How Our AI Actually Performs
Every closed pick since inception. No cherry-picking, no back-fitting. The full log lives at /track-record. Free to cite — attribution appreciated.
Cumulative PnL by month
Sum of realized % returns across closed picks.
Performance by sector
Sectors where the AI's edge is strongest — and weakest.
| Sector | Picks | Win Rate | Avg PnL |
|---|---|---|---|
| Clean Energy | 3 | 100.0% | +12.92% |
| EV / Auto | 4 | 100.0% | +11.74% |
| Industrials / Defense | 6 | 100.0% | +11.34% |
| Fintech / Payments | 4 | 100.0% | +10.05% |
| Cryptocurrency | 14 | 85.7% | +7.06% |
| Big Tech | 7 | 100.0% | +3.59% |
| Other | 10 | 90.0% | +2.75% |
| AI / Semiconductors | 9 | 88.9% | +2.06% |
Performance by timeframe
Short-term vs swing vs long. Which horizon actually pays.
| Timeframe | Picks | Win Rate | Avg PnL |
|---|---|---|---|
| swing | 58 | 91.4% | +6.27% |
Biggest winners and losers
The tails of the distribution — good and bad.
- NEAR-USD+21.61%
- NEAR-USD+18.89%
- RIVN+17.07%
- ACHR+16.83%
- OKLO+15.90%
- XRP-USD-12.44%
- ARM-6.61%
- NEAR-USD-1.29%
- SIE.DE-1.26%
- MARA-0.21%
Every pick logged in track_record at the moment it was generated by the AI. Positions settle against live market prices — never manually overridden. Win rate is closed-trade only. Expectancy = P(win)·avgWin + P(loss)·avgLoss. Profit factor = Σgross wins / Σgross losses. Sector is assigned from an internal ticker taxonomy across 57 closed picks.
Past performance does not guarantee future results. Full disclaimer. Data licensed CC-BY — please link back to this page.