We don't publish how our strategies decide. That makes how we measure them the only thing you can hold us to — so it is written down here in full, with numbers.
Every level published on the brief is written to a journal at the moment it is published, and graded automatically against that journal — never by hand, never in hindsight. A level either triggers or it does not. If it triggers, the outcome is scored from the entry we published to the exit the system took.
Results are scored after modelled spread, slippage and — where the instrument carries it — overnight financing. A win that only exists at mid-price is not a win. We also compute, for every engine, the round-trip cost at which its edge would reach zero: our fixed-target breakout book breaks even at about 47 basis points, our trend book at around 142. A strategy that needs flawless execution to survive does not survive.
When a single bar touches both the stop and the target, we book the stop. That biases our own record against us, which is the correct direction for a published record to lean.
Expired orders, losing trades and flat days are counted. “No trade today” is a result. We do not list every untriggered order one by one — most are the same idea re-quoted as its level drifts, and printing them as a wall of failures overstates the misses as badly as hiding them would understate them — but the total sits on the record page beside the number that actually traded.
A strategy is not called validated until it has at least 30 resolved trades in forward, out-of-sample data. Anything still accruing that sample is labelled as exactly that. Today, one of our strategies has passed every gate we apply, and its forward count stands at 23 of the 30 required — which is why the record describes it that way rather than as a finished result.
Before a strategy is trusted, the same code is run on pure noise — synthetic price series with no edge in them at all. If it still returns a profit there, that profit was manufactured by the measurement rather than found in the market, and the strategy is rejected however good its real backtest looked. This has caught our own work more than once: one system produced a convincing edge on noise and was deleted; another looked strong for a year until a fill-convention error was found, and its result went from strongly positive to strongly negative on the identical trades.
Research questions are written up — including what result would kill the idea — and committed to a timestamped repository before the test runs. That makes it impossible for us to move the goalposts afterwards. Several of those documents record us predicting an outcome and turning out to be wrong.
The large majority of ideas we test are rejected, and rejected by the tests above rather than by taste. Systems that run on our own screens but have not survived the noise test do not appear on the record at all — being interesting, or being something we personally watch, earns nothing here.
One book on our record has a thirteen-year validated history and is currently losing money on its live forward sample. Both numbers are printed side by side. A backtest that never has to meet its forward record is marketing.
The common convention among signal providers is to grade at spot price, assume perfect fills, count a take-profit as won the moment price touches it, and quote gains to the peak. We do none of those things — which makes our numbers look smaller and mean more.