A Futures Trading Journal That Tracks Tick-Level Edge

A journal built on entry, exit and P&L answers exactly one question — did I win? — and none of the ones that keep you funded: which setup, which session, which contract, and whether the edge is still there. The useful data lives in the fields most traders never log.

What to capture on every futures trade

Start with the fields that let you reconstruct the decision, not just the result. Six categories cover it:

Contract and expiry — ES, NQ, or a micro. Tick value and behaviour change completely between them.
Direction and size — number of contracts, and whether you scaled in or out.
Entry and exit price, plus the stop and target you intended at entry. The intended risk is what makes a trade measurable after the fact.
Timestamps to the minute — session and time-of-day are among the strongest predictors of whether a setup pays.
Setup tag — the named pattern you were trading, not a freeform sentence.
Net P&L — after commissions and fees, expressed in dollars and in ticks.

Get these on every trade and you can already compute a real expectancy. Skip any of them and you’re back to guessing from memory.

Tick-level fields most journals miss

This is where a futures-native log pulls ahead of a generic one — the fields that turn a P&L receipt into an edge read.

Ticks of risk and ticks of reward. Logging in ticks, not just dollars, makes trades comparable across contract sizes and across days when you traded a mini one session and a micro the next. Ticks are the true unit of a futures edge.
Maximum adverse excursion (MAE). How many ticks did the trade dig against you before it worked? A setup that constantly goes deep before paying is telling you your entries are loose, even when the win rate looks clean.
Maximum favourable excursion (MFE). How far did a winner run before you exited? Consistently large MFE means you’re leaving ticks on the table and your exit logic needs attention.
Slippage. The gap between the fill you intended and the fill you got, on entry and on the stop. On fast index futures this quietly erodes the edge, and you can only manage what you record.

These fields are tedious to type by hand, which is precisely why most traders don’t — and why the ones who automate capture end up with far cleaner data. Shibiki reads the fills straight from the broker and writes the tick math, MAE and MFE for you, so the tedious part happens whether or not you feel like journaling that night.

Tagging by contract, session and setup

Raw trades are noise until you can slice them, and three tag dimensions do most of the work:

By contract — your edge on NQ is not your edge on ES; aggregating them hides both.
By session — the RTH open behaves nothing like the London-hours move or the afternoon drift. Tag it so you can find the hours where your setup actually earns.
By setup — a consistent, named tag per pattern is what lets you rank setups by expectancy and cut the ones that never clear their costs.

The discipline that matters is naming things the same way every time. “Breakout,” “bo,” and “range break” are three tags to a computer and will fragment your sample until nothing has enough trades to judge. Pick a fixed vocabulary and hold to it. This is exactly where a hand-kept spreadsheet rots — the Shibiki vs. a spreadsheet comparison walks through why consistent tagging is the first thing to slip.

From logged trades to live expectancy

Once the fields and tags are consistent, expectancy falls out almost for free. Expectancy is your average result per trade — win rate times average win, minus loss rate times average loss — and expressed per contract in ticks it’s the cleanest single measure of whether a setup deserves your risk. If the math is new to you, the trading expectancy primer walks it through step by step.

The reason to keep it live rather than reviewing monthly: expectancy drifts. A live read recomputes every time a trade closes, so you see the trend instead of a stale snapshot. Shibiki attaches each trade to its strategy and maintains a running expectancy per setup, per contract, so the figure on screen is always current.

Catching edge decay before it costs you

The dangerous failure mode isn’t a strategy that never worked — it’s one that worked, then stopped, while you kept sizing up on faith.

A single win rate can’t separate a real slump from ordinary variance. That’s why Shibiki wraps each strategy’s edge in a Wilson confidence interval: instead of one point estimate, you see the plausible range your true win rate sits in given how many trades you’ve actually logged. A tight interval that has slid decisively negative is genuine decay. A wide interval on a dozen trades is just a small sample — and the honest response is to keep size modest until the sample grows, not to declare the setup dead or alive on a hunch.

That’s the part a spreadsheet can’t do, and a real gap against generic tools. If you’re weighing options, the Shibiki vs. TradeZella comparison lays out where automated tick-level capture and confidence-interval edge health change the workflow. The point was never more logging — it’s logging that turns into a decision: keep, tune, or kill, made on evidence rather than the last three trades you happen to remember.