Aim Volatility Labby Bao Research
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How we grade ourselves

Most trading tools publish their wins. We built a system that grades every recommendation — and every refusal — against the do-nothing alternative, in public, with receipts.

896 decisions enrolled722 matured & graded2 refusals on the ledgergate registry v1
Instant Verdict hit-rate83% hits across 12 matured verdicts10 hit · 1 partial · 1 missEvery verdict is graded ~20 bars later against what actually happened: a trade-worthy call must go positive AND beat buy-and-hold to count as a hit; a no-edge refusal is a hit when doing nothing was right. Watch/wait verdicts made no directional claim, so they're shown but never scored.

We built this scoreboard before knowing what the score would be. The ledger below started counting on July 29, 2026 — whatever it says in a quarter, it says in public.

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We grade the regime detector too

Every verdict stamps the market regime the detector saw at issue. Twenty trading days later we also record whether that regime persisted or transitioned — and score the verdict separately in each stratum. If the detector is informative, verdicts should survive persistence better than transitions. A verdict on the detector itself is only issued once both strata reach n≥5 matured checks.

Regime at issueMaturedRegime persistedRegime transitionedDetector verdict
strong uptrend349109 of 219 verdicts held27 of 130 verdicts survivedinformative
moderate trend23123 of 39 verdicts held109 of 192 verdicts survivedinformative
strong downtrend6319 of 34 verdicts held8 of 29 verdicts survivedinformative
range-bound6112 of 20 verdicts held17 of 41 verdicts survivedinformative

18 matured receipts carry no regime stamp (enrolled before stamping shipped) — excluded, not hidden.

Meanwhile on our structural board: ▲31 JPMPL climbed to rank 60 (Strong Downtrend) this week — the screener hunts engine-friendly structure, and its picks are graded against a control group.

Our stock screener is graded too

Our internal screener hunts engine-friendly structure — and enrolls its top picks AND a control group of mid-ranked names into the same forward ledger. Matured so far: picks showed a validated out-of-sample edge in 10 of 11 re-races, controls in 10 of 10 — a gap of -9.1 pts, published whichever way it lands.

Every recommendation becomes a receipt

When our optimizer recommends a configuration — or refuses and says "keep your baseline" — that decision is enrolled in a forward ledger automatically. Twenty trading days later, we grade it: did the chosen config actually beat keeping the baseline on the exact same forward bars? Then again at 60 days and a quarter. The grade measures the decision, not the stock — a recommendation on a stock that fell can still be right if it lost less than the baseline would have.

We grade our refusals too

When the optimizer finds no configuration that honestly beats what you already have, it says so — and that refusal is enrolled and graded like any other decision. A refusal scores as correct when the baseline wins the forward window. Nobody else grades their own no’s; we think it’s the most important grade on the page.

The ledger is hash-chained

Each receipt carries a SHA-256 hash of its contents chained to the previous receipt, so the history cannot be quietly edited, backdated, or pruned after the fact. A broken chain is detectable by anyone. The same construction protects our public regime-forecast calibration ledger.

Counts, never percentages — pooled across users

Matured receipts pool across all users by ticker, engine, and configuration (within tolerance). We report them as counts — "beat baseline in 7 of 9 matured checks" — never as polished percentages, and we claim nothing below five matured receipts. Small samples get labeled as small samples.

The gates that judge results are versioned

The thresholds behind every verdict — what counts as validated, what triggers an overfit warning, when a drawdown is flagged — live in an append-only registry, currently v1. Any change must be pre-registered: declared with a future effective date and the receipt evidence motivating it, then graded only on receipts that mature AFTER the change. We never retro-fit a threshold to the ledger that motivated it and call it verified.

Live positions are never touched

Gates and thresholds apply at decision time only. Positions snapshot their full parameters at entry, and no system change — gate version, memory update, anything — reaches back into an open position. Improvements affect the next decision, presented as evidence before you act, and strategy-level changes always end at a human decision.

All results are hypothetical backtests and forward paper-grades, not live trading or advice. The one promise this page makes: the grades will be published whether they flatter us or not.

Aim Volatility Labby Bao Research

Rules-based AIM backtesting for volatile markets. Compare engines, validate out-of-sample, and find out when your edge is fake.

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© 2026 Bao Research. AIM Volatility Lab. All rights reserved.

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Backtested and simulated results are hypothetical, do not reflect live trading, and do not guarantee future performance. AIM Lab is a research and educational tool and is not financial, investment, or trading advice. AIM = Automatic Investment Management.

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