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Test a Signal Seller's Claims With Arithmetic

Situation: a service advertises an 85 percent win rate, with winners averaging 10 pips. In the small print, losses average 60 pips. They charge 99 dollars a month. Does this make money?

Compute expectancy in pips. Winners: 0.85 times 10 is 8.5 pips. Losers: 0.15 times 60 is 9.0 pips. Net: minus 0.5 pips per trade before costs.

Add costs. With a spread of 1.5 pips per trade, expectancy becomes minus 2.0 pips per trade.

The headline win rate hides a negative edge. To break even at those payoffs, the win rate would need to be 60 divided by 70, which is 85.7 percent, so even a service hitting its claimed rate loses slightly, and costs make it worse.

Now scale. If the service sends 20 signals a month and you trade 0.20 lots, one pip is 2 dollars. Monthly expectancy is minus 2.0 times 20 times 2, which is minus 80 dollars, plus the 99-dollar fee. Total monthly cost: about 179 dollars.

This pattern is typical of strategies that take small profits and let losses run: the curve is smooth until a large loss arrives, and a run of such losses can erase months of gains.

Questions to ask: what is the verified track record, how long, and in what account? What is the maximum drawdown? Are all signals included?

If the seller presents only the win rate, treat it as a red flag.

Exercise: compute the break-even win rate for any advertised payoff structure.

A signal arrives by message at 10:32:05. The entry price in it was the price at 10:32:00. By the time the message is read, the order is placed, and the fill is received, it might be 10:32:25.

On a slow-moving pair, that's fine. For a scalping signal with a three pip target, it often means the first pip or two of the move is gone, the spread is paid at a worse moment, and the stop is closer than intended.

Multiplied across hundreds of followers all hitting the market at the same time, the entry price also deteriorates.

A fair evaluation of a signal service uses timestamps. Record the time each signal was posted, the price in the message, and the price at which a real order would have filled a few seconds later. The difference, averaged over a month, is the delay cost.

Services that post results using their own entry prices, not follower-realistic ones, overstate what's achievable.

Some providers deliberately target slower setups for exactly this reason, with wider stops and longer holding times that tolerate the lag.

How much of a signal's stated profit survived the delay between posting and entry?