FAILED

Averaging down on new losses (up to 5 units, every 1 day(s), 60-day average)

If the trend's direction is right, a worse price is a better opportunity: adding to the position on each new loss improves the average entry price, and the trade needs less favourable movement to turn a profit.

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

Net per trade

+3.38%

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

−47%

597 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 47% less than its own best previous moment, and it spent 597 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 2017-08-17 to 2026-07-28. It found trades in 540 coins, 40,281 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 29 of the 40,281. 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

+3.58% per trade. This is the number the technique claims, and the only one on this page that has not yet been through a single control.

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. To give the measure: 72% of the profit came from the top 5% of trades, and the same technique with its dates shuffled would concentrate 54%. The control fails above 50%.

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 9.20× what it started with. At its worst the account was worth 47% less than its own best previous moment, and it spent 597 days below that peak. In none of the 12 paths tested did it fall to less than half of what it started with.

The account would not fit every signal

64% of the trades had to be turned down: by the time they appeared, the money was already tied up in other positions. That matters because the average return per trade the technique claims is computed over trades that nobody could have taken all of.

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 540 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 technique itself, entering in tranches (weighted average price). 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 40,281 trades, but only 29 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 29 episodes, what the data supports is a range from -1.61% to +8.78% 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	inconclusive	1.33	2.05	29
placebo	inconclusive	1.36	2.05	29
benchmark	passed	—	—	—
out of sample	passed	—	—	—
multiple testing	inconclusive	—	—	—

invariance72% of the gross profit comes from 2014 trades (5% of the total) — lotteryconcentration: +72.30% of the profit sits in the top 5% of trades — with the dates shuffled, +54.28% (fails above +50.00%)
costsgross +3.581% · cost 0.200% · net +3.381% (t=1.33) · the range runs from -1.814% to +8.577%
placeboactual +3.381% · placebo -0.123% · excess +3.505% ± 2.569% (t=1.36 against a threshold of 2.05, 29 real groups, 2,014,050 sham dates, draw error ±0.032%)
benchmarktechnique +3.38% · buy and hold (same horizon) +1.17% · excess +2.21%
out of sampleasset half A: +3.864% (t=1.25, 29 episodes) · asset half B: +2.926% (t=1.39, 29 episodes) · liquid half (>= US$ 2,066,613/day): +4.165% (t=1.51, 29 episodes) · illiquid half: +2.492% (t=1.02, 28 episodes) · period 1/4 (47792136-10-22 a 52339800-05-07): +10.750% (t=2.29, 15 episodes) · period 2/4 (52342538-04-03 a 53878504-02-01): +1.796% (6 episodes — too small, does not count) · period 3/4 (53881241-12-28 a 55348760-02-24): +1.606% (6 episodes — too small, does not count) · period 4/4 (55351498-01-20 a 56569866-09-03): -0.589% (5 episodes — too small, does not count)
multiple testing4 variation(s) tested · t=1.33 across 29 episodes (equivalent to t=1.28) · p≈0.2021 · 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: ×9.20
worst drawdown from the peak: −47%
days below the previous peak: 597
signals refused for lack of capital: 64%
paths where the account halved (out of 12): 0

Reproducibility

period: 2017-08-17 to 2026-07-28
assets that traded: 540
variations tested before this one: 4
gross per trade: +3.58%
net per trade: +3.38%
exit rule: the technique itself, entering in tranches (weighted average price)
measured return: per unit of position opened — NOT weighted by capital allocated
median duration bars: 3
mean duration bars: 17.1
max duration bars: 356
fee per leg: 0.001
episode days: 112
seed: 20260728
pyramid on: loss
tranche spacing: 1
tranches: 5
scaled pyramid: 0
slope period: 60

Binance spot klines (delisted pairs included) · collected from 2026-07-27 23:31 to 2026-08-03 10:49 · 540 assets · 750,934 bars · 2017-08-17 to 2026-07-28

Hypothesis, filed before the result

The third limited case on p. 1082 and the mirror of the inverted pyramid: «run the same Adding to Profits test but reverse the logic, so that we are adding to losses. Equal positions were added after at least n days, provided the open position was making new losses greater than remaining at the previous loss». Same 60-day base, same grid of n in {1, 3, 5, 10}. THE SOURCE ALREADY REJECTS IT IN 3 OF 4 MARKETS: «Apple was the only market in which averaging down improved long-term performance, in both total profit and profit factor. The other three test markets produced noticeably worse results for all delay combinations». AND IT PREDICTS AGAINST THE TECHNIQUE ITSELF: «we would expect either of the other methods, entering in tranches or adding to profits, to produce better results». The source justifies it by prevalence, not by merit: «because the practice of averaging down is widespread in the equity markets, we would be negligent not to run the same test». Audited by the average entry price, with the published weighting caveat. Family-level prediction, recorded before measuring: (1) NONE survives the corpus-wide Benjamini-Hochberg; (2) the FRACTIONAL ENTRY and the two PYRAMIDS ON PROFIT will move the mean by LESS THAN THE ERROR BAR and will NARROW the deviation — it is the mechanism the protocol has already measured twice, at breakeven (median from −2.75% to 0.00%, mean unchanged) and at partial profit taking (−0.023% ± 0.518%, deviation from 19.9% to 12.4%): position management moves the SHAPE and is read as if it had moved the CENTRE; (3) the EQUITY CURVE GATE fails, and for lack of autocorrelation — this is the family's most falsifiable prediction, because the number already exists in the corpus: the source states that «first one must find out whether returns are positively autocorrelated», and `confirmacoes.py` publishes, over 742,175 crypto days, that daily direction is a coin flip WITH NO MEMORY; (4) AVERAGING DOWN will be the worst in the family and will die at CONTROL 1, concentration, because adding to losses fattens the tail — and the source itself already rejects it in 3 of 4 markets; (5) the gravedigger in crypto will be CONTROL 1 and not the benchmark, which is the correction of the prediction refuted in part 76 and what part 74 had already established: in crypto, what pays a lot pays it concentrated; (6) the 80-day BASE will do better than any layer built on top of it.

filed on 2026-08-04, before the number existed

The original, as it was filed

O terceiro caso limitado da p. 1082 e o espelho da pirâmide invertida: «rodar o mesmo teste de Adicionar nos Lucros mas inverter a lógica, de modo que estamos adicionando nas perdas. Posições iguais foram acrescentadas depois de pelo menos n dias, desde que a posição aberta estivesse fazendo novas perdas maiores do que permanecer na perda anterior». Mesma base de 60 dias, mesma grade n em {1, 3, 5, 10}. ⚠️ A FONTE JÁ A REPROVA EM 3 DE 4 MERCADOS: «a Apple foi o único mercado no qual a média para baixo melhorou o desempenho de longo prazo, tanto em lucro total quanto em fator de lucro. Os outros três mercados de teste produziram resultados sensivelmente piores para todas as combinações de atraso». ⚠️ E ELA MESMA PREVÊ CONTRA A TÉCNICA: «esperaríamos que qualquer um dos outros métodos, entrar em parcelas ou adicionar nos lucros, produza resultados melhores». ⚠️ A fonte a justifica pela prevalência, não pelo mérito: «como a prática de fazer média para baixo é difundida nos mercados de ações, seríamos negligentes se não rodássemos o mesmo teste». ⚠️ Auditada pelo preço médio de entrada, com a ressalva de ponderação publicada. Previsão da família, registrada antes de medir: (1) NENHUMA sobrevive ao Benjamini-Hochberg do corpus; (2) a ENTRADA FRACIONADA e as duas PIRÂMIDES SOBRE LUCRO moverão a média por MENOS QUE A BARRA DE ERRO e ESTREITARÃO o desvio — é o mecanismo que o protocolo já mediu duas vezes, no breakeven (mediana de −2,75% para 0,00%, média parada) e na realização parcial (−0,023% ± 0,518%, desvio de 19,9% para 12,4%): gestão de posição mexe no FORMATO e é lida como se tivesse mexido no CENTRO; (3) o GATE PELA CURVA DE PATRIMÔNIO reprova, e por falta de autocorrelação — esta é a previsão mais falsificável da família, porque o número já existe no corpus: a fonte declara que «primeiro é preciso descobrir se os retornos são positivamente autocorrelacionados», e `confirmacoes.py` publica, em 742.175 dias de cripto, que a direção diária é cara-ou-coroa SEM MEMÓRIA; (4) a MÉDIA PARA BAIXO será a pior da família e morrerá no CONTROLE 1, concentração, porque adicionar nas perdas engorda a cauda — e a própria fonte já a reprova em 3 de 4 mercados; (5) o coveiro em cripto será o CONTROLE 1 e não o benchmark, que é a correção da previsão refutada na parte 76 e o que a parte 74 já tinha estabelecido: em cripto, o que rende muito rende concentrado; (6) a BASE de 80 dias irá melhor que qualquer camada sobre ela.

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.

cryptoFAILED← this one
forexFAILEDopen that card

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