Journaling Backtest Trades (Template Included)

Why the Journal Is Non-Negotiable

A replay session without logging is a feeling — “that went well.” A session with logging is data you can interrogate: what’s the expectancy, where’s the drawdown, does the edge live in one session? Every metric and every cost audit on this site reads from the journal. It’s also the instrument that later measures your discipline gap: replay a live period and compare logs.

The Minimal Template

Column	Captures	Powers
Date/time (server)	When, in the data’s clock	Session/regime segmentation
Setup tag	Which rule fired	Per-setup expectancy
Direction	Long/short	Directional bias check
Entry / Stop / Target	The plan	R:R, fill realism
Exit	What happened	Result
Result (R)	Normalized P/L	Expectancy, equity curve
Session	Asia/London/NY/overlap	Session segmentation
Nights held	Overnight count (+2 Wed)	Swap cost
Spread / Commission	Per-trade costs	Net result
Note	”entered late,” “hesitated”	Execution findings

Result in R (multiples of risk), not money — R normalizes across position sizes so the stats describe the strategy, not your account.

Fill It In Live, Not From Memory

The cardinal rule: log each trade the moment it closes, inside the replay session. Reconstructing a journal afterward from a finished chart reintroduces hindsight bias — you’ll “remember” the trades more favorably than they were. The note field especially must be live: “hesitated on entry,” “moved stop early” are execution truths you won’t recall honestly later, and they’re often the most valuable lines in the whole journal.

Tool-Assisted vs Manual

Replay tools that simulate trades usually record the mechanical columns automatically — entry, exit, result, running win/loss and expectancy (tick tools like StrategyTune track P&L and stats as you trade). That covers the numbers, which is most of the value. Two things stay manual regardless of tool:

1. Cost columns — no replay tool models swap or commission, so those columns live in your own sheet, applied to the exported trade list.
2. The note/setup-tag field — your read of why and how well, which only you can record.

A practical hybrid: trade in the tool (auto-stats + hidden-future enforcement), export the trade list, and finish the cost audit and segmentation in Excel.

From Journal to Decision

Once the journal holds 100+ trades: compute the five metrics, plot the equity curve, segment by session and regime, run the cost stress test. Every one of those reads straight from the columns above — which is why the boring discipline of logging is what makes the interesting analysis possible.

Frequently Asked Questions

What's the single most important journal column?

Result in R, because expectancy, drawdown and the equity curve all derive from it and it normalizes across position sizes. A close second is the note field — execution observations like hesitation or early exits are where you learn the difference between the strategy's edge and your ability to capture it.

Should I journal during the replay or after?

During — log each trade the instant it closes. Journaling after the session from a completed chart lets hindsight bias recolor the trades, and you'll never reconstruct the honest note field ('hesitated,' 'entered late') accurately. Live logging is part of what keeps the backtest valid.

Do I need a journal if my replay tool tracks stats automatically?

The tool covers the mechanical numbers, which is most of the value — but you still need your own columns for costs it doesn't model (swap, commission) and for the setup tags and notes only you can record. Think of it as tool-stats plus a thin personal layer, not either/or.

Why log result in R instead of pips or money?

R (the trade's profit/loss as a multiple of the amount risked) makes every trade comparable regardless of stop size or position size, so a +2R win on a wide-stop trade and a +2R win on a tight-stop trade count equally. Pips ignore stop size; money ignores sizing. R isolates the strategy's actual performance.