Confluence filters: 0 of 5 crypto stacks beat random

Source: Confluence trading, widespread

One filter cut profit factor from 1.87 to 0.95. It threw out the good trades.

On small samples, most confluence claims can't be checked at all.

This verdict is about the strategy as published, not about the person who shared it.

The claim

Here’s what the strategy promises, in its own terms.

A signal too weak to trade alone still helps as a filter on another strategy.

How we tested it

Same six checks as everything else here: random entries, coin flips, a look-ahead audit, unseen years, double costs and a luck check. How we test →

What we found

Ten stacks were written down before testing (5 gold, 5 crypto). On crypto, 0 of 5 beat a control that used a random secondary signal with the same firing rate. Worse, one filter cut the base strategy's profit factor from 1.87 to 0.95 while keeping 63% of trades: it removed the good trades. The trap: at a 4:1 reward-to-risk and 18% win rate, a random filter reaches profit factor 2.3-5.1 on 50 trades at the 95th percentile, so most confluence claims on small samples cannot be falsified at all.

The numbers

The headline numbers from our test.

Stacks preregistered	10
Crypto stacks beating random	0
Filter effect PF	1.87 -> 0.95
Trades kept	63%
Random filter PF 95th-pct n=50	2.3-5.1

• Profit factor: money won divided by money lost. Below 1.0 loses money. Around 1.0 is break-even.
• R-multiple: profit or loss measured in units of the amount risked per trade. +1R means you made what you risked.
• vs random: how the strategy did against the same trades with random entries.