Best finance YouTubers by accuracy
Most rankings sort by subscribers. We score every creator's calls against what the stock actually did afterwards, then rank by accuracy. Only creators with at least 20 scored calls qualify, so a lucky streak can't reach the top.
| # | Creator | Accuracy |
|---|---|---|
| 1 | | 71% |
| 2 | | 65% |
| 3 | | 63% |
| 4 | | 62% |
| 5 | | 59% |
| 6 | | 58% |
| 7 | | 58% |
| 8 | | 57% |
| 9 | | 56% |
| 10 | | 55% |
| 11 | | 55% |
| 12 | | 51% |
| 13 | | 50% |
| 14 | | 49% |
| 15 | | 48% |
| 16 | | 40% |
| 17 | | 16% |
Accuracy = the share of a creator's calls (at least 7 days old, with price data) where the stock moved the direction they called. “vs S&P 500” compares an equal-weight copy-portfolio of their buy calls against the index over the same dates. Figures update twice a day. Methodology
FAQ
Who is the most accurate finance YouTuber?
By our measure, the creator at the top of this list — accuracy is the share of their qualified calls where the stock moved the way they predicted, across at least 20 scored calls. The ranking updates twice a day as new calls are scored.
How is accuracy measured?
We transcribe every video, extract qualified calls (a named stock, a clear stance, real reasoning), then check whether the price moved the called direction after 7+ days. Only creators with 20 or more scored calls are ranked. Full details on the methodology page.
Does a bigger channel mean better calls?
No. Several creators under 100K subscribers out-score channels with 500K+, and audience size has no relationship to measured accuracy. That is exactly why we rank by results, not reach.