FAILED

Inverted ascending scallop

The mirrored variant of the cup-and-handle in an uptrend.

Measured in crypto — Binance spot · 540 pairs, delisted ones included · 0.2% per round trip

Net per trade

−0.54%

after fees

The fee is charged on both legs: every trade pays to open and pays to close.

Died at

invariance

the result is not physically plausible

Worst drawdown

−2%

1,357 days underwater

How far the account fell below its own best previous moment.

Timeframe

1 day

The time grid this was measured on. The same technique on a coarser or finer grid is a different measurement, and can earn a different verdict.

invariance
costs
placebo
benchmark
out of sample
multiple testing

Equity curve

Risking 1.0% per trade, marked to market every day — not only when a trade closes. The line at 1.0 is the capital it started with.

At its worst the account was worth 2% less than its own best previous moment, and it spent 1,357 days below that peak.

The technique against chance

Same number of trades, same holding time, same assets — only the dates were drawn at random.

The average trade and the typical one

The mean sits BELOW the median: most trades win a little and the tail loses a lot. It is the lottery inverted, and no less dangerous — what decides the outcome is the rare loss.

What was measured

We coded the rule exactly as it is described and let it trade on its own from 2017-08-17 to 2026-07-28. It found trades in 45 coins, 204 in total. Each one enters and exits at the price that existed on that day — the program never sees what comes next, which is the most common mistake people make testing strategies at home. Wherever the description was ambiguous we took the reading least favourable to the technique; whatever was left open is stated in the hypothesis, at the foot of this page.

How many of those trades actually count

Only 102 of the 204. Cryptocurrencies rise and fall almost in unison, so the same rule fires on dozens of coins on the same day — and that is one bet repeated, not dozens of different bets. Counting them all separately is the trick that makes a bad test look impressive.

What it paid, before any deductions

-0.34% per trade. Look at the sign: the average is already negative before any fee is taken out. The controls below still hold, but here they are not knocking down an edge — they are confirming there never was one.

Why it did not pass — it died here · where the result came from

We look at where the result came from: whether it is spread across the trades or packed into a handful of them. It concentrated. That is the shape of a lottery: the typical trade loses, and a rare handful pays for everything. Anyone following the rule for real would face a long run of losses before any gain, and would almost certainly quit before it arrived.

What would have happened to the money

Risking 1.0% of capital per trade — the most widely taught rule — across the whole period: The capital would have ended at 0.99× what it started with. At its worst the account was worth 2% less than its own best previous moment, and it spent 1,357 days below that peak. In none of the 12 paths tested did it fall to less than half of what it started with.

What this result does NOT say

For an edge to be assertable here it would have to reach 4.54% per trade — that is the size that survives this archive's multiple-testing correction, and it rises as the archive grows. So FAILED means “we found nothing above that size”, and never “it cannot possibly work”. The instrument is far more sensitive than that: on synthetic data, with a clean effect, it separates from 0.69% upwards. The distance between the two numbers is the price of a real market and the price of publishing many claims. The difference matters, and it is the rule of this house: the card confronts the claim, never the person who made it.

What this card does not measure

Every verdict holds for the conditions it was measured under. These are this card's — and outside them the result does not apply.

One market, one universe: Measured on 45 spot cryptocurrency pairs, delisted ones included. It says nothing about futures, equities or indices, nor about how the same technique behaves in another market.
One window of time, not every window: The measured period runs from 2017-08-17 to 2026-07-28. A market moves through regimes, and a technique can work in one and fail in another — the card measures the regimes that fit inside this window, not the ones still to come.
One cost structure: The cost charged is 0.10% per leg, in and out. Anyone paying more than that gets a worse result, and anyone paying less gets a better one — the verdict holds for this fee.
One exit rule: The trade was closed by: the auditor's fixed horizon (10 bars). The same entry measured with a different exit is a different strategy, and can earn a different verdict — it happens in this archive.
The number of trades is not the sample size: There are 204 trades, but only 102 independent market episodes: a single move fires the technique across dozens of assets at once, and counting those as separate observations inflates any result. It is the smaller number that governs the arithmetic. With 102 episodes, what the data supports is a range from -0.93% to +0.25% per trade — the published average is the centre of it, not the exact measurement.
Daily bars: Measured at the daily close. Nothing here measures what happens inside the day, and an intraday technique is not auditable with this data.

Numbers and reproducibility

The six controls

control	status	t	threshold	episodes
invariance	failed	—	—	—
costs	failed	-1.82	1.98	102
placebo	inconclusive	-0.52	1.98	102
benchmark	failed	—	—	—
out of sample	failed	—	—	—
multiple testing	passed	—	—	—

invariance63% of the gross profit comes from 10 trades (5% of the total) — lottery
costsgross -0.343% · cost 0.200% · net -0.543% (t=-1.82)
placeboactual -0.543% · placebo -0.349% · excess -0.194% ± 0.373% (t=-0.52 against a threshold of 1.98, 102 real groups, 10,200 sham dates, draw error ±0.099%) — the status flips inside the placebo's own Monte Carlo error
benchmarktechnique -0.54% · buy and hold (same horizon) +0.38% · excess -0.93%
out of sampleasset half A: -0.630% (t=-2.36, 65 episodes) · asset half B: -0.446% (t=-1.03, 66 episodes) · liquid half (>= US$ 2,284,931/day): -0.329% (t=-1.56, 84 episodes) · illiquid half: -1.070% (t=-1.40, 40 episodes) · period 1/4 (2019-02-19 a 2022-02-07): -0.401% (t=-3.46, 23 episodes) · period 2/4 (2022-02-08 a 2023-10-09): -0.084% (t=-0.14, 28 episodes) · period 3/4 (2023-10-12 a 2025-01-28): -1.358% (t=-1.48, 28 episodes) · period 4/4 (2025-02-02 a 2026-07-10): -0.331% (t=-0.83, 26 episodes)
multiple testing1 variation(s) tested · t=-1.82 across 102 episodes (equivalent to t=-1.80) · p≈0.0715 · false positives expected by chance ≈ 0.07

Equity — outside the six controls, and here is why

The t of the trade series is invariant to bet size: 0.5%, 1% and 3% agree to the sixth decimal. Nothing here moves the verdict — it moves what the account would have lived through.

risking 1.0% per trade: ×0.99
worst drawdown from the peak: −2%
days below the previous peak: 1,357
signals refused for lack of capital: 0%
paths where the account halved (out of 12): 0

Reproducibility

period: 2017-08-17 to 2026-07-28
assets that traded: 45
variations tested before this one: 1
gross per trade: −0.34%
net per trade: −0.54%
exit rule: the auditor's fixed horizon (10 bars)
horizon bars: 10
fee per leg: 0.001
episode days: 10
confirmation bars: 5
tolerance: 0.03
max window: 120

Binance spot klines (delisted pairs included) · collected from 2026-07-27 23:31 to 2026-07-28 14:29 · 540 assets · 750,934 bars · 2017-08-17 to 2026-07-28

Seed not recorded: audits before 2026-07-29 used 20260728 by convention in the code, and the value is not in the record.

Hypothesis, filed before the result

Chart patterns are the best-known class in technical analysis and the one most damaged by the pivot error: almost every published backtest marks the signal on the pivot's own date, when on that date nobody knew it was one. Measured with a CAUSAL pivot — five bars of confirmation lag, which is what a real trader faces — I expect them to come out WORSE than the candlestick patterns, and for a legitimate reason: by the time the break is recognisable, the price has already moved. Specific, falsifiable prediction: none survives the Benjamini-Hochberg correction across the 52 patterns, and the control that kills the most will be the benchmark, not costs — unlike the candlesticks, because these trade far less often.

filed on 2026-07-28, before the number existed

The original, as it was filed

Padrões gráficos são a classe mais famosa da análise técnica e a que mais sofre com o erro de pivô: quase todo backtest publicado marca o sinal na data do pivô, quando naquela data ninguém sabia dele. Medidos com pivô CAUSAL — 5 velas de atraso de confirmação, que é o que o operador real enfrenta — espero que saiam PIORES que os de vela, e por um motivo legítimo: quando o rompimento é reconhecível, o preço já andou. Previsão específica e falsificável: nenhum sobrevive ao Benjamini-Hochberg de 52 padrões, e o controle que mais mata será o benchmark, não o custo — diferente dos de vela, porque estes operam bem menos vezes.

Pre-registration exists to keep prediction apart from rationalisation: written after the number, every hypothesis is right.

Earlier audits of the same technique

Each variation an author teaches enters as its own test, so that whatever might work in the strategy gets covered. The verdict held in all of them.

2026-08-03FAILEDopen ↗
2026-08-03FAILEDopen ↗
this measurement →FAILED
2026-07-28FAILEDopen ↗
2026-07-28FAILEDopen ↗