I spent $9,600/year on Substack newsletters so you don’t have to. Here’s who actually makes money.

This sort of blew up on r/ValueInvesting so posting here too.

I work in AI and started trading casually last year. Like any good regard, I immediately subscribed to every investing newsletter I could find on Substack. 23 paid subscriptions. $9,600/year, including Michael Burry's.

The problem? I can't actually read them all. And I have no idea which ones are worth the money.

So I did what any engineer would do — I wrote codes to find out.

What I Built

A pipeline that:
– Crawls every article from 23 paid Substack authors (1,782 articles over the past year)
– Uses Gemini AI to extract high-conviction stock picks only — not casual mentions, but tickers the author actually analyzed in depth
– Tracks returns at 1d, 7d, 15d, 30d, and 60d after publication
– Calculates alpha vs sector benchmarks (SOXX for semis, IGV for SaaS, XLF for financial services etc)
– Dedupes: if the same author calls the same ticker multiple times within 14 days, it only counts once (first mention wins). Different authors calling the same ticker are tracked independently

Total dataset: 3,519 high-conviction calls tracked over 1 year.

The Results

30-Day Absolute Return Leaderboard (Long Calls)

30-Day Alpha vs Benchmark (Long Calls)

30-Day Win Rate (Long Calls)

But 30 Days Isn't the Whole Story

30d is a reasonable window for swing traders, but some of these authors are deep value investors with 6-12 month theses. Here's what the 60-day numbers look like — the rankings shift significantly:

60-Day Absolute Return Top 10 (Long Calls)

Notable shifts: Fabricated Knowledge jumps from #9 (30d: +5.8%) to #3 (60d: +14.2%). Altay Capital goes from +7.2% to +13.7%. Deep value theses need time to play out. Conversely, Collyer Bridge drops out of the top 10 at 60d — their edge is more short-term.

Take these numbers for what they are: one time horizon among many. A 60d or even 90d window would tell a different story for buy-and-hold investors. This is for information, not gospel.

And at the bottom…

Michael J Burry: 24 long calls, 30d avg return +0.1%, 60d avg return -11.1%, 30d alpha -2.7% (60d alpha: -11.4%). Then again, The Big Short took 2 years to play out — maybe his thesis just needs more time than our 60-day window can capture.

Methodology Caveats (Please Challenge This)

I want to be upfront about limitations:

1. AI extraction isn't perfect. Gemini parses articles and extracts ticker calls. To reduce noise, we only count high conviction — where the author dedicates multiple paragraphs, specific data, or explicit price targets. Passing mentions are filtered out.
2. We validated this. Spot-checked extraction accuracy against manual reads, and cross-verified with alternative model outputs (codex / claude). It's not 100%, but it's consistent.
3. Survivorship bias matters. We only track tickers with available price data. Delisted stocks, non-US tickers without yfinance data, and typos get counted as No Data and excluded from return calculations.
4. This is a bull market. Many of these authors are long-biased. Absolute returns look good partly because the market went up. The alpha column adjusts for this using sector-specific ETF benchmarks.
5. The full dataset is available. All 3,519 calls, every author, every ticker, every return at every horizon. You can audit everything. I will put up the link later.

What I Learned

• The expensive ones aren't always the best. Some of the top performers cost 80−360/year.Some1,000+ newsletters are mid-table.
• Volume ≠ quality. Authors with 300+ calls often have mediocre win rates. The ones with 15-80 highly targeted calls tend to outperform.
• Shorts are hard. Almost every author has worse short performance than long. The few exceptions (Global Tech Research shorts: -20.5% at 60d) are impressive outliers.
• Michael Burry's Substack picks haven't worked yet — but his most famous trade took 2 years, so the jury's still out.

Total Cost Breakdown

$9,599/year across 23 newsletters. Here's every single one:

If I could only keep 5 based on this data: Global Tech Research (100),PauloMacro(360), Doomberg (300),SemiAnalysis(500), The Setup Factory (450).That′s1,710/year — 82% cheaper and probably better returns.

Shoutout to every author on this list. Even the bottom-ranked ones taught me more about markets than any YouTube video. This isn't meant to trash anyone — just data.

Happy to answer questions. Roast my methodology. Tell me I'm wrong. That's how this gets better.

Full methodology + data / charts: https://x.com/pyhrroll/status/2027374283669066045?s=20

Positions: long several names mentioned by top authors. Not financial advice, obviously.