how ibes is used
ibes aims to be a concise centralized system to aid in decision making about securities it allows for access to a broader consensus estimate rather than relying on the narrow judgments that can be made from day to day as analysts publish their reports ibes can be used in a variety of ways forecast models for earnings per share results for instance can be created using ibes as a benchmark the database also is used in accounting research ibes spinoffsthomson reuters has other distinct databases based on ibes for example ibes guidance data and earnings estimates are available to academics at the wharton school of the university of pennsylvania to review and evaluate expectations for companies 4 an ibes historical database is used to compare and test investment theories the ibes is one of a number of databases used by money managers and investors the center for research on security prices has developed databases for stock prices including daily and monthly market information research and historical data advantages and disadvantages of ibesibes aggregates earnings estimates from a wide array of sell side analysts including those from investment banks brokerage firms and other financial institutions this extensive coverage spans various industries sectors and geographic regions meaning there s a lot of different information available for many different purposes ibes consolidates analysts earnings estimates into a single database this saves investors time by acting as a centralized platform for getting forecasts and relevant information it also provides stability and accessibility into historical earnings estimates and revisions ibes updates its database regularly with the latest earnings estimates ensuring that investors have access to up to date information you can consider ibes data to be near real time not only will you have quick access to information ibes implements validation checks data cleaning procedures and verification of credentials to make sure any input data is correct ibes relies on earnings estimates provided by sell side analysts it s important to note that these folks may have biases or conflicts of interest as they may be incentivized to maintain relationships with the companies they cover or their employers this the data fed into ibes may be optimistic or pessimistic estimates that do not accurately reflect underlying fundamentals the specific methodologies used by individual analysts to formulate their forecasts may not always be transparent this lack of transparency can make it difficult for investors to assess the reliability and credibility of the estimates plus even though there are data checks ibes data may still be subject to errors or mistakes while ibes updates its database regularly there may still be delays in reflecting analysts revisions to earnings estimates in an industry where everyone is fighting for the same information having small lags in data accessibility may be detrimental in addition ibes may have limited coverage for smaller companies or companies in niche industries you may not always have access to the specific information you re looking for wide analyst coverage for diverse industriessimplifies research with centralized standardized dataaccess to historical trends aids forecast evaluationprovides timely updates for informed decisionsensures data accuracy through quality controlanalyst biases influence forecast accuracylack of transparency in forecasting methodologiesestimates prone to errors and variabilitypotential delays in reflecting revisionslimited coverage for smaller companies niche industries