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.

Process

  1. Benzinga Analysts start with GAAP earnings and identify non-comparable items which make the results unusable.
  2. Call sell side analysts when there are discrepancies on the comparable earnings figures (1,200 calls per quarter).
  3. Update API with Wall Street’s most accurate figures.

Earnings suite covers the Wilshire 5000 + 1000 additional US equities

Data field descriptions

IDUnique ID of the output
dateDatestamp
date_confirmedIf predicted date has been confirmed by company. 0 = No, 1 = Yes
timeTimestamp of the announcement HH:MM:SS format
isinISIN identifier
tickerTicker symbol
exchangeExchange the security is traded on
nameCompany name of the security
periodFiscal period being reported
period_yearFiscal year being reported
epsEarnings per share for current quarter
eps_estAnalyst prediction for the upcoming announcement
eps_priorEPS reported for the same quarter a year prior
revenueRevenue for current quarter
revenue_estAnalyst prediction for the upcoming announcement
revenue_priorRevenue reporter for the same quarter a year prior
revenue_surpriseDifference between the prediction and actual figure reported
revenue_surprise_percentDifference in percentage between prediction and actual figure
importanceImportance of the action (scale of 0-5) 0 = least important
updatedLast 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.