomas, 2023. "Let’s talk about risk! Stock market effects of risk disclosure for European energy utilities," Energy Economics, Elsevier, vol. 125(C).
    15. Wei, Lu & Li, Guowen & Li, Jianping & Zhu, Xiaoqian, 2019. "Bank risk aggregation with forward-looking textual risk disclosures," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    16. Li, Jingyu & Li, Jianping & Zhu, Xiaoqian, 2020. "Risk dependence between energy corporations: A text-based measurement approach," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 33-46.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Misund, Bard & Mohn, Klaus, 2014. "Exploration Risk in Oil & Gas Shareholder Returns," UiS Working Papers in Economics and Finance 2014/4, University of Stavanger.
    2. Mohmmad Enamul Hoque & Soo Wah Low & Mohd Azlan Shah Zaidi, 2020. "Do Oil and Gas Risk Factors Matter in the Malaysian Oil and Gas Industry? A Fama-MacBeth Two Stage Panel Regression Approach," Energies, MDPI, vol. 13(5), pages 1-15, March.
    3. Ben Ammar, Semir & Eling, Martin, 2015. "Common risk factors of infrastructure investments," Energy Economics, Elsevier, vol. 49(C), pages 257-273.
    4. Li, Jingyu & Li, Jianping & Zhu, Xiaoqian, 2020. "Risk dependence between energy corporations: A text-based measurement approach," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 33-46.
    5. Stavros Degiannakis & George Filis & Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, , vol. 39(5), pages 85-130, September.
    6. Scott Alan Carson, 2022. "Long-Term Daily Equity Returns Across Sectors of the Oil and Gas Industry, 2000–2019," Journal of Industry, Competition and Trade, Springer, vol. 22(1), pages 125-143, March.
    7. Daniel Wurstbauer & Stephan Lang & Christoph Rothballer & Wolfgang Schaefers, 2016. "Can common risk factors explain infrastructure equity returns? Evidence from European capital markets," Journal of Property Research, Taylor & Francis Journals, vol. 33(2), pages 97-120, April.
    8. Sunil K. Mohanty & Stein Frydenberg & Petter Osmundsen & Sjur Westgaard & Christian Skjøld, 2023. "Risk factors in stock returns of U.S. oil and gas companies: evidence from quantile regression analysis," Review of Quantitative Finance and Accounting, Springer, vol. 60(2), pages 715-746, February.
    9. Mohammad Enamul Hoque & Soo-Wah Low & Mohd Azlan Shah Zaidi, 2020. "The Effects of Oil and Gas Risk Factors on Malaysian Oil and Gas Stock Returns: Do They Vary?," Energies, MDPI, vol. 13(15), pages 1-22, July.
    10. Mohammad Enamul Hoque & Soo-Wah Low & Mohd Azlan Shah Zaidi & Lain-Tze Tee & Noor Azlan Ghazali, 2023. "Asymmetric and Lag Effects of Industry Risk Factors on the Malaysian Oil and Gas Stocks," SAGE Open, , vol. 13(3), pages 21582440231, July.
    11. Szczygielski, Jan Jakub & Brzeszczyński, Janusz & Charteris, Ailie & Bwanya, Princess Rutendo, 2022. "The COVID-19 storm and the energy sector: The impact and role of uncertainty," Energy Economics, Elsevier, vol. 109(C).
    12. Mohammad Enamul Hoque & Soo-Wah Low, 2020. "Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework," Mathematics, MDPI, vol. 8(10), pages 1-28, October.
    13. Carson, Scott Alan, 2020. "United States oil and gas stock returns with multi-factor pricing models: 2008–2018," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    14. Samir Cedic & Alwan Mahmoud & Matteo Manera & Gazi Salah Uddin, 2021. "Information Diffusion and Spillover Dynamics in Renewable Energy Markets," Working Papers 2021.10, Fondazione Eni Enrico Mattei.
    15. Liu, De-Chih & Liu, Chih-Yun, 2016. "The source of stock return fluctuation in Taiwan," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 77-88.
    16. Serkan Yilmaz Kandir & Ahmet Erismis & Ilhan Ozturk, 2015. "Investigating Exchange Rate Exposure of Energy Firms: Evidence from Turkey," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(6), pages 729-743.
    17. Mohamad Husam Helmi & A. Nazif Catik & Begum Yurteri Kosedagli & Gul Serife Huyuguzel Kisla & Coskun Akdeniz, 2023. "The Effects of Energy Prices on Oil-Gas Sectoral Stock Returns for BRIC Countries: Evidence from Space State Models," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 430-440, November.
    18. Zhu, Zhaobo & Ji, Qiang & Sun, Licheng & Zhai, Pengxiang, 2020. "Oil price shocks, investor sentiment, and asset pricing anomalies in the oil and gas industry," International Review of Financial Analysis, Elsevier, vol. 70(C).
    19. Liu, Jingzhen & Kemp, Alexander, 2019. "Forecasting the sign of U.S. oil and gas industry stock index excess returns employing macroeconomic variables," Energy Economics, Elsevier, vol. 81(C), pages 672-686.
    20. Düsterhöft, Maximilian & Schiemann, Frank & Walther, Thomas, 2023. "Let’s talk about risk! Stock market effects of risk disclosure for European energy utilities," Energy Economics, Elsevier, vol. 125(C).

    More about this item

    Keywords

    Risk management; Energy industry; Risk factor; Text mining; Form 10-K;
    All these keywords.

    JEL classification:

    • P28 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Natural Resources; Environment
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:452-460. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.