This website provides information on LSEG Guidance Reports (GR) data and research.
What are LSEG Guidance Reports (GR)?
Guidance Reports (GR) are produced by LSEG and contain raw as-reported corporate issued guidance. GR content is sourced from company public disclosures, such as conference calls, press releases, analyst days, and industry conferences. Academic scholars can obtain GR data via LSEG Workspace with LSEG license.
The paper below provides an overview of the GR data and discusses directions for future research:
Mayew, W. J., Pinto, J., & Wu, X. (2026). "On the Usefulness of Guidance Reports."
Review of Accounting Studies, Accepted
Available at SSRN: link
Abstract:
We extract and describe corporate-issued guidance contained in over 23,000 LSEG Guidance Reports (GR) of S&P 1,500 firms from 2005 to 2021. Our sample contains 1.735 million GR guidance instances that span over 180 guided items and fall into three broad categories: (1) qualitative topics, (2) consolidated financial statements, and (3) other key performance indicators. We identify research opportunities arising from GR’s extensive set of guided items, as well as from the rich guidance features GR provides, including quantitative or qualitative guidance form, guidance underpinning text, disclosure channels, and source speakers. We also compare GR content to the commonly used LSEG I/B/E/S Guidance (IG) database. IG is a subset of GR covering only quantitative guidance instances for 13 guided items, which LSEG standardizes to be comparable to analyst consensus estimates. GR contains approximately 1.494 million guidance instances that fall outside of IG’s coverage. For GR instances that do overlap with the 13 IG quantitative items, only a subset is translated to IG based on LSEG cost-benefit considerations. Our findings suggest that researchers should be aware of the extent and nature of IG omissions when studying guidance. Our findings complement and update prior work suggesting that the IG database fails to fully capture management guidance and highlight how GR’s more comprehensive data coverage can advance academics’ understanding of management guidance.
If you have any questions about GR data in our paper, please feel free to contact Xiaoxi Wu (xiaoxi.wu@unibocconi.it).
Happy to help!