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FAILED

Moving average crossover (20/50)

The moving-average crossover identifies the trend's turn in time to get into it: buying the upward cross and selling the downward one captures the main move and keeps you off the wrong side of the market. You hold until the opposite cross.

Measured in cryptoBinance spot · 540 pairs, delisted ones included · 0.2% per round trip

Net per trade
+7.70%
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
not measured
Equity was not measured for this claim.
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
The technique against chance
Same number of trades, same holding time, same assets — only the dates were drawn at random.
0%barthe technique+7.70%random dates−0.23%
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.
0%mean+7.90%median−4.31%

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, 14,459 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 84 of the 14,459. 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

+7.90% 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.

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 (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 14,459 trades, but only 84 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 84 episodes, what the data supports is a range from -1.20% to +16.99% 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

controlstatustthresholdepisodes
invariancefailed
costspassed1.681.9984
placeboinconclusive1.711.9984
benchmarkpassed
out of sampleinconclusive
multiple testingpassed
  • invariance59% of the gross profit comes from 722 trades (5% of the total) — lottery
  • costsgross +7.896% · cost 0.200% · net +7.696% (t=1.68)
  • placeboactual +7.696% · placebo -0.233% · excess +7.929% ± 4.624% (t=1.71 against a threshold of 1.99, 84 real groups, 722,950 sham dates, draw error ±0.085%)
  • benchmarktechnique +7.70% · buy and hold (same horizon) +3.64% · excess +4.06%
  • out of sampleasset half A: +7.902% (t=1.63, 84 groups) · asset half B: +7.490% (t=1.58, 83 groups) · period 1/4 (2017-10-11 a 2022-05-10): +30.067% (t=3.63, 44 groups) · period 2/4 (2022-05-11 a 2023-10-30): +0.683% (t=0.18, 15 groups) · period 3/4 (2023-10-31 a 2025-02-28): +2.874% (t=0.57, 13 groups) · period 4/4 (2025-03-01 a 2026-07-27): -2.850% (t=-1.25, 14 groups)
  • multiple testing1 variation(s) tested · t=1.68 across 84 episodes (equivalent to t=1.66) · p≈0.0972 · false positives expected by chance ≈ 0.10

Reproducibility

period
2017-08-17 to 2026-07-28
assets that traded
540
variations tested before this one
1
gross per trade
+7.90%
net per trade
+7.70%
exit rule
the technique itself (held until the opposite signal)
median duration bars
38
mean duration bars
46.7
max duration bars
283
fee per leg
0.001
episode days
38
fast average
20
slow average
50

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

The moving average crossover is a transformation of past price. I expect: gross edge close to zero, and whatever little there is being eaten by the fee — the pattern measured across four independent arenas on 2026-07-27.

the filing date is not in this audit's record

The original, as it was filed

O cruzamento de médias é uma transformação do preço passado. Espero: vantagem bruta próxima de zero, e o pouco que houver sendo consumido pela taxa — o padrão medido em quatro arenas independentes em 2026-07-27.

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.

  1. 2026-08-07FAILEDopen ↗
  2. 2026-08-03FAILEDopen ↗
  3. 2026-08-03FAILEDopen ↗
  4. 2026-07-28FAILEDopen ↗
  5. 2026-07-28FAILEDopen ↗
  6. this measurement →FAILED
  7. 2026-07-28FAILEDopen ↗
  8. 2026-07-28FAILEDopen ↗
  9. 2026-07-28FAILEDopen ↗

record 5fe1b5e4575f · 2026-07-28 14:48

This code comes from this card's content: if anything here changed after publishing, the code would stop matching — that's how a change gets caught. We audit the technique, never the person — no record names an author, a channel or a brand.

The full record behind this verdict. No seed (predates 2026-07-29): the placebo may not replicate.