Why a glossary needs formulas
Look up "profit factor" and every source gives the same sentence: gross profit divided by gross loss. Then load the same trades into two journals and read two different numbers.
The definitions are not wrong. They are incomplete, because the interesting part of any metric is not the formula — it is what happens at the edges:
- What does profit factor return when there were no losing trades? Infinity is not a number you can put on a dashboard, and zero would be a lie.
- Does "profit" mean before or after commission? Both are defensible; they are not the same number.
- Is drawdown measured on closed equity or including open positions? A prop firm's answer to that decides whether your account survives.
- Is a break-even trade a win, a loss, or neither? It changes your win rate.
None of these are exotic. They come up in the first hundred trades of any account, and a glossary that skips them is a glossary you cannot reconcile against your own spreadsheet.
What each entry contains
Every page in this section gives four things:
- The formula, written so you can reproduce it by hand.
- The edge case — the situation where implementations disagree.
- What our code does at that edge, stated plainly so a figure in our app can be checked rather than believed.
- What the number is actually good for, and where it misleads.
The bias worth knowing about
These entries describe metrics as our own product computes them. That is the point — it makes the numbers auditable — but it also means the edge-case choices are ours, and another journal may legitimately choose differently.
Where a choice is genuinely a judgement call rather than a standard, the page says so. Where there is a real convention and we follow it, the page says that too.
Where to start
If you are reconciling a figure that looks wrong, start with net P&L — most disagreements between two tools trace back to costs being counted twice or not at all, before any ratio is even involved.