IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v41y2020i5p213-238.html

Natural Gas Storage Forecasts: Is the Crowd Wiser?

Author

Listed:
  • Adrian Fernandez-Perez
  • Alexandre Garel
  • Ivan Indriawan

Abstract

This paper examines the usefulness of crowdsourced relative to professional forecasts for natural gas storage changes. We find that crowdsourced forecasts are less accurate than professional forecasts on average. We investigate possible reasons for this inferior performance and find evidence of a greater divergence of opinions and a lower incorporation of publicly available information among crowd analysts. We further show that crowdsourced consensus forecast does not influence the market’s expectation of gas storage changes beyond what is already contained in professional consensus forecast, suggesting that crowdsourced forecasts provide little new information. Overall, our results indicate that the incremental usefulness of crowdsourced forecasts for gas market stakeholders is very limited.

Suggested Citation

  • Adrian Fernandez-Perez & Alexandre Garel & Ivan Indriawan, 2020. "Natural Gas Storage Forecasts: Is the Crowd Wiser?," The Energy Journal, , vol. 41(5), pages 213-238, September.
  • Handle: RePEc:sae:enejou:v:41:y:2020:i:5:p:213-238
    DOI: 10.5547/01956574.41.5.afer
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.41.5.afer
    Download Restriction: no

    File URL: https://libkey.io/10.5547/01956574.41.5.afer?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
    ---><---

    References listed on IDEAS

    as
    1. Chen Gu & Alexander Kurov, 2018. "What drives informed trading before public releases? Evidence from natural gas inventory announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(9), pages 1079-1096, September.
    2. Pierdzioch, Christian & Rülke, Jan-Christoph, 2012. "Forecasting stock prices: Do forecasters herd?," Economics Letters, Elsevier, vol. 116(3), pages 326-329.
    3. Clement, Michael B., 1999. "Analyst forecast accuracy: Do ability, resources, and portfolio complexity matter?," Journal of Accounting and Economics, Elsevier, vol. 27(3), pages 285-303, July.
    4. Harrison Hong & Jeffrey D. Kubik & Amit Solomon, 2000. "Security Analysts' Career Concerns and Herding of Earnings Forecasts," RAND Journal of Economics, The RAND Corporation, vol. 31(1), pages 121-144, Spring.
    5. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    6. Ramnath, Sundaresh & Rock, Steve & Shane, Philip, 2008. "The financial analyst forecasting literature: A taxonomy with suggestions for further research," International Journal of Forecasting, Elsevier, vol. 24(1), pages 34-75.
    7. Ye, Shiyu & Karali, Berna, 2016. "The informational content of inventory announcements: Intraday evidence from crude oil futures market," Energy Economics, Elsevier, vol. 59(C), pages 349-364.
    8. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2017. "When no news is good news – The decrease in investor fear after the FOMC announcement," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 187-199.
    9. Scott C. Linn & Zhen Zhu, 2004. "Natural gas prices and the gas storage report: Public news and volatility in energy futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(3), pages 283-313, March.
    10. Mariassunta Giannetti & Yishay Yafeh, 2012. "Do Cultural Differences Between Contracting Parties Matter? Evidence from Syndicated Bank Loans," Management Science, INFORMS, vol. 58(2), pages 365-383, February.
    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. Bao, Te & Corgnet, Brice & Hanaki, Nobuyuki & Okada, Katsuhiko & Riyanto, Yohanes E. & Zhu, Jiahua, 2025. "Financial forecasting in the lab and the field: Qualified professionals vs. smart students," Journal of Behavioral and Experimental Finance, Elsevier, vol. 46(C).

    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. Jiao, Yawen, 2024. "Managing decision fatigue: Evidence from analysts’ earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 77(1).
    2. Andrew C. Call & Shuping Chen & Yen H. Tong, 2009. "Are analysts’ earnings forecasts more accurate when accompanied by cash flow forecasts?," Review of Accounting Studies, Springer, vol. 14(2), pages 358-391, September.
    3. Yang, Yanhua Sunny & Yung, Chris, 2024. "Do analysts distribute negative opinions earlier?," Journal of Financial Markets, Elsevier, vol. 67(C).
    4. Sean Cleary & Jonathan Jona & Gladys Lee & Joshua Shemesh, 2020. "Underlying risk preferences and analyst risk‐taking behavior," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 47(7-8), pages 949-981, July.
    5. Huang, Allen H. & Lin, An-Ping & Zang, Amy Y., 2022. "Cross-industry information sharing among colleagues and analyst research," Journal of Accounting and Economics, Elsevier, vol. 74(1).
    6. Truc (Peter) Thuc Do & Huai Zhang, 2020. "Peer Effects among Financial Analysts," Contemporary Accounting Research, John Wiley & Sons, vol. 37(1), pages 358-391, March.
    7. Suresh Kadam & Madhvi Sethi, 2026. "Mapping the Landscape of Analyst Stock Recommendations: A Bibliometric Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 17(2), pages 3740-3793, April.
    8. Brian Gibbons & Peter Iliev & Jonathan Kalodimos, 2021. "Analyst Information Acquisition via EDGAR," Management Science, INFORMS, vol. 67(2), pages 769-793, February.
    9. Wai Fong Chua & Yu Flora Kuang & Yi (Ava) Wu, 2024. "The Effect of Organizational Climate on Sell‐side Analyst Turnover and Performance," Abacus, Accounting Foundation, University of Sydney, vol. 60(1), pages 49-90, March.
    10. Sanford, Anthony, 2024. "Information content of option prices: Comparing analyst forecasts to option-based forecasts," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    11. Russell Jame & Rick Johnston & Stanimir Markov & Michael C. Wolfe, 2016. "The Value of Crowdsourced Earnings Forecasts," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 54(4), pages 1077-1110, September.
    12. Ying Cao & Rubin Hao & Yong George Yang, 2024. "National culture and analysts’ forecasting," Review of Accounting Studies, Springer, vol. 29(2), pages 1147-1191, June.
    13. Hirshleifer, David & Levi, Yaron & Lourie, Ben & Teoh, Siew Hong, 2019. "Decision fatigue and heuristic analyst forecasts," Journal of Financial Economics, Elsevier, vol. 133(1), pages 83-98.
    14. Jung, Boochun & Shane, Philip B. & Sunny Yang, Yanhua, 2012. "Do financial analysts' long-term growth forecasts matter? Evidence from stock recommendations and career outcomes," Journal of Accounting and Economics, Elsevier, vol. 53(1), pages 55-76.
    15. Xiao, Zhongyi & Horton, Joanne & Rui, Oliver & Wu, Shan, 2024. "Balancing Diversity in analyst teams: Examining the impact of informational and social Diversity on analyst team Performance," International Review of Economics & Finance, Elsevier, vol. 96(PA).
    16. Cowan, Arnold R. & Salotti, Valentina, 2020. "Anti-selective disclosure regulation and analyst forecast accuracy and usefulness," Journal of Corporate Finance, Elsevier, vol. 64(C).
    17. William J. Mayew & Nathan Y. Sharp & Mohan Venkatachalam, 2013. "Using earnings conference calls to identify analysts with superior private information," Review of Accounting Studies, Springer, vol. 18(2), pages 386-413, June.
    18. Mary J. Benner, 2010. "Securities Analysts and Incumbent Response to Radical Technological Change: Evidence from Digital Photography and Internet Telephony," Organization Science, INFORMS, vol. 21(1), pages 42-62, February.
    19. Olivier Rousse & Benoît Sévi, 2017. "Informed Trading in Oil-Futures Market," Working Papers hal-01460186, HAL.
    20. Vesa Pursiainen, 2022. "Cultural Biases in Equity Analysis," Journal of Finance, American Finance Association, vol. 77(1), pages 163-211, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:sae:enejou:v:41:y:2020:i:5:p:213-238. 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: SAGE Publications (email available below). General contact details of provider: .

    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.