Earning Calendar API provides detailed and reliable information on the financial results of listed companies, including publication dates, earnings per share (EPS), and revenue figures. Each entry provides data on both analysts' expectations and actual reported results, allowing users to directly compare projections with actual results. This information is essential for investors, financial analysts, fund managers, and financial application developers who need to integrate accurate, real-time data.
The API not only offers EPS and revenue figures, but also organizes results by quarter and by company, facilitating historical visualization and the identification of financial trends. Users can filter information by date, company ticker, or revenue range, ensuring quick and efficient access to the most relevant data. In addition, our API supports standardized JSON formats, simplifying integration into dashboards, analytics systems, and investment applications.
In short, this API is the ideal tool for monitoring, analyzing, and leveraging company financial results, facilitating understanding of market trends and improving efficiency in financial planning and informed investing.
Get financial results, EPS, and actual versus estimated revenue dates for companies, facilitating stock market performance analysis and accurate investment decisions.
Earning reports - Endpoint Features
| Object | Description |
|---|---|
ticker |
[Required] Indicate a ticker |
show_upcoming |
Optional Indicates whether you want to obtain upcoming results publication dates (true or false). |
limit |
Optional Indicate a limit (between 1 and 100) |
[{"date": "2026-01-28", "ticker": "MSFT", "actual_eps": 4.14, "estimated_eps": 3.9, "actual_revenue": 81273000000, "estimated_revenue": 80308701686, "earnings_call_timestamp": 1769639400, "earnings_timing": "after_market"}, {"date": "2025-10-29", "ticker": "MSFT", "actual_eps": 4.13, "estimated_eps": 3.67, "actual_revenue": 77673000000, "estimated_revenue": 75494678452, "earnings_call_timestamp": 1761773400, "earnings_timing": "after_market"}, {"date": "2025-07-30", "ticker": "MSFT", "actual_eps": 3.65, "estimated_eps": 3.37, "actual_revenue": 76441000000, "estimated_revenue": 73926767276, "earnings_call_timestamp": 1753911000, "earnings_timing": "after_market"}]
curl --location --request GET 'https://zylalabs.com/api/9553/earning+calendar+api/17678/earning+reports?ticker=MSFT' --header 'Authorization: Bearer YOUR_API_KEY'
| Header | Description |
|---|---|
Authorization
|
[Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed. |
No long-term commitment. Upgrade, downgrade, or cancel anytime. Free Trial includes up to 50 requests.
The Earning Calendar API returns financial results for publicly traded companies, including earnings per share (EPS), actual versus estimated revenue, and publication dates for earnings reports. This data is crucial for analyzing stock market performance.
Key fields in the response data include company ticker, earnings report date, EPS, estimated revenue, actual revenue, and the difference between estimated and actual figures. These fields enable detailed financial analysis.
The response data is organized in a structured JSON format, with each entry representing a company's earnings report. This includes nested fields for EPS and revenue figures, making it easy to parse and analyze.
Users can customize their data requests using parameters such as date range, company ticker, and revenue range. This allows for targeted queries to retrieve specific financial data relevant to their analysis.
The endpoint provides information on earnings dates, EPS, estimated and actual revenue figures, and comparisons between estimates and actual results. This comprehensive data supports in-depth financial analysis.
Data accuracy is maintained through rigorous sourcing from reliable financial databases and regular updates. Quality checks are implemented to ensure that the information reflects the latest financial results.
Typical use cases include financial analysis, investment decision-making, portfolio management, and market trend analysis. Investors and analysts use this data to evaluate company performance and make informed decisions.
Users can utilize the returned data by integrating it into financial dashboards, analytics systems, or investment applications. The structured format allows for easy visualization and comparison of financial metrics over time.
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