From boring spreadsheet to your sharpest edge: building a journal that actually improves your trading

If you’re stuck in a cycle of making progress and then giving it back, the problem may not always be the strategy itself. It can also be the absence of a reliable feedback loop.

A trading journal should be more than a spreadsheet you update occasionally. Used properly, it becomes a record of what you actually did, the conditions surrounding each decision, and whether the strategy is performing the way you think it is.

One useful way to build a journal is in three levels, starting with basic trade data and gradually adding behavioural and performance analysis.

Level 1: The Data Collector

When you’re starting out, the first job of the journal is to capture hard data.

This provides the minimum information needed to begin evaluating whether a trading approach has produced a repeatable statistical result across a meaningful sample of trades.

What Belongs in Level 1

Instrument and time: what did you trade, and when did you enter and exit?

Direction and size: was the position long or short? What position size did you use, and what percentage of the account was at risk?

Entry reason: what specific rule authorised the trade?

Keep this mechanical. For example, it might be a VWAP reaction, an inside bar, a break of structure, a liquidity-based setup or another predefined condition within your strategy.

Outcome: did the position reach the stop loss, take-profit target or another planned exit? Was it closed manually? What risk-reward result was actually achieved?

A common mistake is reconstructing trades from memory days later.

Memory can be selective, particularly after emotionally significant wins or losses. Recording trades shortly after the session gives you a more reliable record of what actually happened.

Level 2: The Psychological Mirror

Once you’ve collected enough basic information to understand how the strategy is behaving, the next step is to record how you are actually executing it.

The journal now becomes more than a collection of numbers. It starts recording the context surrounding your decisions.

Before-and-After Screenshots

Take a screenshot when you enter and another when the trade finishes.

The entry screenshot preserves what the chart looked like when the decision was made. The exit screenshot shows how the market subsequently developed.

Reviewing both together can help distinguish between a trade that followed the original plan and one where the reasoning changed after the fact.

Setup Grading

You can also classify trades according to how closely they matched your predefined rules.

A-grade setup: all required strategy conditions were present. The trade can still lose while remaining a correctly executed trade.

B-grade setup: most conditions were present, but one or more elements were weaker, early or less clearly defined.

C-grade setup: the trade did not properly meet the strategy criteria and may have been driven by impulse, FOMO or another discretionary decision.

The exact grading system is less important than applying it consistently.

Emotional State

Record your emotional and physical state before entering.

You might use a simple scale from 1 to 5 and add a short note:

Were you calm?

Were you tired?

Were you frustrated after a previous loss?

Were you tempted to recover money quickly?

Over time, this information can help you test whether certain emotional states are associated with more rule violations or poorer execution.

Don’t assume in advance that psychology is responsible for most losses. Let your own journal data show whether the problem is the strategy, the execution, or a combination of both.

Level 3: The Optimizer

Once a journal contains enough consistent data, it can be used for more detailed performance analysis.

The objective is not necessarily to find another strategy. It is to identify where the existing process performs well, where it performs poorly and which changes are worth testing.

MFE: Maximum Favorable Excursion

Maximum Favorable Excursion (MFE) measures how far a trade moved in your favour while the position was open.

For example, imagine your strategy normally exits at 2R, but your journal shows that many trades subsequently reached considerably further before reversing.

That information may justify testing alternative exit methods, such as partial profit-taking, larger targets or trailing techniques.

It does not automatically mean that a larger target or trailing stop will improve profitability. Any change needs to be tested because increasing the target can also reduce the percentage of trades that actually reach it.

MAE: Maximum Adverse Excursion

Maximum Adverse Excursion (MAE) measures how far a trade moved against you while it remained open.

MAE data can help you understand whether your stop-loss placement matches the normal behaviour of the setup.

For example, if profitable trades rarely move beyond a certain adverse distance before recovering, that may give you a reason to test whether stop placement can be refined.

Again, tighter stops do not automatically improve performance. A smaller stop can increase the apparent risk-reward ratio while simultaneously causing more trades to be stopped out.

The journal gives you evidence to test the change rather than relying on intuition.

Filtering by Time and Day

Your results can also be filtered by variables such as:

Day of the week

Trading session

Time of entry

Instrument

Setup type

Market condition

For example, your data might eventually show materially different results between trades taken during one session and another.

If a pattern persists across a sufficiently large sample, you can then test whether restricting certain trading periods improves the overall strategy.

Be careful with very small samples. Five strong Wednesday trades or five poor Friday trades are not enough by themselves to establish a reliable trading rule.

Turning the Journal Into a Feedback Loop

The real value of journaling comes from repeatedly moving through the same cycle:

Trade. Execute the predefined strategy.

Record. Capture the numbers, screenshots and context.

Review. Separate strategy losses from execution mistakes.

Measure. Look for patterns across a meaningful sample.

Test. Change one variable at a time and compare the results.

Repeat. Continue collecting evidence rather than relying on memory or intuition.

What This Comes Down To

Start with the facts. Record the instrument, timing, position size, entry reason and result of every trade.

Add the context. Screenshots, setup grading and emotional notes can reveal execution problems that raw profit-and-loss numbers cannot.

Use MFE and MAE carefully. They can help identify potential improvements to exits and stops, but any modification still needs to be tested.

Segment your results. Time, day, market, setup and market conditions may reveal where the strategy performs differently.

Let the data challenge your assumptions. Don’t decide beforehand whether the problem is psychology, risk management or the strategy itself. Use the journal to find out.

Conclusion

Traders often spend considerable time searching for new strategies, tools and external opinions while overlooking the evidence generated by their own trading.

A well-maintained journal cannot guarantee profitability, but it can give you something far more useful than memory: a structured record of your decisions and results.

Start taking the screenshots. Grade the setups consistently. Record the context. Build enough data to identify genuine patterns rather than isolated outcomes.

The better your records become, the easier it becomes to understand what is actually helping your trading — and what is holding it back.