Get today's unusual options activity in one call. Pick an asset class (stocks, ETFs or indices) and the actor returns one clean record per option signal — ready to pipe into a screener, alerting bot, or trading model. Pay once per run — no login, no external proxy key.

What you get (one record per signal)

Field	Description
ticker	Underlying symbol (e.g. AAPL, SPY)
optionSymbol	Full option contract symbol
optionType	Call or Put
strike	Strike price
expiration	Expiration date
daysToExpiry	Days to expiration (DTE)
underlyingPrice	Underlying price at scrape time
moneyness	% in/out of the money
bid / ask / lastPrice	Quote at scrape time
volume	Contract volume
openInterest	Open interest
volumeOIRatio	Volume ÷ open interest — the unusual-activity signal
impliedVolatility	Implied volatility (%)
volatility	Historical volatility (%)
delta	Option delta (greek)
lastTradeTime	Last trade timestamp
assetClass / source	Which board the signal came from

Clean dataset, by design. The dataset holds only signals — the per-run summary (counts, filters, timestamp) is written to the run's OUTPUT, not mixed into your data as a junk row. Pipe the dataset straight into your tools without filtering anything out first.

Input

Field	Type	Notes
assetClass	select	stocks (default), etfs, or indices.
optionType	select	all (default), call, or put.
maxResults	integer	Cap on signals returned. Default 100.
minVolume	integer	Optional. Keep signals with volume ≥ this. 0 = off.
minVolumeOIRatio	integer	Optional. Keep signals with Vol/OI ≥ this. 0 = off.
proxyConfiguration	proxy	Default Apify Residential.

Example

{
  "assetClass": "stocks",
  "optionType": "call",
  "maxResults": 50,
  "minVolumeOIRatio": 3
}

How it works

1. Opens the unusual-activity board for the chosen asset class through a residential proxy.
2. Lets the page complete its own session handshake and read its activity feed, captures that feed, and maps it to a clean schema. If the feed is unavailable it falls back to reading the rendered table structurally — by column header, never by CSS class — so it keeps working when the page is restyled.
3. Drops footer/summary rows, applies your filters, and returns one clean record per signal.

Notes

• Unusual options activity is most populated during US market hours.
• Billing event: unusual-options-table — one flat charge per run that returns at least one signal.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Companies France
• Companies House UK Scraper
• Crunchbase Scraper
• Seeking Alpha Scraper
• Transfermarkt Scraper
• Yahoo Finance Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.