Dataroma is great - but I prefer backrunner
Sure I do. I made it.
I love dataroma. During my recent venture into the stock picking game it was my primary source of ideas. Not all of them are hitting their prime fair valuation as is evident by my portfolio lagging both S&P500 and my passive holdings. But may be that is because I’ve been doing the 13F stuff wrong.
13F is a mandatory quarterly filing for investment funds with more than $100 million in AUM. In this filing they disclose their position at end of quarter. Comparing it to the previous quarter gives a glimpse into what each fund is doing in terms of their conviction across the public long-only market.
Screening those filings for high-conviction moves, such as buying a new position at a substantial % of total holdings, adding or selling can generate a signal for own retail investors research. And that’s what I’ve been mostly doing.
Dataroma is good, but looks outdated now. Some of the facts that it provides are misleading in my opinion and might use a little fine touch.
I had to bolt on a screener that would surface decent ideas. A combination of AI agent, some python scripts and a data API.
There should be a better solution.
I went through WhaleWisdom, GuruFocus, TipRanks and other known sites that focus on consensus, yet found them too complicated. When you try to be everything for everyone - you tend to loose usability and focus.
I though of recreating a dataroma curated list of investors in WhaleWisdom but still WW did not give me the things I was personally looking for. UI was frustrating.
So I had to take a stab at this problem.
Let me introduce you to backrunner.io
I would not pretend that is it obviously better than other solutions. But it is set to improve on the old guard and add features that I was missing.
Here are those features:
Curated list of funds - it expands core dataroma superinvestor list of investors by adding growth, quality and failed funds (yes, failed funds as well).
Fund performance reconstruction - not just AUM growth/contraction but tracking purchases at a min/max/median quarterly price band as well as a follower performance (copycat portfolios executed at filing date deadline + 7 days) for clear picture on who is probably doing better than the broad market.
Clean UI for easy reading and understanding of each filing, stock, who does what, who holds the stock etc.
Robust database which allowed me to do some backtesting.
So yeah, backtesting.
After digging through some research I found that there is more to 13F than just single stock ideas.
There is a substantial body of evidence, that following great investors can generate returns that beat S&P500 index. There are different approaches to that. You can just copy the holdings of one that you fancy the most. Or you can hold the top holdings of funds. There are caveats to this but it seems to me that this strategy if implemented correctly survives the filing lag.
I will be digging into 13F Alpha deeper, so it’s probably a decent idea to subscribe to this substack.
Don’t want to make this post any longer than it needs to be.
I would be glad if you check out backrunner.io and give it a feedback under this post.
I focused on making a robust and clean core screener but I have more useful features in mind.
Hope this helps.