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New Data: Aggregated Insider Transactions

The datasets described herein are proprietary to FactSet Research Systems, Inc. ("Factset") and may not be copied or distributed. The datasets made available to Quantopian by FactSet are not exhaustive of FactSet's data, products, software, and/or services.

Hey everyone,

We have a new dataset, Aggregated Insider Transactions, that is now available to use on the platform with US equities.

Insider transactions are trades by corporate insiders, like executives or board members. You can use insider transactions data to measure the behavior of these insiders and check if they are buying or selling their company's stock (or derivates of their company's stock).

Insider transactions are reported to the SEC using Forms 3, 4, and 5. FactSet collects individual insider transaction filings from the SEC, and Quantopian aggregates this data into daily metrics about the counts of unique insiders taking action.

For an example and more details, see the attached notebook. For further information, see the Aggregated Insider Transactions documentation.

As always, please try this data out, and let us know if you have any questions!

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5 responses

Thanks for this post.
I was wondering if it was possible to view the following items:
-number of transactions in an aggregation period
-number of securities transacted or dollar value of transacted securities.

I read the documentation but it appeared that only unique buyers and sellers was available.

Thanks for the help,

What should be the "asof_date" for slice with days_aggregated = 1 when there are no unique buyers or sellers?
Here I have attached a note book where "asof_date" is non-null and unique buyers and sellers are zero. What does it mean?

Can someone please help?

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Hey Peter,
Sorry for the late reply, I totally missed this. Unfortunately we aren't providing that information right now, but are looking into ways in which we can expose it data in a way that gives a large amount of flexibility to our users.

Hey Shiv,
We still expect the asof_date to be non-null, because that's just the latest date we saw some new data. Since data is very sparse with a 1-day aggregation window (that's why it's probably usually a good idea to use a larger aggregation window like 7 or 90), you will see that the asof_date rarely updates from one day to the next, even for stocks like AAPL. The asof_date reflects the trade date on days where we have nonzero transactions in the 1-day aggregation. Let me know if that doesn't make sense.

Is there a proper way to distinguish between seasonality and cyclical nature of the transactions? Could it be coincidence that the acquisition occurred during a usual low count given the time of year? I am trying to understand a method or approach to the tearsheet challenge that has reasoning.

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Insiders typically have a ‘trading freeze’ window (when they are not allowed to buy or sell shares) leading up to the next public release of financial statements. Perhaps it’s this phenomenon you’re seeing?