# Upcoming Earnings Calendar (`gochujang/upcoming-earnings-calendar`) Actor

Get upcoming stock earnings reporting dates for the next N days. Lookup specific tickers or browse the full US earnings calendar. Returns company, report date, time of day, and EPS estimates. Powered by Yahoo Finance.

- **URL**: https://apify.com/gochujang/upcoming-earnings-calendar.md
- **Developed by:** [Hojun Lee](https://apify.com/gochujang) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 earnings date returneds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Upcoming Earnings Calendar

**Upcoming Earnings Calendar** extracts the full US stock **earnings calendar** from Yahoo Finance for any date range — including EPS estimates, report timing (BMO/AMC), and surprise data for recently reported companies. Use it to plan trades around earnings, monitor catalyst dates, or build earnings-driven screeners.

***

### Why use Upcoming Earnings Calendar?

1. **Pre-earnings positioning** — Know which stocks report this week so you can buy/sell options, hedge, or avoid holding through the event.
2. **Options strategy timing** — Earnings dates drive IV spikes. Fetch the calendar 7-14 days out to identify straddle or iron condor setups.
3. **Automated watchlist alerts** — Schedule daily runs to push upcoming earnings for your watchlist tickers to Slack, Notion, or a trading dashboard.
4. **Earnings surprise monitoring** — Scan last week's reporters for large EPS surprises (+/- 20%) that historically trigger post-earnings drift.
5. **Sector rotation** — Pull all earnings dates for a sector ETF's holdings to anticipate high-volatility windows.

***

### How to use

1. Open the actor on Apify Store and click **Try for free**.
2. Set `daysAhead` (how far out to look) and optionally paste tickers into `tickers`.
3. Optionally set `daysBack` to capture companies that reported in the past N days.
4. Click **Start**. Results are returned as a flat list of earnings events.
5. Use the **Apify Scheduler** to run this daily or weekly and push data to your webhook.

***

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `tickers` | string | `""` | Comma-separated tickers to look up (e.g. `"AAPL,MSFT,NVDA"`). Empty = full calendar. |
| `daysAhead` | number | `14` | How many days ahead to fetch (max 90) |
| `daysBack` | number | `0` | Also include companies that reported in the past N days |
| `maxResults` | number | `200` | Maximum records to return |

***

### Output

All records are structured earnings events. Example:

```json
{
  "ticker": "NVDA",
  "company": "NVIDIA Corporation",
  "report_date": "2026-05-28",
  "report_time": "AfterHoursClose",
  "eps_estimate": 0.89,
  "eps_actual": null,
  "eps_surprise_pct": null
}
```

```json
{
  "ticker": "AAPL",
  "company": "Apple Inc.",
  "report_date": "2026-05-01",
  "report_time": "AfterHoursClose",
  "eps_estimate": 1.65,
  "eps_actual": 1.83,
  "eps_surprise_pct": 10.9
}
```

#### Output fields

| Field | Type | Description |
|-------|------|-------------|
| `ticker` | string | Stock ticker symbol |
| `company` | string | Company display name |
| `report_date` | string | Earnings report date (YYYY-MM-DD) |
| `report_time` | string | `BeforeMarketOpen`, `AfterHoursClose`, `TAS`, or `TNS` |
| `eps_estimate` | float | Consensus EPS estimate (null if not available) |
| `eps_actual` | float | Reported EPS (null if not yet reported) |
| `eps_surprise_pct` | float | Surprise percentage: `(actual - estimate) / abs(estimate) * 100` |

***

### Cost estimation

**Pay-Per-Event: $0.005 per actor start + $0.005 per earnings date returned.**

| Use case | Records | Estimated cost |
|----------|---------|----------------|
| Weekly calendar (14 days) | ~150 | ~$0.75/run |
| Specific 10 tickers | 10 | ~$0.05/run |
| Monthly calendar (30 days) | ~300 | ~$1.50/run |
| Daily run on 50 watchlist tickers | 50 | ~$0.25/day |

***

### FAQ

**Does it cover pre-market (BMO) vs after-hours (AMC) reports?**
Yes — `report_time` distinguishes `BeforeMarketOpen`, `AfterHoursClose`, `TAS` (time as set), and `TNS` (time not supplied).

**Are EPS estimates always available?**
No — estimates are pulled from Yahoo Finance consensus; very small-cap stocks or newly public companies may not have analyst coverage, in which case `eps_estimate` is null.

**How far ahead can I look?**
Up to 90 days ahead. For earnings beyond 90 days, companies often haven't confirmed their date yet, so data is less reliable.

**Can I get historical earnings dates?**
Yes — set `daysBack` to pull companies that reported in the past N days. EPS actuals and surprise percentages will be populated for these.

***

### Related actors

- [Earnings Surprise Tracker](https://apify.com/gochujang/earnings-surprise-tracker) — Deep dive on historical EPS beats/misses and post-earnings price reactions
- [Analyst Price Target Tracker](https://apify.com/gochujang/analyst-price-target-tracker) — Track analyst upgrades/downgrades timed around earnings
- [Options Expiration Calendar](https://apify.com/gochujang/options-expiration-calendar) — Monthly OPEX dates, max pain, and put/call ratios

### Feedback

If this actor is useful, a quick review helps other traders discover it: [Leave a review on Apify Store](https://apify.com/gochujang/upcoming-earnings-calendar#reviews)

***

**Keywords:** earnings calendar, earnings date, EPS estimate, Yahoo Finance, stock earnings, reporting date, pre-market earnings, after-hours, quarterly earnings, earnings season, ticker lookup

# Actor input Schema

## `tickers` (type: `string`):

Specific tickers to look up, e.g. 'AAPL,MSFT,NVDA'. Leave blank for full calendar.

## `daysAhead` (type: `integer`):

How many days forward to search for earnings dates.

## `daysBack` (type: `integer`):

How many days back to include (for recent actual results).

## `maxResults` (type: `integer`):

Maximum number of earnings events to return.

## Actor input object example

```json
{
  "tickers": "",
  "daysAhead": 14,
  "daysBack": 0,
  "maxResults": 100
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("gochujang/upcoming-earnings-calendar").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("gochujang/upcoming-earnings-calendar").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call gochujang/upcoming-earnings-calendar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,gochujang/upcoming-earnings-calendar"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/21wnOvin4kJ9UF0iP/builds/a2wK4SurTpKZxPASa/openapi.json