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Trading Strategy: Factor Ranking with Insider BUYS

Datasets tend to be large and there are often times numerous applications for the same set. For example, insider transactions tend to work differently with different strategies for different people. Board members, officers, CEOs, and CFOs can all conduct insider buys - each with its own transaction amount and varying amounts of significance. One board member could purchase, in a single big bang, one million dollars worth of Kraft while the CEO of that same company could roll out an equal amount of purchases through six transactions throughout the year. Does it matter that CEOs are buying? Does it matter what the transaction size is? Does it matter that a company hasn’t had a sell transaction in the past three months?

These are all questions that are relevant for you and there may be different answers for different strategies. While I have my own opinions, the data from 2iQ makes it easy for you to test that for yourselves - but for now, I'll get you started with a simple example.

I’m going to show you a simple strategy for filtering through and creating a trading strategy based off of insider transactions. It uses a scoring system that gives each stock a point based off the following criteria only looking at Insider Buys (The data is sourced from 2iQ). So a stock can receive a point for each of the criteria listed below (specifics are found in the code):

  • Transaction Size – The amount in dollars bought in the transaction
  • Insider Relation – The position of the buyer (e.g. CEO, CFO)
  • Insider Level –The insider level provides a category of the insider relation (Level A: the buyer is on the management board or chairman of the company, Level B: the buyer is upper level management, Level C: the buyer is on the supervisory board of the company)
  • Lakonishok 6 month – The Lakonishok ratio measures the insider sentiment in the company over a period of 6 months. The formula is:
    (6m buying volume-6m selling volume)/6 m aggregated buying and selling volume
  • Relative 3 month performance to SPY – Stock performance > SP500 performance in same date range
  • Insider Buy Count 24m – The number of insider buys within 24 months
  • Price of insider buy close to 52 week high

In addition, how long ago the insider buy occurred is also taken to account through a linear scale. The strategy rechecks each stock’s score daily and rebalances accordingly, taking the top 25 securities by rank (with ranks > 0).

I’m excited to be able to bring you this collaboration so take a look at the strategy and let me know what you think!

For those interested in backtesting this themselves, you can contact [email protected]

Seong

Clone Algorithm
181
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Backtest from to with initial capital
Total Returns
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Alpha
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Beta
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Sharpe
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Sortino
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Returns 1 Month 3 Month 6 Month 12 Month
Alpha 1 Month 3 Month 6 Month 12 Month
Beta 1 Month 3 Month 6 Month 12 Month
Sharpe 1 Month 3 Month 6 Month 12 Month
Sortino 1 Month 3 Month 6 Month 12 Month
Volatility 1 Month 3 Month 6 Month 12 Month
Max Drawdown 1 Month 3 Month 6 Month 12 Month
# Backtest ID: 55a80cea65a0850c74ce05b7
There was a runtime error.
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4 responses

Here's an alternative backtest that might be interesting. It uses the same scoring system as the first backtest, but doesn't filter out for when the stocks have less than zero points.

I feel like the perspective here is a bit more raw and gives you a better sense of what would happen if you longed any stock with an insider buy.

I'm also considering releasing an event study off of this data. Would love your thoughts on how to approach that (e.g. just insider buys within sp500? all insider buys?)

Seong

Clone Algorithm
181
Loading...
Backtest from to with initial capital
Total Returns
--
Alpha
--
Beta
--
Sharpe
--
Sortino
--
Max Drawdown
--
Benchmark Returns
--
Volatility
--
Returns 1 Month 3 Month 6 Month 12 Month
Alpha 1 Month 3 Month 6 Month 12 Month
Beta 1 Month 3 Month 6 Month 12 Month
Sharpe 1 Month 3 Month 6 Month 12 Month
Sortino 1 Month 3 Month 6 Month 12 Month
Volatility 1 Month 3 Month 6 Month 12 Month
Max Drawdown 1 Month 3 Month 6 Month 12 Month
# Backtest ID: 55a80cea65a0850c74ce05b7
There was a runtime error.

Seong, it says your code has some problems...I can't figure out where..please advise. Thanks!

Hi Daniel,

If you'd like to run the backtest please reach out to [email protected] for access to the sample Insider Buys data and replace data_link with the URL he provides you

Seong

Seong,

I would be interested in a few versions of studies.
1. Establish a core insider buy and 'net buy' (total buys vs. sales) 'baseline' for all of the core 'top level' execs for a set of companies. We're trying to set up the basics of what buys are simply them exercising options regularly.
2. Look for all the historical occurrences of 1.5 or 2 St dev variations above this baseline (or any 'threshhold value) for a key officer.
3. Build out a 'historical test' to see if such variations have produced 'big stocks' moves in the past (> +-5% above the bench or industry over 30 day period).
4. For those companies and 'key officers' were large moves (up or down) have led to big stock moves, set up a ranking on the people most influential.
5. Rank stocks that have 'most influential' insiders who have been 'most predictive in the past' making key buy (or sell) moves.
6. Go long the top stocks and (short) the bottom stocks.

It would also be interesting to look at new IPO's and heavy net selling. Does heavy net selling by key insiders in the first year after public offering affect future price performance.

This is just the first idea.

Best,
Tom