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[Update 6/14] How to conduct your own event study using Research

UPDATE 6/14: We've just released 'Cloning' for notebooks. If you have access to Research and are looking to see how you can conduct your very own event study, take a look at this notebook and post back with questions and comments.

Previously, we had released a notebook and algorithm that detailed using Share Buybacks Announcements as a trading signal. In this post, we're going to show you an event study conducted in the same Research Environment that takes an in-depth look at share buybacks announcements as a singular event. We collaborated with EventVestor, a data vendor who provides information about corporate events. Find more information about the data and how you can gain access to it by clicking here.

Below is a chart from the notebook that summarizes our findings from the study. In total, we found that while there is a large ~1% movement in stock prices immediately following a buybacks announcement (which most retail investors can't trade on), there is also a drift that follows for several days afterwards with average abnormal returns closing up on .5~1%. This abnormal drift is what we can create a strategy around and we did so here in this notebook and algorithm.

Click the "VIEW NOTEBOOK" button and scroll through the notebook. There's a lot of interesting findings here and I promise you're going to learn a lot.

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4 responses

Hi all,

Here's the algorithm that inspired it all! We use a custom fetch_eventvestor method that will get you a static set of data from 2007 up till January, 2015.

There are a number of different parameters that you can change in order to fiddle around with the algorithm:

context.days_to_hold_positions - The number of days to enter into a position before exiting
context.hedge_lookback - The number of days to look back before calculating our beta hedge (SPY)
In choose strategy, you have a number of different lines that you can comment/uncomment to turn on the different parts of the strategy found in the notebook.
Notes:

The sample data in this algorithm provides a static snapshot between January 2007 - January 2015. That being said, fetch_eventvestor is not allowed in Live Trading and your algorithm will throw an error if you try to deploy it in either paper, context, or live trading modes!

We are working to incorporate this data in a more permanent fashion but until then, you can contact EventVestor for more information.

This particular algorithm was created by @Richard Prokopyshen who found an error in the hedging logic of my first algorithm. Thanks for the share Richard!

Heya - I notice you seem to be setting the universe to the fetched data (from eventvestor?). Do you have a link to the evidence that eventvestor's data is survivorship-bias free? I am suspicious that the good results are only around the financial crisis...

Hi Simon,
EventVestor tracks all buyback announcements and to make sure the data is survivorship-bias free, we provide all data as reported, keeping all history even if the stock doesn't trade any more. The same data is provided to Quantopian for this research. We will soon be releasing more details about data on other key corporate events including CEO/CFO Changes, Clinical Trials, Dividends, Earnings Announcements, Executive Changes, FDA Filings/Approvals, Earnings Guidance, Issue Debt, Issue Equity, Insider Transactions, Activists and Hedge Funds Ownership Changes, Mergers & Acquisitions, Retail Same Store Sales, Spin-offs, and Stock Splits.

Thanks,
Anju Marempudi

Hey all,

We've just released 'Cloning' for notebooks. If you have access to Research and are looking to see how you can conduct your very own event study, take a look at this notebook and post back with questions and comments.

Seong