Benzinga has stringent processes to collect and curate the highest quality earnings data, which is consistently considered the cleanest in the market. Benzinga follows a three-step method to ensure quality, accuracy, and timeliness.
- BZ Analysts start with GAAP earnings and identify non-comparable items which make the results unusable.
- Call sell side analysts when there are discrepancies on the comparable earnings figures (1,200 calls per quarter).
- Update API with Wall Street’s most accurate figures.
Earnings suite covers the Wilshire 5000 + 1000 additional US equities
Data field descriptions
|ID||Unique ID of the output|
|date_confirmed||If predicted date has been confirmed by company. 0 = No, 1 = Yes|
|time||Timestamp of the announcement HH:MM:SS format|
|exchange||Exchange the security is traded on|
|name||Company name of the security|
|period||Fiscal period being reported|
|period_year||Fiscal year being reported|
|eps||Earnings per share for current quarter|
|eps_est||Analyst prediction for the upcoming announcement|
|eps_prior||EPS reported for the same quarter a year prior|
|revenue||Revenue for current quarter|
|revenue_est||Analyst prediction for the upcoming announcement|
|revenue_prior||Revenue reporter for the same quarter a year prior|
|revenue_surprise||Difference between the prediction and actual figure reported|
|revenue_surprise_percent||Difference in percentage between prediction and actual figure|
|importance||Importance of the action (scale of 0-5) 0 = least important|
|updated||Last updated timestamp (UNIX)|
Benzinga’s data samples are intended to provide a data sample large enough for testing data quality and application for the financial markets. These sample files demonstrate a sample of the formats and content that can be delivered.
Please refer to docs.benzinga.io for all your API integration needs, including parameter queries and a look at our entire offerings.