alt Hacker NewsShow HN: Every CEO and CFO change at US public companies, live from SEC
Built this solo. It watches SEC filings for executive and board changes, extracts the data, and shows it in real time. 2,100+ changes in the last 30 days. The comp data is interesting: average new CEO total comp is $8.4M across 284 appointments. The /explore page is fully open, no login needed.
Comments
Given this is failing due to HN hug of death, might I suggest that you do a periodic batch, save the results and serve static?
Getting “literally who” vibes from the list of execs that were listed with a job title but not a company name.
Mobile browser, if that makes a difference (maybe one of the people on the list helped me downsize as well at some point without me realizing it).
Nice idea. Small thing: the categories are pretty much fixed. If you have to abbreviate a never-changing category like "Consumer Defen..." in a widget, your design doesn't work in this aspect.
You can also check any signal from publicly available sources using tools like CatchAll.
For example, "CEO and CFO appointments at US public companies in the last two weeks" found 142 records [0]
You can also set up monitors to get updates.
[0] https://platform.newscatcherapi.com/catchall/example/gtm--ex...
Nice work.
I remember giving this task to a summer co-op 10-12 years ago. it was alot harder to scrape the edgar site then and gather all for form 4 filings without the new api call first interface and the XBML markup in 10-K and 10-Q filings.
Great proof of concept!
At the top it says:
> 2,100+ > CEO, CFO, Board, and other executive changes tracked in the past 30 days
Could you add a little metric there such as how many companies are being tracked, and perhaps how that compares to the previous 30 days, or 6 months ago, or 12 months ago?
Maybe a graph showing how many changes happen each month, so we can see when things are more volatile or not.
Interesting, you should save part of the data to do some caching and avoid api requests for old positions.
This feels like the start of a “people layer” for public companies—almost like a Bloomberg terminal but focused purely on executive movement.
Curious if you’ve looked at second-order signals yet (e.g. clusters of execs moving across the same companies)?
Interesting. How do you yourself use this(I am assuming of course you built it out of a need to want to have to track this data)?
been mulling visualizing this for years.. nice work.
How does the comp extraction work? 8-K prose has no standard format so curious whether you're running it through an LLM or using a rules-based parser, and how you handle amendments where the actual figures show up in a later filing.
I think one of the interesting things here is that many senior executives make similar base pay to very senior ICs. The primary compensation difference is in their equity compensation, where executives get massive PSU/RSU packages, while senior ICs get much more modest packages. A senior IC may have 30-50% of their compensation as stock, while a typical senior executives may have as much as 97% of their compensation as stock.
Is the equity piece one-time or yearly grants? I think it is adding up yearly salary with one-time equity grants. Also, how about bonuses?
Nice job! Is there a way to double click on any name to see more details on the person like previous positions or current compensation?
The site fails to load...it just gets stuck in a fetching state. Another downside of vibe programming.
You hit on something that AI can be really good at, which is shining light on corporate activities. Salary and movement are great, and interesting, but this could also help parse things like entry and exits into business markets where companies often quietly add or remove things from their filings. Keep going.
did you write the SEC parsers yourself or use oss/off the shelf tech?
What's the backend? I'd recommend to migrate such project to the edge (Cloudflare, etc)
Fun project but meh on subscription. This data already exists in much better detail including full network graphs of people and many additional data points. Financial data is a hard problem because it’s not only hard to offer something new but also your only real consumer unless novel data is going to be retail.
[dead]
[dead]
What would also be very interesting is a graph of relationships and movements. Let's see just how incestuous the boards really are, and what's going on with serial CEOs who move from one business to the next.