Pattern Reality Check / Fair value gap

PATTERN REALITY CHECK · SMART MONEY AND LEVELS · TESTED 8 OCT 2026

Fair value gap: does it work after costs?

Three candles leave a gap that the middle one covers. Courses say price comes back to fill it.

Small positive result, not confirmed

Verdict

Small positive result, not confirmed

The average is slightly positive, but the result does not pass our strict test and does not hold up across all periods.

Average per trade+6.7%+0.067Rof the amount risked, after costs and funding. 95% range: +1.6% to +11.8%.

Trades tested10,52129 coins2020-06-02 to 2026-09-23, 4-hour candles.

Trades won38%needs 36% to break evenWins averaged +1.871R, losses -1.039R.

Against random entries100%of random runs beatenRandom entries averaged -4.7%, because costs hit every trade. Beating them is not enough: the average must also be clearly above zero.

Read with care. Limit orders are assumed to fill whenever price touches the level. Real fills are worse, because the touches that do not fill are often the winners. This makes the result optimistic.

Why "not confirmed". The average is above zero and its 95% range stays above zero. It does not pass our stricter bar: the 99% range includes zero, and the held-back period is not positive. The limit-order fill test below shows the result depends on how generously fills are assumed. Treat it as a hint to test further, not as evidence.

Percentages are % of the amount risked per trade. New to R? Read this first.

What courses teach

The idea

Another "smart money" idea. When a strong candle leaves a gap between the first and third candle, that gap is a "fair value gap", said to be an imbalance that price will revisit and respect.

The rules we froze

These numbers are the usual textbook values. They were written before we saw a single result and were not changed afterwards.

PartRule, fixed before the test

Signal

Three candles where the middle one is at least 1 ATR and the low of the third is above the high of the first (or the mirror), a gap of at least 0.5 ATR.

Entry

Limit order at the near edge of the gap, filled if price returns within 40 candles without closing through the gap.

Stop

0.25 ATR beyond the first candle. At least 1 ATR from entry.

Target

Twice the distance to the stop (2R).

Time limit

Closed after 60 candles (10 days) if neither stop nor target was hit.

Costs

0.14% round trip plus real funding, charged on every trade.

What it looks like

Examples, good and bad

Two real trades picked by a fixed rule, not for being pretty, and six drawn at random from the held-back period (the most recent two years). 3 of the 6 won. Examples show the rule, they are not results: the results are the numbers further down.

Fair value gap example that reached the target

Fair value gap example that was stopped out

Results

Trade after trade

All 10,521 trades added up, with the three periods shaded. The right axis shows euros if you risked €100 on each trade. The dashed line is what random entries would have done.

By period

The same average, split by period. The black bars are the 95% range: if they cross zero, we cannot tell the result from luck.

PeriodTradesAverage per tradeTrades won95% range

Build

4,959

+11.2% +0.112R

39.5%

+4.6% to +17.8%

Validation

3,560

+8.7% +0.087R

38.5%

-0.8% to +18.6%

Held-back

2,002

-7.8% -0.078R

33.5%

-18.2% to +3.1%

By version

VersionTradesAverage per tradeTrades won

Long

5,461

+8.6% +0.086R

38.6%

Short

5,060

+4.7% +0.047R

37.4%

How the trades ended

The honest yardstick

Compared with entering at random

A pattern should beat luck, not zero. We ran 1,000 simulations that enter at random times on the same coins and periods, in the same direction, with the same stop distance, target and time limit.

Fair value gap compared with random entries

In plain words

Why the numbers look like this

Random entries lose too. Entering at random times with the same stops and targets averaged -4.7% per trade (-0.047R) because of fees, funding and spread. The pattern averaged +6.7% and did better than 100% of 1,000 random runs. That is the honest comparison: not zero, but what luck plus costs produce.

Before costs: +11.9%. After costs: +6.7%. Fees, funding and slippage took 5.2% of the amount risked from every trade, on average.

Win rate versus break-even. It won 38.0% of trades. With average wins of +1.871R and losses of -1.039R, it needed 35.7% to break even. The win rate is above what it needs, which is what a positive result looks like.

Consistency across time. The average was positive in 2 of 3 periods. A real edge should not depend on which period you look at.

Sensitivity. Across 32 variations of the rule, 30 were positive and 2 negative. The best variation (+10.3%, 21,390 trades) is not a result: with 32 variations, a few green cells appear by chance. We look for a broad green region.

Stress tests

Does it survive changes?

Changing the pattern shape

Each cell is the same test with a different setting. The outlined cell is the rule we froze. Green is positive, red negative. We do not pick the best cell: we look for a broad region.

Changing the exits

Same idea for the target and the stop.

Changing the costs

CostsAverage per trade

No costs, funding only

+11.5% +0.115R

Half the costs

+9.1% +0.091R

Our costs (0.14% + funding)

+6.7% +0.067R

Double costs

+2.0% +0.020R

Triple costs

-2.7% -0.027R

Stricter limit-order fills

Limit orders rest at a level and fill when price touches it. In real markets, a touch is often not a fill: your order sits in a queue, and the touches that do not fill tend to be the ones that reverse in your favour. To test this, we kept only the trades where price went further through the level.

Fill ruleTradesAverage per tradeHeld-back period

Our assumption: filled when price touches the level

10,521

+6.7% +0.067R

-7.8%

Filled only if price trades 0.1 ATR through the level

8,280

-2.3% -0.023R

-16.8%

Filled only if price trades 0.25 ATR through the level

5,416

-13.3% -0.133R

-29.1%

If the result were real, it should survive a stricter fill. It does not: the more demanding the fill, the lower the average.

Another timeframe

On daily candles the same rule gave +13.6% over 1,592 trades.

Coin by coin

24 of 29 coins had a positive average. With a few dozen trades per coin, some are always positive by chance.

Limits

What this does not say

It does not say fair value gap never works. It says this version of the rule, applied to every case, shows small positive result, not confirmed in this data.
It is a simulation. Real fills, delays and emotions make results worse.
The market may change. Results from the past are not a forecast.
We publish tests of popular patterns, we do not publish or comment on strategies we use ourselves.

Method: how we test · Errors: corrections · Education only, not investment advice.

Questions

Questions about fair value gap

Does fair value gap work in crypto?

In our test of 10,521 trades on 29 crypto perpetuals, with real costs and funding, the average result was +0.067R per trade (+6.7% of the amount risked). Verdict: small positive result, not confirmed. This applies to the textbook rule defined on this page, not to every way of using it.

Why do I see charts where fair value gap worked?

Because any rule produces winning examples. A chart that shows a winner says nothing about how often the same rule fails. The test above applies the rule to every case, with costs, without picking.

What would make this result change?

A different timeframe or market, different exits, or filters that add information the pattern does not contain. We tested a second timeframe and 32 variations of the rule; the numbers are on this page.

How should I read the percentages?

They are percentages of the amount you risk per trade, not of your account or of the coin price. +6.7% means +6.7% of the amount risked, on average. See what is R.