Free historical insider trading data. Institutional holdings, too.

Download SEC insider disclosures back to 2006 and institutional holdings back to 2013, then query them on your laptop.

A simulated insider strategy turning $100,000 into $781,454 is hard to scroll past. That's the result on Nuvectis's company profile, and below I'll show you the curve, the rules, and the filings behind it.

I made the underlying insider disclosures and institutional holdings available as free downloads so you can investigate these ideas yourself. One command turns the published files into a local SQLite database.

Download the complete dataset

Run this command to download the full published history of both insider disclosures and institutional holdings, including their filing tables, into one SQLite database:

npx sec-ownership-disclosures@latest download --sqlite

The database is saved at ./sec-ownership-data/sec-ownership.db. You need Node.js 22.5 or newer. The download requires no API key or SEC credentials.

If you prefer Parquet files for notebooks or a data warehouse, use:

npx sec-ownership-disclosures@latest download

Both commands fetch all published years and all four tables. The October 3, 2026 snapshot totals 2.68 GB of compressed Parquet files across 70 files. Institutional holdings account for 2.42 GB of that download. The SQLite command retains those files and creates an additional database, so its total disk usage will be larger than 2.68 GB.

Download the free SEC ownership datasetBrowse the Parquet files and snapshot receipt, or use the commands above to download the full published history.huggingface.co/datasets/austin-starks/sec-ownership-disclosures →

You can use the rows yourself, or open NexusTrade to search the disclosures and compare strategies built from them. You can also combine disclosure signals with technical indicators, company fundamentals, and economic conditions in a custom strategy.

Research insider activity without writing SQL

Start with the insider research page. The Companies view combines each company's officers and directors into one strategy. Switch to People to follow a reporting owner across the companies where they file. You can search by company or ticker, then narrow the people view by reporting owner and role.

Those views answer different questions. A company's strategy asks what happened when its officers and directors reported acquisitions in that company. A person's strategy follows that owner across their reporting history. The company model excludes 10% holders, which keeps a fund's ownership activity from becoming an officer-and-director signal.

Open a profile to see the strategy rules, performance curve, comparison with SPY, and maximum drawdown. The filing section separates the transaction date from the public date and lets you inspect the evidence behind a signal.

A 681.5% gain is an extraordinary result. The Nuvectis follower strategy turned $100,000 into $781,454 over roughly five years, while the same starting investment in SPY grew to about $188,100. That's almost eight times the starting capital and more than four times SPY's ending value. This is the simulated result shown on October 3, 2026, with fees included.

That is the kind of result that makes these disclosures worth investigating. You can open the strategy, inspect its rules, and test your own variation. Its 71.2% maximum drawdown also tells you how rough the ride was: the remarkable ending value came with a severe loss along the way.

The insider model treats public purchases and issuer awards as separate acquisition signals. An award is compensation, so it is kept distinct from a purchase; a purchase-only strategy like the Aurora example below excludes awards. The follower rules can select shares or modeled yearly at-the-money options, held for a 45-day window. A public sale blocks the corresponding stock, call, or put position. Those options are modeled substitutions, rather than a reconstruction of the insider's actual account.

You can also switch the leaderboard to strategies that trailed SPY. That gives you a way to examine where the same rules failed, rather than choosing only the most impressive historical winner.

Explore insider strategiesSearch companies and reporting owners, compare their modeled strategies with SPY, and inspect public filings.nexustrade.io/research/insiders →

Inspect institutional holdings and test a follower strategy

The institutional research page ranks modeled strategies built from managers' public 13F disclosures. Search a manager by name or CIK, open its profile, and inspect the disclosed positions alongside the strategy result. The leaderboard also lets you examine strategies that trailed SPY.

A manager profile shows the reporting period and the date the filing became public. Its holdings table includes issuer names, security identifiers, reported values, and share amounts, with a link to the official SEC filing.

NexusTrade follows each quarterly book after publication and models disclosed stock positions with shares. Disclosed calls and puts become modeled yearly at-the-money options because a 13F does not provide the original strike or expiration. The reported underlying value determines their relative budgets; it does not tell you the option premium the manager paid.

The profile's curve, SPY comparison, and risk statistics describe that follower simulation, with fees. They do not establish the manager's actual fund performance. This matters especially when a leaderboard result looks extraordinary: inspect the holdings and model assumptions before deciding the approach belongs in your own portfolio.

Explore institutional strategiesFind a manager, inspect its public holdings, and compare the modeled follower strategy with the S&P 500.nexustrade.io/research/institutions →

Build a custom strategy with technical, fundamental, economic, and alternative data

NexusTrade lets you describe investing rules in plain English and use Aurora to turn them into a strategy you can backtest. Insider disclosures and institutional holdings add another set of inputs to the technical, fundamental, and economic data already available in the platform.

Each type of data can answer a different question:

For example, insider purchases might identify a company worth investigating. A fundamental filter can narrow that list to companies meeting your valuation criteria. A moving average can control when you enter, and an economic condition can determine when the strategy is allowed to hold risk.

Here is a concrete research request you can give Aurora:

SELECT resolvedTicker,
       COUNT(*) AS reported_purchase_legs
FROM insider_transactions
WHERE transactionCode = 'P'
  AND availableAt >= '2024-01-01'
  AND availableAt < '2025-01-01'
  AND resolvedTicker IS NOT NULL
GROUP BY resolvedTicker
ORDER BY reported_purchase_legs DESC, resolvedTicker
LIMIT 10;

SELECT accession, availableAt, issuerName,
       cusip, sharesAmount
FROM institutional_holdings
WHERE availableAt < '2025-01-01'
ORDER BY availableAt DESC, accession, cusip
LIMIT 10;