FAILED

Moving average crossover (20/50) · exit by Parabolic

A trend technique delivers its result despite the trades that turn against it, not because of them. Cutting each trade as soon as price moves far enough from its own best point takes the loss before the technique itself notices the turn — and what remains is better than having no stop at all, provided the level adapts to volatility instead of being a fixed amount.

Measured in forex — EUR/USD and GBP/USD · daily bars built from 15m · 1 pip spread (~0.009% per round trip) · no survivorship bias

Net per trade

−0.02%

after fees

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

Died at

benchmark

loses to buy and hold (same horizon)

Worst drawdown

−0%

1,257 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 0% less than its own best previous moment, and it spent 1,257 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 above the median: the lottery signature — the typical trade loses and a rare handful pays for everything.

What was measured

We coded the rule exactly as it is described and let it trade on its own from 2020-01-01 to 2026-06-26. It found trades in 2 coins, 88 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 76 of the 88. 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

-0.01% 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 · against buying and holding

We compare it against simply buying and holding for the same stretch of time, with no rule at all. Sitting still paid more. The technique takes work, demands attention, and delivers less than doing nothing.

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 1.00× what it started with. At its worst the account was worth 0% less than its own best previous moment, and it spent 1,257 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 0.65% 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 0.09% 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 2 spot currency pairs. 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 2020-01-01 to 2026-06-26. 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 a 1.0 pip spread, crossed once. 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 technique itself (held until the opposite signal). 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 88 trades, but only 76 independent market episodes: trades that overlap in time are not independent observations, and counting them as if they were inflates any result. It is the smaller number that governs the arithmetic. With 76 episodes, what the data supports is a range from -0.20% to +0.17% 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	passed	—	—	—
costs	inconclusive	-0.25	1.99	76
placebo	inconclusive	-0.07	1.99	76
benchmark	failed	—	—	—
out of sample	inconclusive	—	—	—
multiple testing	inconclusive	—	—	—

invariance88 signals across 4055 barsconcentration: +35.47% of the profit sits in the top 5% of trades — with the dates shuffled, +37.94% (fails above +50.00%)
costsgross -0.015% · cost 0.008% · net -0.023% (t=-0.25) · the range runs from -0.211% to +0.164%
placeboactual -0.023% · placebo -0.017% · excess -0.007% ± 0.095% (t=-0.07 against a threshold of 1.99, 76 real groups, 4,400 sham dates, draw error ±0.017%) — the status flips inside the placebo's own Monte Carlo error
benchmarktechnique -0.02% · buy and hold (same horizon) +0.00% · excess -0.03%
out of sampleasset half A: -0.070% (t=-0.49, 44 episodes) · asset half B: +0.023% (t=0.22, 43 episodes) · liquid half (>= US$ 0/day): -0.023% (t=-0.25, 76 episodes) · period 1/4 (2020-03-10 a 2021-09-27): -0.054% (t=-0.27, 21 episodes) · period 2/4 (2021-10-29 a 2023-03-28): -0.004% (t=-0.02, 20 episodes) · period 3/4 (2023-05-22 a 2024-08-21): +0.044% (t=0.26, 17 episodes) · period 4/4 (2024-10-10 a 2026-05-29): -0.078% (t=-0.51, 18 episodes)
multiple testing1 variation(s) tested · t=-0.25 across 76 episodes (equivalent to t=-0.24) · p≈0.8078 · false positives expected by chance ≈ 0.81

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: ×1.00
worst drawdown from the peak: −0%
days below the previous peak: 1,257
signals refused for lack of capital: 0%
paths where the account halved (out of 12): 0

Reproducibility

period: 2020-01-01 to 2026-06-26
assets that traded: 2
variations tested before this one: 1
gross per trade: −0.01%
net per trade: −0.02%
exit rule: the technique itself (held until the opposite signal)
median duration bars: 4
mean duration bars: 5.5
max duration bars: 20
spread pips: 1.0
episode days: 7
seed: 20260728
fast average: 20
slow average: 50
stop line: parabolic
base: Moving average crossover (20/50)

Twelve Data forex (15m aggregated to 1d) · collected on 2026-07-25 · 2 assets · 4,055 bars · 2020-01-01 to 2026-06-26

Hypothesis, filed before the result

Advancing the stop by a percentage of the price change, as in the parabolic system. The parameters are those of the card already published since chapter 17 (0.02 to 0.20), so that what is measured is the USE as a stop and not the ruler. This one advances and never retreats — the source cites it as the example of a stop that does not back away. Family-level prediction, recorded before measuring: (1) the stop IMPROVES concentration and worsens the mean — it cuts the right tail along with the left, and control 1 is where the 20/50 crossover already dies; if any card in this family changes its verdict relative to the base, I expect it to be by clearing the invariant, not by gaining return; (2) the VOLATILITY stops will do better than the fixed percentage, because that is what the source claims («the ones most likely to work need to adapt to volatility, and not to a fixed value in money or percentage of price») and the claim is testable; (3) the 12 × average true range of 252 will almost never be touched — it is far too wide a stop for crypto, and will measure practically the same thing as the base with no stop; (4) the profit TARGETS will do worse than the stops, because the source's own table shows that the best result for the slow average was WITHOUT profit taking; (5) none survives the family's Benjamini-Hochberg. MEASURED IN FOREX (EUR/USD and GBP/USD, daily aggregated from 15m), and not in crypto. This is a pre-registered REPLICATION of the same technique in the second market — not a new discovery —, and the multiple-testing count treats it as such. What changes: 2 pairs over 6.5 years against 670 symbols over 9, the cost of turnover is ~20× lower, the detection floor is ~10× lower (0.092% against 0.97%) and there is no survivorship bias. And there is one difference that matters especially to this family: a 3% stop is enormous in forex and tight in crypto — the same rule, measured in two markets, is not the same severity.

filed on 2026-08-03, before the number existed

The original, as it was filed

Avançar o stop por um percentual da variação do preço, como no sistema parabólico. Os parâmetros são os do card já publicado desde o capítulo 17 (0,02 a 0,20), para que a diferença medida seja o USO como stop e não a régua. ⚠️ Este avança e nunca recua — a fonte o cita como o exemplo de stop que não recua. Previsão da família, registrada antes de medir: (1) o stop MELHORA a concentração e piora a média — ele corta a cauda direita junto com a esquerda, e o controle 1 é onde o cruzamento 20/50 já morre; se algum card desta família mudar de veredito em relação à base, espero que seja por sair do invariante, não por ganhar retorno; (2) os stops de VOLATILIDADE irão melhor que o percentual fixo, porque é isso que a fonte afirma («os que têm mais chance de funcionar precisam se adaptar à volatilidade, e não a um valor fixo em dinheiro ou percentual do preço») e a afirmação é testável; (3) o 12 × amplitude real de 252 dias quase nunca será tocado — é um stop largo demais para cripto, e vai medir praticamente a mesma coisa que a base sem stop; (4) os ALVOS de lucro irão pior que os stops, porque a própria fonte mostra na tabela dela que o melhor resultado da média lenta foi SEM tomada de lucro; (5) nenhuma sobrevive ao Benjamini-Hochberg da família. ⚠️ MEDIDO EM FOREX (EUR/USD e GBP/USD, diário agregado de 15m), e não em cripto. Isto é uma REPLICAÇÃO pré-registrada da mesma técnica no segundo mercado — não uma descoberta nova —, e a conta de múltiplos testes a trata como tal. O que muda: 2 pares em 6,5 anos contra 670 símbolos em 9, o custo do giro é ~20× menor, o piso de detecção é ~10× menor (0,092% contra 0,97%) e não há viés de sobrevivência. ⚠️ E há uma diferença que importa especialmente a esta família: um stop de 3% é enorme em forex e apertado em cripto — a mesma regra, medida em dois mercados, não é a mesma severidade.

Quotations from the source were translated from the Portuguese record and back into English — they are not the author's exact words.

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

The same technique in the other market

The verdict held in the other market too, on independent data.

forexFAILED← this one
cryptoFAILEDopen that card

This claim has been audited once — there is no history to compare against.