Behaviour leaves numbers behind
Most writing on trading psychology talks about mindset. That is hard to act on, because you cannot measure a mindset. You can measure what it does to your trades. Every decision you make under pressure (cutting a winner early, moving a stop, adding size to win something back) shows up in times, prices and sizes that your broker already records.
This guide looks at behaviour only through that data. It is not about diagnosing anyone, and it makes no medical claims. If trading is affecting your wellbeing or finances in a way that worries you, talk to someone qualified; a spreadsheet is not the right tool for that.
What a journal can do is turn "I think I get nervous" into "my losing trades are held almost three times as long as my winners". The second sentence has a fix.
Six behaviours and the column that measures each
| Behaviour | What to measure | Warning sign |
|---|---|---|
| Cutting winners, holding losers | Average hold time and average R for winners vs losers | Losers held much longer; average loss larger than planned 1R |
| Moving the stop | Planned stop vs actual exit on losing trades | Losses beyond −1R |
| Revenge after a loss | Minutes since last losing close, risk vs median | Fast, oversized trades after losses |
| Overtrading | Trades per day vs plan, results by trade number | Trades past the limit lose money |
| Hesitation | Planned entry vs actual entry price | Entries consistently late, worse R:R |
| Size drift | Risk per trade over time | Risk rises after win streaks or losses |
Each row needs only a column or two. The trading journal spreadsheet covers the core fields; add a planned stop and planned entry if you do not log them yet.
Worked example: when the win rate hides the problem
A trader reviews 50 trades. The win rate is 60%, which feels good. The journal shows:
- Average winner: +$80, held a median of 12 minutes.
- Average loser: −$140, held a median of 34 minutes.
- Planned risk per trade: $90 (the stop distance times shares).
Expectancy = 0.60 × 80 + 0.40 × (−140) = 48 − 56 = −$8 per trade. A 60% win rate and the account still shrinks.
With a payoff of 80 ÷ 140 = 0.57, the break-even win rate is 1 ÷ (1 + 0.57) = 63.6%. The trader needs to win nearly two trades in three just to stand still.
Now the behaviour. The planned loss was $90, but the average loss was $140, so the stop is being moved or ignored on many losers. Winners are closed in a third of the time losers are held. Those two facts describe a habit, not bad luck.
If losers had been closed at the planned stop, the average loss would be −$90, and expectancy = 0.60 × 80 + 0.40 × (−90) = +$12 per trade. Same entries, same win rate, and a change of $20 per trade, from −$8 to +$12. This is an illustration, and real exits would not all land exactly at the stop, but it shows where the leak is.
You can repeat this with your own numbers in the R-multiple calculator. Losses beyond −1R are the clearest sign a stop was moved. The guide on win rate vs risk:reward has the break-even table.
Practical habits that make the numbers better
Emotions are part of trading. The practical question is how to make them matter less to the result. Habits that are easy to check in a journal:
- Write the stop before entry, and log it. You cannot measure stop discipline without the planned stop.
- Size from a formula, not a feeling. Position size = (account × risk %) ÷ |entry − stop|, rounded down. The position size calculator does it in seconds.
- Use brackets or OCO orders where your broker supports them, so the exit is decided when you are calm.
- A short pre-trade line: setup name and why. Trades with no line are your first suspects.
- A stop rule for the day: a trade count or loss limit that ends the session.
Do not add them all at once. Start with the one tied to your most expensive behaviour from the table above, and add the next only when the first has held for a month. Each habit leaves a trace, so next month you can see whether you kept it.
A monthly behaviour check
Once a month, answer these from the data, not from memory:
- What share of losing trades closed beyond −1R?
- Median hold time of winners vs losers: how far apart?
- How many trades opened within your cooldown after a loss, and what did they make?
- How many days exceeded your trade limit, and what did the extra trades make?
- How many trades had no setup tag?
- Did risk per trade stay within plan?
Write the six numbers down each month. A single month is noisy; the trend over three or four months tells you whether your habits are changing. A journal app that imports fills from your broker, such as TradeGreen, computes win rate, profit factor, R and expectancy per setup automatically, which leaves you the behavioural questions.
For the full review routine, see how to review your trades.
Where to go next
Two of the behaviours above have their own guides because they are so common: revenge trading and overtrading. If you are not sure which leak is the costly one, start with why you might be losing money day trading, which shows how to group trades by setup and time of day.
A journal will not change how you feel during a trade. It makes the cost of each habit visible, which tends to be a stronger argument for change than any amount of advice.