The historical replay, in numbers.
Every buy-to-sell signal in the current-rule historical replay, in aggregate: by year, by theme, the return distribution, the best and the worst. Closed round trips and the positions still open are both counted. Regenerated after every US close; retrospective, not live.
Data status: what these statistics are, and are not
Data status: historical replay. Generated 2026-09-11 16:39, today’s Hesper Atlas rules produce 578 closed BUY-to-SELL signals across 155 tracked names since 2022-06-21. 64.9% ended in profit; the average closed signal returned +39.7% over 135 days. The average winner made +65.1% while the average loser cost −7.2%, and 8.8% of all closed signals at least doubled.
The replay leaves 111 more signals open, 16.1% of all replay signals, and they are included rather than left out of the count: marked at the last close, 80.2% of them are in profit (median +61.8%, worst −20%). Counting the closed and the open book together, all 689 signals average +65.9% with 67.3% in profit. Open marks are unrealized and can still turn.
Source and status: every figure on this page is computed from the machine-readable JSON replay (field stats_ext), regenerated with current rules after every US close. Retrospective, losing signals included, not live performance. Educational tool, not financial advice.
The open replay book
Closed-trade statistics have a well-known failure mode: bank the winners, let the losers run, and the closed book still looks excellent. The only honest answer is to publish the positions the replay still leaves open. All 111 of them are aggregated here, 16.1% of all replay signals, so the closed numbers above can be checked against what was left out. The full open replay list is public on the track page. The latest end-of-day action and trade-plan levels remain the paid layer.
| Every signal, cut the same way | Closed (578) | Open (111) | All (689) |
|---|---|---|---|
| In profit | 64.9% | 80.2% | 67.3% |
| Up 20% or more | 28.5% | 61.3% | 33.8% |
| Up 50% or more | 15.2% | 55.0% | 21.6% |
| At least doubled | 8.8% | 39.6% | 13.8% |
| Down 10% or more | 8.5% | 4.5% | 7.8% |
| Down 20% or more | 2.1% | 0.9% | 1.9% |
| Median return | +4.2% | +61.8% | +5.8% |
| Average return | +39.7% | +202% | +65.9% |
Closed returns are realized at the exit price. Open returns are marked at the last close, are unrealized, and can still turn: a position up 40% today can close flat. The point of the column is not to claim those gains, it is to show that the signals left out of the closed statistics are not the bad ones. Nor is the open column a like-for-like read: a position is still open precisely because its trend has not broken, so the open book skews to longer holds and larger marks by construction. What matters is the direction of that skew, and it runs against the closed figures rather than flattering them.
Results by year
Every closed signal, grouped by the year it exited. Trend engines earn their keep in trending years and get whipsawed in choppy ones; both show up here.
| Year | Signals | Ended in profit | Avg return |
|---|---|---|---|
| 2022 | 42 | 33.3% | −2% |
| 2023 | 130 | 60.8% | +10.4% |
| 2024 | 130 | 68.5% | +36.2% |
| 2025 | 157 | 72.6% | +53% |
| 2026 | 119 | 66.4% | +72.8% |
The current year contains only the signals that already closed; open positions join it when they exit.
What a closed signal looks like
The distribution behind the averages. A trend engine's math is asymmetry: it takes many small losses to stay in the game for the few very large wins.
Results by theme
Closed signals grouped by the theme of the underlying name, largest first.
| Theme | Signals | Ended in profit | Avg return |
|---|---|---|---|
| Genomics & AI-Health | 99 | 57.6% | +11.5% |
| AI Software | 64 | 60.9% | +33.3% |
| AI Power & Grid | 58 | 62.1% | +47.8% |
| AI Chips | 52 | 59.6% | +31% |
| Consumer & Internet | 52 | 71.2% | +14% |
| Fintech & Crypto | 39 | 61.5% | +42.5% |
| HBM & Packaging | 28 | 71.4% | +41.4% |
| Quantum | 24 | 58.3% | +87.9% |
| AI Servers & Systems | 17 | 76.5% | +89% |
| Energy | 16 | 68.8% | +6.9% |
| Industrials | 16 | 62.5% | +28.5% |
| AI Cloud | 15 | 66.7% | +102.9% |
Ten best closed signals
| Symbol | Entry | Exit | Return |
|---|---|---|---|
| AXTI | 2025-08-28 | 2026-06-10 | +2820.9% |
| PLTR | 2023-05-11 | 2026-01-28 | +1492.6% |
| IREN | 2025-05-01 | 2025-11-05 | +1099.5% |
| SMCI | 2022-09-06 | 2024-07-24 | +1055.5% |
| RGTI | 2024-09-13 | 2025-02-26 | +987.9% |
| POWL | 2022-10-25 | 2025-02-18 | +809.8% |
| LITE | 2025-06-25 | 2026-07-06 | +696.8% |
| VRT | 2023-04-26 | 2025-01-27 | +656.3% |
| NVDA | 2022-12-09 | 2025-03-14 | +616.3% |
| RGTI | 2025-04-21 | 2025-10-17 | +471.9% |
Ten worst closed signals
| Symbol | Entry | Exit | Return |
|---|---|---|---|
| RGTI | 2024-07-15 | 2024-08-05 | −33.1% |
| MDB | 2022-08-11 | 2022-09-08 | −32.9% |
| TER | 2025-02-26 | 2025-04-25 | −32.8% |
| TEM | 2025-06-18 | 2026-03-20 | −32% |
| IREN | 2024-07-26 | 2024-08-07 | −29.1% |
| IONQ | 2023-09-11 | 2023-09-27 | −27.6% |
| NU | 2024-09-19 | 2025-02-28 | −27.4% |
| AXTI | 2023-01-27 | 2023-02-24 | −22.9% |
| ON | 2024-02-22 | 2024-04-22 | −22.6% |
| MSTR | 2025-05-06 | 2025-10-21 | −21.7% |
Walk-forward validation, separate from this replay
The replay above inherits hindsight. The stricter test re-selects each name's rules every January on earlier data only and trades the next year, 2016 to 2026, after costs: across 144 names the class engine returned a median +18.5% a year versus +20.7% holding, with a median worst drawdown of -50% versus -57%, shallower on 128 of 144. The self-audit has the benchmarks and the per-name detail; the walk-forward rows are public JSON and the method is on the methodology page. Backtested, not live.
The honest fine print, before quoting the numbers
- These are the signals of TODAY'S engine replayed over history: the rules were researched and improved over time, so early-period signals are partly retrospective.
- The universe is today's catalog (survivorship-biased: it contains names that earned their place; delisted or faded names aren't represented).
- Returns are raw per-signal price returns (dividend-adjusted), end-of-day, without position sizing, costs or slippage; the in-app backtests apply 0.1% round-trip costs and vol-targeted sizing.
- A trend engine exits AFTER tops and enters AFTER bottoms by design; win rate matters less than the size of wins vs losses.
- Closed-signal statistics cover completed round trips only. Every still-running position is published alongside them (the 'open' list here, aggregated in stats_ext.open_book), marked at the last close and therefore unrealized: read the two together, because a record that banks its winners and leaves its losers open would look identical on the closed book alone.
- Past performance (measured or backtested) does not predict future results. Educational tool, not investment advice.
stats_ext) · Educational tool, not investment advice ·
Past performance (measured or backtested) does not predict future results.
Reading this with software? These statistics, their provenance and caveats are also a tool call away on the agent-verifiable evidence page, free and without an account.
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