Day trading Setup + session tags Weekly review loop

Day Trading Journal

Day trading is fast. That’s exactly why your journal needs a low-friction schema and a strict weekly review using real metrics (not vibes).

Direct answer

A day trading journal is a system for logging trades with planned risk, costs, and setup/session tags so you can review weekly using expectancy and profit factor. The goal is to measure edge per trade and remove what isn’t working-fast.

Who this is for

This day trading journaling system is built for traders who want evidence and repeatable improvement.

High-frequency decision makers

If you take multiple trades per session, your journal must be quick and structured to avoid drift.

Traders who manage risk professionally

You track planned risk and evaluate performance in R, not just dollars.

Setup-focused traders

You want “this setup works here” clarity-not a blended average.

Weekly reviewers

You’re willing to run a weekly review loop and make changes based on data.

What to track

If your day trading journal doesn’t track these, your review becomes opinions.

Track this Why it matters Review use
Planned risk (R-ready) Lets you compare trades fairly, even with variable size. Compute expectancy in R.
Costs (commissions/spread) Day trading edge is small; costs can erase it. Use net P&L for metrics.
Setup tag Turns trades into categories you can improve. PF/expectancy by setup.
Time bucket / session Edges appear/disappear in different periods. Performance by hour/session.
Entry/stop/target plan Allows compliance review and execution analysis. Find rule-break patterns.
Short note (1–2 lines) Captures context without bloating the workflow. Link conditions to outcomes.

Weekly review workflow

Day trading requires fast learning cycles. This weekly loop keeps you focused on what actually moves performance.

1) Clean your dataset (10 minutes)

Fix missing tags and confirm costs are included. A dirty dataset produces fake insights.

2) Segment by setup + session (15 minutes)

Your overall stats are a blend. Real edge is usually setup-specific and time-window-specific.

3) Run metrics (15 minutes)

Compute expectancy and profit factor by segment, then rank by sample size and consistency.

4) Make decisions (keep / modify / cut)

This is the point of a journal. Decide what setups you will trade next week and what rules you’ll change.

Day trading futures?

Futures day trading has session effects and cost sensitivity. Use the futures guide.

Common mistakes

Most day trading journals fail because they log activity instead of creating reviewable evidence.

  • Tracking only win rate and ignoring risk normalization.
  • Missing costs (commissions/spread) and using gross P&L.
  • Inconsistent setup tags (tags drift = insights die).
  • No weekly review (journaling without decisions is just logging).
  • Journaling too many fields (you stop doing it).

FAQ

Day trading journal

A day trading journal logs trades with planned risk, costs, and tags so you can review weekly using expectancy and profit factor. The goal is to find which setups and sessions produce edge and remove what doesn’t.

Day trading journal template

A day trading journal template should include instrument, time, entry/stop/target plan, planned risk, size, costs, net P&L, realized R, setup tags, session tags, and short notes. Start here: day trading journal template.

Best day trading journal

The best day trading journal measures results after costs and normalizes by risk. It supports tagging and fast segmentation by setup and session, and it makes weekly review using expectancy and profit factor repeatable.

How to journal trades

To journal trades, record the plan (entry/stop/target), planned risk, outcome after costs, and tags for setup and session. Then review weekly by setup using expectancy and profit factor to improve decisions.