# Dark Pool Volume Tracker: Weekly ATS Trading by Ticker (`mrdoe/dark-pool-volume-tracker`) Actor

Weekly dark pool (ATS) volume by ticker and venue from FINRA: shares, dollar value, trade count, average trade size and each venue's share. Official public data, weeks delayed. No key.

- **URL**: https://apify.com/mrdoe/dark-pool-volume-tracker.md
- **Developed by:** [MrDoe](https://apify.com/mrdoe) (community)
- **Categories:** Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $4.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

![Dark Pool Volume Tracker: Weekly ATS Trading by Ticker - Dark pool volume tracker with weekly FINRA ATS shares and dollar value by ticker and venue](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/dark-pool-volume-tracker--hero.png)

### What does Dark Pool Volume Tracker: Weekly ATS Trading by Ticker do?

Dark Pool Volume Tracker returns the weekly off-exchange volume that alternative trading systems (dark pools) report to FINRA, one row per ticker, week and venue. Each row has the number of shares, the total dollar value, the trade count, the volume-weighted price, the average trade size, the venue's share of that ticker's dark pool volume for the week, and the date FINRA published it. This is official public data published weeks after the trading week, aggregated per venue and week; individual trade prints are not part of it.

### Why use Dark Pool Volume Tracker: Weekly ATS Trading by Ticker?

- Official FINRA data, the public record of dark pool volume, with no key.
- Per venue: see which dark pools trade a ticker and how large their share is.
- Average trade size and a large-trade flag help separate block activity from retail flow.
- Watchlists of many tickers in one run; delta mode delivers each new week once.
- Every row states when FINRA published it, so freshness is never hidden.

### What makes this different

Paid dashboards sell dark pool prints in real time. This Actor is the free, official, delayed layer: weekly volume by ticker and venue straight from FINRA, with derived average trade size and venue share, and no pretence of being real time.

### Who can use the Dark Pool Volume Tracker and how?

- **Traders:** see where a stock's dark pool volume trades and how big the average trade is.
- **Quant teams:** build off-exchange volume features by ticker and week.
- **Market structure researchers:** study venue market share and routing changes.
- **Newsletter writers:** publish the biggest dark pool tickers each week.
- **Institutional desks:** benchmark venue share for a name.
- **Journalists:** source dark pool volume with a citable official reference.
- **Fintech developers:** add an off-exchange volume view through the API.
- **Analysts:** pair with short interest and insider data.

### How it works

![Dark Pool Volume Tracker: Weekly ATS Trading by Ticker workflow: your input, collection, output](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/dark-pool-volume-tracker--how-it-works.png)

1. **Your input** — enter tickers and how many recent weeks you want.
2. **The Actor collects it** — the Actor reads FINRA's public ATS transparency data for each ticker.
3. **Your output** — you get one row per ticker, week and venue with shares, value, trades, average size and share.

### What data can you extract?

The dataset has 24 fields per row:

| Field                       | Type    | Description                                                    |
| --------------------------- | ------- | -------------------------------------------------------------- |
| `ticker`                    | string  | Stock ticker.                                                  |
| `issue_name`                | string  | Issue name from FINRA.                                         |
| `week_start_date`           | string  | Start of the trading week (YYYY-MM-DD).                        |
| `venue_name`                | string  | Alternative trading system name.                               |
| `venue_mpid`                | string  | Venue market participant id.                                   |
| `venue_type`                | string  | Always ats\_dark\_pool.                                          |
| `tier`                      | string  | FINRA tier description.                                        |
| `trade_size_shares`         | number  | Shares traded at the venue that week.                          |
| `trade_value_usd`           | number  | Dollar value traded at the venue that week.                    |
| `trade_count`               | number  | Number of trades that week.                                    |
| `price`                     | number  | Value divided by shares.                                       |
| `average_trade_size_shares` | number  | Shares divided by trades.                                      |
| `average_trade_value_usd`   | number  | Value divided by trades.                                       |
| `large_average_trade`       | boolean | True when the average trade reaches the large-trade threshold. |
| `share_of_ats_volume_pct`   | number  | Venue share of the ticker's dark pool shares that week.        |
| `ats_total_shares_week`     | number  | All dark pool shares of the ticker that week.                  |
| `ats_total_value_usd_week`  | number  | All dark pool value of the ticker that week.                   |
| `ats_venue_count_week`      | number  | Number of reporting venues that week.                          |
| `reported_at`               | string  | Date FINRA published the week.                                 |
| `last_reported_trade_date`  | string  | Last trade date included in the week.                          |
| `fetch_path`                | string  | finra\_public\_api.                                              |
| `source`                    | string  | Data source.                                                   |
| `scraped_at`                | string  | Collection time (ISO 8601).                                    |
| `actor_version`             | string  | Output schema version.                                         |

### How to use Dark Pool Volume Tracker: Weekly ATS Trading by Ticker

![Dark Pool Volume Tracker: Weekly ATS Trading by Ticker input form](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/dark-pool-volume-tracker--input.png)

1. Open the Actor and go to the **Input** tab.
2. Enter **Tickers**, choose **Latest weeks per ticker**, and run. Filter by **Minimum weekly venue value** to focus on the large venues.
3. Optionally set filters and a **Max results** limit.
4. Click **Start**. A default run finishes in under a minute.
5. Open the **Output** tab, then download the dataset or connect it to your tools.

### Input Parameters

| Parameter                 | Type    | Required | Default                   | Description                                                                                                                  |
| ------------------------- | ------- | -------- | ------------------------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `tickers`                 | array   | No       | `[]`                      | Stock tickers to read, one per line.                                                                                         |
| `weeks`                   | integer | No       | `4`                       | How many of the newest published weeks to return for each ticker.                                                            |
| `sinceDate`               | string  | No       | —                         | Only weeks after this date (YYYY-MM-DD). Default is the last 120 days, which covers FINRA's publication delay.               |
| `minTradeSizeUsd`         | number  | No       | `0`                       | Skip venue rows whose total traded value for the week is below this.                                                         |
| `largeAverageTradeShares` | number  | No       | `5000`                    | Rows whose average trade size reaches this many shares are flagged large\_average\_trade.                                      |
| `maxItems`                | integer | No       | `500`                     | Maximum number of rows returned. Set 0 for no limit.                                                                         |
| `deltaMode`               | boolean | No       | `false`                   | Return and bill only ticker-week-venue rows not delivered by an earlier run with the same delta key. FINRA publishes weekly. |
| `deltaStateKey`           | string  | No       | `"default"`               | Name of the tracked stream.                                                                                                  |
| `proxyConfiguration`      | object  | No       | `{"useApifyProxy":false}` | Optional proxy. FINRA's public data service works without one.                                                               |

### Output Data

![Dark Pool Volume Tracker: Weekly ATS Trading by Ticker dataset table](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/dark-pool-volume-tracker--output.png)

`trade_size_shares`, `trade_value_usd` and `trade_count` are the venue's totals for the week. `price` is value divided by shares. `average_trade_size_shares` is shares divided by trades; `large_average_trade` is true above your threshold (5,000 shares by default). `share_of_ats_volume_pct` is the venue's part of the ticker's total dark pool volume that week. `reported_at` is the date FINRA published the week.

![Dark Pool Volume Tracker: Weekly ATS Trading by Ticker field map of one record](https://api.apify.com/v2/key-value-stores/kE36venAoVchGsE6b/records/dark-pool-volume-tracker--fields.png)

A real dataset item:

```json
{
    "ticker": "BRK.B",
    "issue_name": "BERKSHIRE HATHAWAY Class B",
    "week_start_date": "2026-08-31",
    "venue_name": "UBSA UBS ATS",
    "venue_mpid": "UBSA",
    "venue_type": "ats_dark_pool",
    "tier": "NMS Tier 1",
    "trade_size_shares": 487233,
    "trade_value_usd": 246265235,
    "trade_count": 16262,
    "price": 505.4363,
    "average_trade_size_shares": 30,
    "average_trade_value_usd": 15144,
    "large_average_trade": false,
    "share_of_ats_volume_pct": 15.13,
    "ats_total_shares_week": 3219506,
    "ats_total_value_usd_week": 1627897178,
    "ats_venue_count_week": 30,
    "reported_at": "2026-09-21",
    "last_reported_trade_date": "2026-09-04",
    "fetch_path": "finra_public_api",
    "source": "finra_ats_transparency",
    "scraped_at": "2026-09-26T02:43:40.070Z",
    "actor_version": "1.0.0"
}
```

### How to read and use the results

1. **Sort by trade\_value\_usd** for the biggest venues.
2. **Read share\_of\_ats\_volume\_pct** for venue concentration.
3. **Check average\_trade\_size\_shares** and large\_average\_trade for block-like activity.
4. **Compare weeks** to see changes in dark pool activity.
5. **Read reported\_at** to know how fresh each row is.
6. **Automate** with delta mode and a weekly schedule.

### Usage Examples

#### Dark pool volume for a watchlist

```json
{
    "tickers": ["AAPL", "TSLA", "NVDA", "SPY"],
    "weeks": 4
}
```

#### Only large venues for one ticker

```json
{
    "tickers": ["AAPL"],
    "weeks": 8,
    "minTradeSizeUsd": 500000000
}
```

#### Only new weeks since last run

```json
{
    "tickers": ["AAPL", "TSLA"],
    "deltaMode": true,
    "deltaStateKey": "dark-pool-watch"
}
```

### Tips for Best Results

- Compare a venue's average trade size with the ticker's typical size to spot block-heavy venues.
- Track share\_of\_ats\_volume\_pct over weeks to see routing shifts.
- Schedule weekly with delta mode; FINRA publishes each week a few weeks late.
- Combine with insider buying and short interest for a fuller institutional-flow picture.
- Default is 5 results for a fast test. Set the max to 0 to return everything available.

### Reliability by mode

| Mode                               | Status | Needs login or key? | Notes                        |
| ---------------------------------- | ------ | ------------------- | ---------------------------- |
| Weekly volume per venue            | ✅     | No                  | FINRA public data.           |
| Average trade size and venue share | ✅     | No                  | Derived from the same rows.  |
| Individual dark pool prints        | ❌     | -                   | Not public; sold by vendors. |
| Real-time data                     | ❌     | -                   | Published weeks late.        |
| Buy or sell direction              | ❌     | -                   | Not in the data.             |
| Tickers with no ATS volume         | 🟡     | No                  | Return a clear warning.      |

✅ works as described, 🟡 works with caveats, ❌ not supported.

### Only new records (delta mode)

Turn on **Only new weeks (delta mode)** and set a **Delta key**. Each scheduled run returns, and bills, only ticker-week-venue rows that earlier runs of that key have not delivered.

### Known Limitations

- This is weekly aggregate volume per venue, not individual dark pool trade prints. Trade-level prints are sold by market data vendors and are not part of FINRA's public data.
- Data is published weeks after the trading week (see reported\_at); it is not real time.
- Only alternative trading systems (dark pools) that report to FINRA are included, not internalized retail flow.
- Volume figures show activity, not direction: FINRA data does not say whether trades were buys or sells.
- Newly listed or thinly traded tickers can have no rows.
- FINRA's data terms apply; check them for your commercial use. This is information, not investment advice.

### Integrations

Run it from the Apify API, on a schedule, or from a webhook. Send results straight to Google Sheets, Make, Zapier, Slack or your own database with Apify's built-in integrations.

### Export Formats

Download the dataset as JSON, CSV, Excel, XML, HTML table or RSS from the **Output** tab or the API.

### Frequently Asked Questions

#### Where does the data come from?

FINRA's public OTC transparency data for alternative trading systems, served by FINRA's own data API. It is an official public source.

#### Does it show individual dark pool prints?

No. FINRA's public dataset is weekly totals per venue and ticker. Individual prints are only available from paid market data vendors.

#### Why is the data weeks old?

FINRA publishes ATS transparency data with a delay of a few weeks. reported\_at shows the publication date.

#### Does it need an API key?

No.

#### What is a large\_average\_trade?

A venue whose average trade for the week is at least the number of shares you set, 5,000 by default, which points to block-size activity.

#### Am I charged for failed results?

No. You are only charged for rows written to the dataset.

#### Do I need an account or login?

No. The Actor reads FINRA's public data service and needs no account or API key.

#### Am I charged for failed runs or empty results?

You are only charged for results that are actually written to the dataset.

#### Can I run it on a schedule?

Yes. Create a Task with your input and add a schedule in Apify Console. With monitor mode on, each scheduled run returns only what changed since the previous one.

### Changelog

- **2026-09-26:** First release: weekly FINRA ATS volume by ticker and venue with average trade size, venue share and delta mode.

### Enterprise and custom work

Need higher volumes, a custom output schema, dedicated scheduling or a no-breaking-changes commitment for a production pipeline? Open an issue on the Actor page and describe your use case. Bulk terms and custom builds are available.

### Support

Questions or a missing field? Open an issue from the **Issues** tab on this Actor's page and it will be looked at.

### Legal / Responsible Use

This Actor reads data that FINRA publishes for the public. FINRA's data usage terms apply to your use. You are responsible for how you use the data. It is not investment advice and not affiliated with FINRA.

# Actor input Schema

## `tickers` (type: `array`):

Stock tickers to read, one per line.

## `weeks` (type: `integer`):

How many of the newest published weeks to return for each ticker.

## `sinceDate` (type: `string`):

Only weeks after this date (YYYY-MM-DD). Default is the last 120 days, which covers FINRA's publication delay.

## `minTradeSizeUsd` (type: `number`):

Skip venue rows whose total traded value for the week is below this.

## `largeAverageTradeShares` (type: `number`):

Rows whose average trade size reaches this many shares are flagged large\_average\_trade.

## `maxItems` (type: `integer`):

Maximum number of rows returned. Set 0 for no limit.

## `deltaMode` (type: `boolean`):

Return and bill only ticker-week-venue rows not delivered by an earlier run with the same delta key. FINRA publishes weekly.

## `deltaStateKey` (type: `string`):

Name of the tracked stream.

## `proxyConfiguration` (type: `object`):

Optional proxy. FINRA's public data service works without one.

## Actor input object example

```json
{
  "tickers": [
    "AAPL",
    "TSLA",
    "NVDA",
    "SPY"
  ],
  "weeks": 4,
  "minTradeSizeUsd": 0,
  "largeAverageTradeShares": 5000,
  "maxItems": 500,
  "deltaMode": false,
  "deltaStateKey": "default",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# 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 = {
    "tickers": [
        "AAPL",
        "TSLA",
        "NVDA",
        "SPY"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("mrdoe/dark-pool-volume-tracker").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 = {
    "tickers": [
        "AAPL",
        "TSLA",
        "NVDA",
        "SPY",
    ],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("mrdoe/dark-pool-volume-tracker").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 '{
  "tickers": [
    "AAPL",
    "TSLA",
    "NVDA",
    "SPY"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call mrdoe/dark-pool-volume-tracker --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,mrdoe/dark-pool-volume-tracker"
        }
    }
}
```

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/15WSh5MA3C9OFSUnl/builds/1PCyxEnLJ79abPccJ/openapi.json