Same program, three profit factors: the signal identifiers, the recomputation, and three corrections

The launch post for Execution Caliper leaned on one example: the same EA, run on three accounts, showing profit factors of 1.08, 1.79 and 2.39. I promised the signal identifiers, the recomputation and the three corrections to my own earlier tables, so the claim could be checked rather than trusted. This is that post. Every number below was recomputed this week from the exported trade lists on my disk; where I could not, I say so instead of repeating the figure. Nothing here is about my own products' performance or a verdict on the EA; it is a record of what the data says and of where I was wrong.

The signals

Two of the three accounts are public MQL5 signals. Signal 2195619, "The Gold Reaper Live default settings", runs on PepperstoneUK-Live and started on 3 February 2024. Signal 2265877, "Gold Reaper New V2 2", runs on CapitalPointTrading-MT5-4 and started on 22 October 2024. Both trade XAUUSD only. I took the closed-position exports of both in August: 1,283 positions for 2195619, from 7 February 2024 to 7 August 2026, and 830 for 2265877, from 29 October 2024 to 7 August 2026. Recomputed from those exports with commission and swap included, the profit factors are 1.794 and 2.400, against 1.79 and 2.39 displayed on the signal pages at the time; on the Profit column alone they are 1.814 and 2.457. The win rates are 71.9 and 71.7 percent net, 73.1 and 73.7 percent gross. Today the two pages show 1.81 and 2.34, with 1,323 and 870 trades and win rates of 72.33 and 72.41 percent, because both accounts have kept trading.

The third figure, 1.08, is different in kind. It comes from a Myfxbook account for the same program, quoted on a third-party website. I have no trade export for it, the signal pages do not show it, and I could not verify its period, its broker or its settings. It should not have stood beside the other two, and I do not use it here.

What the recomputation showed

The launch post said the three accounts covered the same period and differed only in fill prices. The exports do not support that. Signal 2195619 started eight and a half months before 2265877, and its first 424 positions, from February to October 2024, had a gross profit factor of 0.924 on their own. Cut both exports to the window they share, 29 October 2024 to 7 August 2026, and the net profit factors are 2.396 for 2195619 and 2.400 for 2265877, with net win rates of 72.4 and 71.7 percent.

To check that the two accounts took the same trades, I matched positions one to one by direction and opening time within three minutes: 760 pairs, 89 percent of one export and 92 percent of the other. Across those pairs the CapitalPointTrading account entered worse by a median of four cents per ounce, mean eight cents. For the 425 pairs that also closed within three minutes of each other, the round-trip difference had a median of zero. With an average losing trade of about $12.60 on 0.01 lot, the execution gap between these brokers was under one percent of a typical loss. The matched pairs give net profit factors of 2.355 and 2.348.

So the honest version of the example is this: the gap between 1.79 and 2.39 was the start date, not the account, and I pooled two periods while writing a paragraph about not pooling periods. The sentence in the launch post and the product description will be corrected. The general point survives only in a weaker form. The reviews on the 2265877 page as of today do not complain about the strategy; of the ten shown, three describe slippage and seven describe trades that did not copy at all, a fill problem of a different kind that this tool does not measure. The instrument measures the part that can be measured without sending an order.

Correction one: mixing symbols in one distribution

The cost-to-stop ratio I call the execution tax is round-trip cost divided by stop width. My first reference table, a working table behind the first design that was never posted here, took nineteen public signals with 69,236 closed positions and computed one ratio per signal, with the stop width taken as the 90th percentile of losing-trade size in pips across every symbol the signal traded. A pip of EURUSD, a pip of XAUUSD and a point of an index are not the same unit, so in a multi-symbol signal the symbol with the largest numbers dominated the percentile and the ratio came out small. Recomputed per signal and per symbol, with at least thirty losing trades per cell, there are 91 cells with a median of 2.40 percent, a 95th percentile of 13.06 and a maximum of 19.99. Inside one signal, 2361862 with nineteen scored symbols, the ratio runs from 1.74 percent on XAUUSD to 19.99 on NZDCHF, a factor of 11.5, and on 2373305 from 0.11 to 5.16, a factor of 46.9. Only the single-symbol rows of the first table survive unchanged; the multi-symbol rows cannot be regenerated from any script I kept, so the table is withdrawn rather than patched.

Correction two: thresholds chosen after the data

The first design had a green, amber, red verdict. The green boundary was set at eight percent because the largest per-signal value in that first table sat just below eight; the line was drawn from the data it was meant to judge. I had pre-registered a rule to kill the verdict if the recomputed boundary moved above fifteen percent, but not how many losing trades a cell needed before it counted. With thirty, the maximum is 19.99 percent and the verdict dies; with one hundred, 17.54 and it dies; with two hundred, 13.44 and it survives. A rule whose outcome depends on a choice made afterwards is not a rule, so the verdict was removed and the tool shows numbers only.

Correction three: pooling periods and brokers

Signal 2358336 trades mainly EURAUD and AUDCAD with fixed stops. Across all seven and a half years its EURAUD ratio is 4.00 percent; excluding 2020 it is 14.12. In 2020 the median and the 90th percentile of its losses were both exactly 50.0 pips, and the stop-loss distances in the export step from about 37 to 50 pips in the early years to 101 pips from 2024 on, so one percentile over the whole period averaged two parameter generations. On 2361862, the NZDCHF cell that produced the 19.99 percent maximum has 89 of its 112 positions in 2026 alone.

The broker side was worse. The tables used one assumed round-trip cost per asset class for every broker, 1.0 pip for a major pair. Spreads can be measured from an export: a buy opens at the ask and closes at the bid, a sell the opposite, so where one symbol shows an ask-side and a bid-side price in the same second, their difference is the spread. On signal 2384807, which pays no commission, EURUSD measured 3.25 pips, NZDUSD 3.50 and USDCHF 3.45, and its EURUSD ratio moves from 1.05 to 3.43 percent. On 2379915, which pays commission separately, AUDCAD measured 0.85 pips against an assumed 2.0. For crypto a flat 15 dollars is 1.65 basis points of one BTC contract and 56 basis points of one ETH contract; measured, the ETH spread on 2273131 is $1.94, and its ratio falls from 13.44 to 1.74 percent. These same-second pairs are few, four to fourteen per symbol, so read them as orders of magnitude, not precise values.

What the tool does about it

Each error now has a rule inside the instrument: one stop width per symbol, never a pooled percentile; costs measured on your own account and nowhere else, with no reference table; and not measured printed instead of an estimate when the data is missing. The red line at about twenty percent remains because it comes from my own EAs dying in live measurement; it says nothing about anyone else's.

How to reproduce

The trade lists are the positions exports of the two signals, at /en/signals/2195619/export/positions and /en/signals/2265877/export/positions, which need a logged-in session; mine were taken in the second week of August 2026, and the last position in each is dated 7 August 2026. Profit factor is the sum of profit over winning positions divided by the absolute sum over losing positions; net includes commission and swap, gross uses the Profit column alone. The execution tax is round-trip cost divided by stop width, where stop width is the 90th percentile of the absolute pip size of losing positions for one signal and one symbol, and round-trip cost is the measured spread plus commission converted to pips as the median of commission divided by profit per pip. The scripts and their printed output are kept with my working notes and are available on request.