A journal records what you planned and what you actually did. A few consistently completed fields can help you review trades without overreading a small sample or a single win.
A quiet review at the desk: documentation begins with an honest note.Image: TradeNeon
Record the trade. Review the decision.
A journal keeps plan, execution and review distinct.
Many people new to trading underestimate the value of a journal. After a trade, you know the outcome, but not necessarily the reasons behind it. A journal records what you planned before entry, what you did during the trade and what you observed afterwards. It lets you compare decisions with your rules, learn from mistakes and examine your strategy.
The essentials
A journal does not make you profitable by itself. It can help you separate plan from execution, spot repeated deviations and formulate specific questions for your next review.
01
Why keep a trading journal?
Trading requires you to consider many variables: the market, entry, position size, risk and how to manage an open position. When a trade goes wrong, memory alone often cannot tell you which assumption or decision mattered. A journal brings order to the process. You record more than wins and losses: you record the circumstances that produced them.
A profitable trade can still break your rules; a losing trade can follow a carefully made plan. Keeping the idea, planned exit and actual execution separate helps you assess the decision itself. Across several trades with the same setup, potential errors and recurring patterns become easier to see. Were entries repeatedly late? Did you take more trades than planned after a loss? Such overtradingOvertrading means taking too many trades or selecting them too loosely rather than choosing opportunities that meet your plan. is easier to recognise in documented decisions than from a memory of one day.
There is a psychological side as well. Note when you felt uncertain, moved an exit out of fear or overlooked a rule out of excitement. This helps you examine which decisions drew on information and which were driven more by emotion. Regular review can help you take responsibility for your process and follow your trading plan more deliberately. It cannot make a strategy profitable on its own.
02
What to record in your journal
A journal combines basic trade data with your thoughts before, during and after the trade. The details that matter depend on your approach. These four areas give you a starting point you can adjust later:
01 · DataWhat did you trade?
Date and time, instrument, direction and position size, entry and exit price or ticks gained, plus the stop price or risk taken.
02 · ReasonsWhy this trade?
The setup or strategy and your analysis: what factors supported the idea, and what counted against it?
03 · EmotionsHow did you feel?
Before the trade, perhaps confident or nervous; during it, doubtful, afraid or greedy; afterwards, satisfied, frustrated or relieved. A short rating scale may help.
04 · ReviewWhat will you take away?
What went well and what did not? Did you follow the plan? Why did the trade unfold as it did, and what will you check next time?
Where useful, add the actual order execution, costs and changes to the plan. The important point is that your notes let you distinguish the planned trade from the executed one.
A mainly statistical approach may need different priorities from a day trading approach in which you make decisions under pressure for minutes or hours. We each have our own habits of thought and behaviour. Prioritise the fields that answer your most important questions instead of collecting every metric you can think of.
03
What a journal entry can look like
A journal can bring the trade idea, emotions, review and chart sketches together. This view shows one way to do it. Both entries are fictional; they show no real trades or results.
Journal · example viewFictional entries
Day & setup
Idea and plan
Execution & feeling
Review & chart
12 MarchBreakout retest
Enter only after a pullback. Stop and size decided before the order.
Rules followed as planned.Feeling: Tense but patient.
Plan followed. Check the news calendar before the next trade.
14 MarchPullback
Enter at the pullback. Stop decided in advance.
Stop moved on impulse.Feeling: Pressure not to miss out.
Mark the deviation. Use the checklist before the next order.
The chart sketches are placeholders. Your own screenshot can help if it shows the areas you marked before entry and the actual execution. An image without a plan or comment tells you little.
04
Turn records into useful questions
Review your journal regularly and group trades by setup, market or rule deviation. Ask first: Which decisions recur? Which losses occurred within the plan, and which followed a change in your process? What actually worked in your winning trades? This lets you learn from mistakes, examine your strategy and recognise emotional decisions rather than looking only at the outcome column.
Keep observations separate from guesses. A short sequence of good or bad trades can be misleading. Look for recurring patterns before turning individual results into a new rule.
A journal is useful only if you maintain it. A very detailed entry can take considerable time for each trade, making the habit hard to sustain. Begin with a few fields and a regular routine. Once you use them consistently, you can examine individual aspects in more depth. “Think big, start small” serves this task better than a form you abandon after a week.
A short weekly review
One recurring pattern · one specific rule deviation · one question to test with more trades.
05
Paper, spreadsheet or software?
A traditional notebook may motivate you if you enjoy writing by hand. Entering every trade and comparing the data later takes time, though. A spreadsheet in Excel or Google Sheets is flexible, can be adapted to your approach and can handle calculations and basic analysis. The fictional example above shows one possible structure; it does not require dedicated journal software.
Specialist programs can import trading data and display statistics clearly. They often cost more and limit you to the fields and functions they provide. Check whether they also let you record your emotions before, during and after a trade, along with your own learning questions. None of these formats replaces an honest record. Choose a method that suits your approach and that you will keep using.
A trading journal makes your process easier to understand: you can see whether you followed your plan, which patterns recur and what you want to work on. Its exact form is up to you. Start with basic data and a short reflection; once that routine holds, you can expand your review.
TradeNeon Academy
Review is part of learning
If you want to develop your trading rules, risk management and trade review within a training programme, see the current paths in the Academy. These programmes are currently taught in German.
No. It makes decisions and deviations easier to review. Whether a strategy is viable and whether you can execute it still need separate evaluation.
Should I record every trade?
If you want to find repeated patterns in your decisions, record trades using the same criteria. A collection of remembered winners or losers can distort your review.
Which fields matter most at the beginning?
Market, date, setup, planned entry and stop, position size, actual execution and a brief review note make a workable first process.
How often should I review my journal?
Record each trade promptly. A regular short review is more useful than a long form you stop completing. The right rhythm depends on how often you trade.
Simon Reichert is a swing trading coach at TradeNeon. He studied International Business Management, worked in finance and auditing, and has traded actively since 2022. His focus is swing trading, the broader market context and risk management.
Statistics in Trading: The Tool Behind Your Decisions
Oliver Sparing
Founder & Head of Trading · TradeNeon
Webinar in German, May 30, 2024 · 68 min video
Whether you trade by fixed rules or decide from experience, every trading decision rests on probabilities. If you know the numbers of your own trading, you doubt less often after losses and change things less spontaneously, even though no evaluation creates certainty. The risk quadrant and a trading journal show you where your levers are.
Only together do many single trades form a picture.Image: TradeNeon
Numbers instead of doubt.
Anyone who has evaluated their approach does not have to decide anew after every loss whether it still holds.
Statistical trading follows a fixed set of rules, while discretionary trading rests on collecting objective information from the market and deciding yourself on the basis of your experience. Doubt about your own approach is a common trigger of psychological problems in trading, and evaluated numbers can reduce that doubt. You can evaluate with a trading journal, the risk quadrant of reward-to-risk ratio, hit rate, trading frequency and risk per trade, and the study of individual market situations.
“Everything we do in trading is based on statistics in some form.”
Oliver Sparing
Anyone who follows only their own gut feeling, or a tip over the garden fence, will sooner or later have to deal with the market. Fewer people are aware that statistics also plays a big role in discretionary trading.
That is why it pays to first sort out what statistical tradingTrading according to a fixed set of rules that can be modeled mathematically or algorithmically. and discretionary tradingTrading in which the trader's experience and interpretation play the biggest role. The trader makes the decision to buy or sell. are, and to be aware of which of the two categories you are in or want to be in.
03
Statistical trading: then and now
In statistical trading, you follow a set of rules that can be modeled mathematically or algorithmically. Classic examples are entry rules such as the crossing of two moving averages. A well-known example of a fixed rule-based system is the Turtle Traders: in the 1980s, a group of traders with no prior experience learned a fixed, rule-based system from two experienced traders.
Such systems wear out when many traders use them: anyone who trades by the same well-known rules places the same orders at the same time. Those orders move the market, and the advantage of the approach fades. That is why it is hard today to find something lasting with a classic rule-based system. Two further reasons add to it. First, dozens or hundreds of people had most ideas before you, and the institutional algorithms in the market know such strategies and know where to find liquidity. Second, market phases change faster than they used to, so a trader has to adapt more often.
Oliver tested a system of his own extensively, and it ran well for a while. Then the idea was transferred to many markets and variants and checked with a backtestTesting a trading idea against historical data. over a long period. It turned out that exactly this setting in exactly this market had been luck and that the system had no lasting edgeA statistical advantage in the market that a trading approach has in the long run.. Trading purely by rules with an algorithm is the most demanding trading discipline, and strategies often work for only a limited time, so the next one has to be ready.
04
Discretionary trading
In discretionary trading, you do not trade like an algorithm; your experience and your interpretation play the biggest role. That is not a gut feeling in the sense of guessing. A certain intuition develops with time in front of the screen, but it rests on pattern recognitionRecognizing market situations you have seen many times and knowing how the market usually behaves afterward.: you have seen certain situations hundreds of times and know how the market most likely behaves afterward.
The core is to collect objective information the market gives you. The market follows certain rules and mechanics that can be learned and understood. Once you have gathered enough information, you form your own opinion about what the market is likely to do next. Whether you click buy or sell is decided by your head. That is the discretionary part.
The approach rests on the fact that markets are made for people and that in the end supply and demand move prices. Once you have understood how the auction process works at the exchange and how institutional market participants such as large funds or market makers trade, you can put these concepts to use and develop your own trading systems. Concepts to learn include how an order book works and how to analyze market structure.
05
Statistics and psychology
This is where the focus lies for everyone who is still on the way to stable trading. Stage fright is a comparable case: it arises whenever you are not sure of your own cause and do not know whether you are prepared well enough. Then you begin to doubt. Trading is similar: “You start having psychological problems whenever you are not one hundred percent convinced of what you are doing,” says Oliver.
Once you have evaluated your system statistically over enough trades and the evaluation points to an edge, it is easier to put a series of losses into perspective. If that basis is missing, you start to doubt and to change things: maybe the stop is too small after all, maybe the trade works better with more room. Such spontaneous adjustments often make the result worse instead of better.
The more you can put knowledge and insights into numbers and back them up statistically, the less room such doubts have. Statistics does not create certainty, though, because evaluations rest on past data. Emotions do not disappear as a result either. The common advice “trade like a machine” is therefore hard to follow: “We are human, we will always be human, and none of us will ever be able to operate like a machine in the end. We are not made for it, and that is a good thing. We have emotions, and every one of our emotions has a purpose. Emotions are not good or bad; they are pleasant or unpleasant,” says Oliver.
06
Trading as a profession: the hard work
Trading is a profession, whether you practice it on the side or full time, and you have to learn this profession. It starts with the fundamentals: how exchange trading works. It is best to learn them from someone you trust professionally and personally; whom you learn from is your own decision. A one-to-one copy of other people's trades does not get you far, because trading is more individual than many think. It is about understanding concepts and developing from them a system that fits your character.
Nobody takes the hard work off your hands. “We can show you the concepts and how we approach things, so that you have something to orient yourself by. But everyone has to do the hard work themselves,” says Oliver. When you sit alone at the market and it is your own money, doubts come up about whether what you learned really holds. You can reduce them by evaluating what you learned or your own insights statistically in a spreadsheet. Oliver knows traders who trade very different approaches, from the order book to options and CoT data, and all of them share one thing: they have invested a lot of time in statistical evaluations.
07
The risk quadrant
The risk quadrantThe four factors reward-to-risk ratio, hit rate, trading frequency and risk per trade, which influence each other depending on the trading rules. consists of four parts: the reward-to-risk ratioThe targeted profit in relation to the risk of the stop. (RRR), the hit rateThe share of trades that end in profit. (HR), the trading frequency (TF) and the risk per trade (RPT). Depending on the trading rules, these four measures influence each other, in statistical and discretionary trading alike. That is not bad; you should just know it and take it into account in your considerations.
Visible: Oliver's slide on the risk quadrant, in German, with four fields: CRV (reward-to-risk ratio, RRR in this article), TQ (hit rate, HR), TF (trading frequency) and RPT (risk per trade). From minute 43:00. Image: ATAS Deutschland
An example from the order book: Oliver waits, above all in the heatmap, for several pieces of information, namely how passive and active market participants position themselves, how the speed behaves and whether there is an order flow event such as stop runs, exhaustion, absorption or iceberg orders. Only then does the entry follow, when the market breaks out of a range. That is one possible approach, not a universal truth. Another trader can enter more aggressively, already after the first order flow event, and accepts that more trades become losers.
A counterexample shows how the factors connect: anyone who wants to force a reward-to-risk ratio of three to one or more because it is seen as the most important measure enters later. The stop becomes larger as a result, and the market has to run further in the desired direction for the ratio to work. If the market, on statistical average, does not offer that distance, the only option is an earlier entry. With less information, however, the hit rate falls, because the market stops you out more often.
In discretionary trading, optimizing one factor often comes at the expense of another. The four measures do not necessarily work against each other, though. Whether a change in one affects the others depends on the trading rules. If you change only the position size, that is, the risk per trade, the hit rate and the reward-to-risk ratio do not change.
For every trading system there is an ideal combination of the four factors, and it depends on three things: your trading system, the market and its character and, most important, your own character. “Do not let anyone tell you that hit rate is the most important thing, or that reward-to-risk ratio is the most important thing, or that you have to trade as often as possible,” says Oliver.
A scalper can build a well-working system with high frequency, small distances, a lower reward-to-risk ratio and a high hit rate. The same person is more likely to fail if, at high frequency, they also try to force a high reward-to-risk ratio. How you find the right setting is shown in the next section. You can find a detailed explanation of the risk quadrant in our article Money Management im Trading (in German).
08
The trading journal with three extra columns
You find the levers by recording your trading statistically. For this, especially in the first years, a classic trading journal is suitable, in which you enter your trades carefully. It has to stay practical: there is no point in spending ten minutes on every small trade. Without numbers, however, you will not arrive at clear insights. With 200 to 300 trades in the table, a first evaluation is worthwhile. That is a rule of thumb, not proof of a lasting edge.
Many people do not have three columns on their radar, although they are a good basis for optimizing.
Possible take profit For winners and losers alike, you record how far the market would have run in your direction on your timeframe before it first made a strong reversal against you. That is partly in the eye of the beholder but can usually be determined fairly clearly.
Required stop for winners For winning trades, you ask how large the stop would have had to be for you to reach the same profit.
Emotions You note briefly how you felt at entry (more on this further below).
A deliberately striking example for the second column: you work with a fixed 15-tick stop and a 30-tick take profit, so a reward-to-risk ratio of two to one. The evaluation shows that over 90 percent of the winners would have remained winners even with a stop of only nine ticks. The hit rate can be expected to fall somewhat with the tighter stop, but the reward-to-risk ratio to improve so much that more remains in net terms. The table shows only the arithmetic behind this, not a result.
Criterion
Current rule
Tested variant
Stop
15 ticks
9 ticks
Take profit
30 ticks
30 ticks
Arithmetic RRR
2 : 1
roughly 3.3 : 1
Hit rate needed to break even, before costs
roughly 33 percent
roughly 23 percent
Data basis
The trades actually taken
A recalculation based on the winners; losers, costs and execution have not yet been checked
Only a full check shows whether the tighter rule really brings more. For that, you recalculate all your previous trades with the new rule, including the losers and the winners that the tighter stop would have stopped out, and you include costs and execution (slippage). After that, you test the rule on a later, separate data period that you did not use for the adjustment; this shows whether it merely fits the old data (overfitting, see Bailey et al., Notices of the AMS, 2014).
Even Oliver manages trades very discretionarily and evaluates them anyway. After 500 to 1,000 trades in the statistics, it is possible to check whether the approach still fits or whether the market has changed and the approach has to be adjusted.
09
Evaluating situations: the VWAP example
Besides your own trades, certain market situations can also be evaluated statistically. A deliberately striking example is the daily VWAPThe volume-weighted average price, here the daily VWAP, which appears as a line on the chart.. You look at what happens when the market stabilizes below the VWAP and approaches it for the first time. In an Excel spreadsheet, you enter how many ticks the price pushed up through the VWAP and how many ticks it bounced off it. That is not a finished trading system but a suggestion.
The difference: anyone who has the VWAP only as a red line on the chart develops a feeling over time, but it stays vague. Anyone who has evaluated a thousand touches really knows the tool and can include it in their own system more clearly, for example depending on the market phase.
Visible: five-minute chart of the E-mini S&P 500 (ES) with the daily VWAP as a red line. The price has stabilized below it and approaches the VWAP on the right of the chart for the first time, exactly the situation Oliver would evaluate. From minute 59:20. Image: ATAS Deutschland
Another example: take the closing price of the previous day's full-day VWAP and evaluate how the market reacts to it the next day.
You evaluate the third column in the journal, the emotions, in the same way. For every trade, briefly note how you felt at entry, for example unsure after several re-entries following a stopped-out trade, or confident because everything fit together. With enough data, you filter by this emotion and compare the results with your overall statistics. That is statistics too, and it can show you which basic mood you trade better in.
10
What you can take away from the webinar
Even discretionary trading needs numbers. You collect objective information from the market, form an opinion and decide for yourself. How markets typically behave is something you can evaluate instead of estimate.
Numbers reduce doubt. Anyone who knows their own approach statistically has to decide less often after a loss whether to change something, and spontaneous adjustments are a common mistake. Numbers do not create certainty, but they do give you a basis.
Reward-to-risk ratio, hit rate, frequency and risk per trade are connected, depending on your rules. What suits you depends on your system, the market and your character. There is no right or wrong.
Your journal shows the levers. With three extra columns (possible take profit, required stop for winners, emotions) and the evaluation of individual market situations, a feeling becomes verifiable knowledge.
“As long as you cannot say with absolute conviction that the stop is exactly where it is right now, right just as it is, you will keep being tempted to adjust something, to improve something, usually to make it worse by trying to make it better.”
Oliver Sparing in the ATAS webinar (translated from German)
11
About the webinar
The webinar ran on May 30, 2024 as part of the ATAS Deutschland webinar series on its YouTube channel, with the ATAS team in the chat. It is held in German; on YouTube, you can switch on machine-translated subtitles. ATAS is a trading platform for order flow analysis. Oliver is a regular guest there; you can find all appearances on our guest appearances page.
Note: the video is a recording from 2024. Brand and company names in the video and in the preview image reflect the status at that time. Offers and notes in the video are no longer current.
Day trading programme
How do you evaluate your trading?
Evaluation, risk and execution belong together. In our day trading programme, you learn to align them. The programme is currently offered in German.
What is the difference between statistical and discretionary trading?
In statistical trading, you follow a fixed set of rules that can be modeled mathematically or algorithmically. In discretionary trading, you collect objective information from the market, form an opinion with your experience and decide yourself whether to buy or sell.
Why is statistics also important in discretionary trading?
Numbers from your own trading can help reduce doubt. Anyone who knows their own approach statistically doubts less after a loss and is less tempted to change stops or rules spontaneously. Statistics does not create certainty, and emotions remain, but they get less room.
What is the risk quadrant?
The risk quadrant consists of reward-to-risk ratio, hit rate, trading frequency and risk per trade. Depending on the trading rules, the four measures influence each other, but they do not necessarily work against each other. In discretionary trading, optimizing one factor often comes at the expense of another. If you change only the position size, hit rate and reward-to-risk ratio do not change. The ideal combination depends on your system, the market and your character.
Which columns are worth having in a trading journal?
Besides the usual entries, three columns: how far the market could have run in your direction before it first ran strongly against you, for winning trades the size of the stop that would have been needed for the same profit, and a short note on your emotion at entry.
How do I know whether a new stop rule is really better?
Only a full check shows it. Recalculate all your previous trades with the new rule, including the losers and the winners that a tighter stop would have stopped out, and include costs and execution (slippage). Then test the rule on a later, separate data period that you did not use for the adjustment, so you can see whether it merely fits the old data.
StatisticsTrading JournalATAS
Oliver Sparing
Founder & Head of Trading · TradeNeon
Oliver Sparing has been actively trading the financial markets since 2011. His professional roots lie in precious metals trading in Hamburg; in 2017 he learned at a London trading floor. At TradeNeon he leads the day trading and swing trading programmes and is responsible for the trading methodology, with a focus on order flow, market structure and fundamental market data. Level of Interest, Futures Insights and Lab of Trades grew out of this work. Platforms such as ATAS, Bookmap and WH SelfInvest regularly invite him as a guest. All guest appearances
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