The 30-Minute Weekly Trading Review: A Checklist for Finding Repeatable Edges

A folder full of screenshots isn’t a trading review. Neither is rereading your biggest loss until it feels explainable.

A useful weekly review has a tighter job: compare your plan with your execution, group similar trades, and choose one change to test next week. Thirty focused minutes is enough when the journal is already up to date.

The time limit helps. It stops the review from turning into a weekend trial where every losing trade is prosecuted and every winner is treated as proof. You need a decision you can carry into the next session, backed by a sample of trades rather than the one trade still occupying your head.

This checklist gives each part of the review a fixed time box.

Here, an edge means a clearly defined setup with positive expected value after losses and trading costs across an adequate sample. A recurring chart shape alone does not meet that standard.

Before You Start: Make the Trades Comparable

Set the review period to the previous trading week. Include every closed trade, including scratched trades and small losses you would rather ignore.

Then gather the fields needed to compare them:

setup or strategy tag;
market and direction;
entry and exit time;
planned and actual entry;
planned stop, target, and initial risk;
position size;
P&L in cash and R-multiples;
fees, funding, and other trading costs;
exit reason;
rule adherence;
screenshot and a short note on market conditions.

Missing fields are part of the result. If you cannot tell whether a trade followed the plan, the journal needs a clearer pre-trade record next week.

Keep the sample in context. Five trades from one week can expose a process problem or suggest a pattern worth testing. They cannot establish that a strategy has a durable edge.

That decision context belongs in the journal before memory edits the story. CME Group’s trade-log guide recommends recording the reasons for a trade alongside entries, exits, targets, time, and market conditions, then using the post-session review to examine how the result happened.

Minutes 0-5: Check the Week-Level Numbers

Start with the whole week. Record the same small set of metrics every Friday or weekend so the comparison remains consistent.

Metric	What it tells you	What it can hide
Net P&L	The result after gains and losses	Whether one outlier produced the week
Total trading costs	How much friction reduced the result	Costs created by overtrading or poor order choice
Win rate	The share of trades that closed positive	The size of winners versus losers
Average winner and loser	The payoff shape of the sample	A few extreme trades in a small sample
Profit factor	Gross profit divided by gross loss	Sequence, drawdown, and sample quality
Expectancy	Average outcome per trade over the sample	Whether the same conditions will persist
Maximum drawdown	The largest peak-to-trough decline	Intratrade risk if your data only uses closed equity
Rule adherence	How often execution matched the written plan	Whether the plan itself was useful

Use net results after fees where possible. Frequent trading can look productive while costs quietly absorb a large part of the gross result.

The definitions also need to stay stable. QuantConnect’s official glossary defines win rate after transaction fees and describes drawdown as the largest peak-to-trough decline. MetaTrader 5’s testing documentation defines profit factor as gross profit divided by gross loss. Neither metric should carry the review by itself.

Calculate expectancy in one line

Expectancy estimates the average result per trade in the sample:

Expectancy = (win rate × average win) - (loss rate × average loss)

Use positive values for average wins and absolute values for average losses. You can calculate it in cash, percentage terms, or R-multiples. R-multiples make trades with different position sizes easier to compare because each result is expressed relative to the amount initially risked.

Suppose a week contains 10 trades. Four win an average of 1.5R and six lose an average of 0.7R:

(0.40 × 1.5R) - (0.60 × 0.7R) = 0.18R per trade

That number describes the reviewed sample. It is not a forecast for the next trade.

Minutes 5-10: Audit Rule Adherence

Separate decision quality from outcome.

Mark each trade with one of these labels:

plan followed;
rule broken;
execution issue;
plan was incomplete.

A profitable rule break belongs in the rule-broken group. A planned loss belongs in the plan-followed group. Mixing outcome and execution makes the review useless because a lucky result can excuse a poor decision while a normal loss can make a sound process look defective.

For each broken rule, record the exact behavior. Examples include entering before confirmation, widening a stop, adding beyond the planned size, taking profit before the written trigger, or reopening the same idea during a cooldown period.

Count the cost of those breaks in two ways:

Their direct P&L contribution.
Their effect on exposure, drawdown, or the ability to follow later trades.

The second figure often carries more information. An oversized trade may finish flat while still creating enough stress to distort every decision that follows.

Minutes 10-15: Group Trades by Setup and Condition

Now stop looking at the trades in chronological order. Group them by the conditions that should make them comparable.

UltraTrader Strategy view comparing trading performance across tagged strategies.

Start with setup. Then add one useful dimension at a time:

market or asset class;
long versus short;
market session or hour;
trend, range, or another condition defined before the review;
planned risk band;
hold-time band;
entry or exit method.

Avoid slicing a small sample into tiny groups. One winning London-session breakout and one losing New York-session breakout do not support a session rule. Keep the observation as a note and test it against a larger history.

For each group, compare trade count, total P&L, expectancy, profit factor, average winner, average loser, drawdown, and rule adherence. A candidate pattern deserves attention when the group has a clear definition, enough repeated examples to inspect, and an explanation tied to the trading method.

The label must be usable before the next trade. “Clean setup” is weak because it can be assigned after seeing the result. “First pullback to the breakout level within 30 minutes, with volume above the 20-period average” can be checked without knowing the outcome.

Minutes 15-20: Inspect the Largest Winners and Losers

Review the two largest winners and two largest losers. The point is to learn whether the tail of the distribution came from the strategy, execution, or chance.

Use the same checks for all four trades:

Verify that the setup was tagged correctly.
Compare planned risk with the final position size.
Confirm that the exit rule was written before entry.
Measure any material difference between the planned order and the fill.
Flag results dominated by one unusual market event.
Judge whether the same decision would be acceptable with the opposite P&L result.

Pay special attention to concentration. If one 5R winner produced the entire week’s profit, record the week both with and without that trade. Do not delete the winner from the official result. The second view shows how dependent the week was on one event.

Apply the same treatment to the largest loss. A rare gap, exchange interruption, or extreme slippage event should stay in the record, with the execution issue labelled. That prevents an operational failure from being misread as proof that the setup itself failed.

Minutes 20-25: Compare Planned Exits With Actual Exits

Exit behavior deserves its own pass because final P&L hides how the trade was managed.

Filter for:

stops moved farther from invalidation;
profits taken before the planned trigger;
targets extended after price moved in your favor;
time exits ignored;
partial exits taken without a written rule;
orders filled away from the expected price.

Compare the planned exit, actual exit, and any allowed change written before entry. This separates a strategy question from an execution question.

Alternative exit rules can also be tested against closed trades. Change one variable, such as the stop distance or partial-profit rule, and inspect the effect across a group of comparable trades. Treat the result as a historical scenario. A rule that would have improved last week’s P&L may fail on the next sample or may simply fit one unusual price path.

Risk Management Starts With Your Exit Rules explains how to define the invalidation, profit-taking logic, time condition, and allowed changes before entry.

Minutes 25-30: Write One Test for Next Week

End with one controlled change. More changes make it hard to identify what produced the next result.

Write the test in this format:

Observation:
Evidence from this review:
Change for next week:
Trades included:
Metric to watch:
Condition that cancels the test:
Review date:

Here is a filled example:

Observation: Three of five breakout losses came from entries made before a candle closed beyond the level.
Evidence from this review: Early entries lost 2.1R combined. Confirmed entries gained 0.8R combined.
Change for next week: Enter this setup only after the confirmation candle closes.
Trades included: Breakout setup in BTC and ETH during the defined session.
Metric to watch: Rule adherence, trade count, expectancy, and average entry slippage.
Condition that cancels the test: The confirmation rule cannot be identified consistently in real time.
Review date: Next weekly review.

This is a test plan, not a permanent strategy revision. Keep it for a defined sample, then review it with the same fields.

The Weekly Trading Review Checklist

Copy this into your journal, notes app, or recurring task.

Data check

[ ] Every closed trade from the review period is included.
[ ] Fees and funding costs are included where available.
[ ] Setup, initial risk, exit reason, and rule adherence are recorded.
[ ] Missing data is listed as a process issue.

Week-level review

[ ] Record net P&L, win rate, average winner, and average loser.
[ ] Record expectancy, profit factor, and maximum drawdown.
[ ] Compare planned risk with realized loss.
[ ] Check whether one trade dominates the result.

Execution review

[ ] Label each trade as plan followed, rule broken, execution issue, or incomplete plan.
[ ] Count each type of rule break.
[ ] Compare rule-followed and rule-broken results.
[ ] Record profitable rule breaks without excusing them.

Pattern review

[ ] Group trades by setup first.
[ ] Add only one or two conditions with enough trades to compare.
[ ] Write candidate patterns in terms that can be identified before entry.
[ ] Treat small groups as leads for further testing.

Exit review

[ ] Compare planned and actual exit reasons.
[ ] Check early profits, widened stops, ignored time exits, and unplanned partials.
[ ] Separate execution slippage from decision changes.
[ ] Test only one alternative exit variable at a time.

Next-week test

[ ] Choose one change.
[ ] Define the trades included in the test.
[ ] Choose the metric and cancellation condition.
[ ] Set the next review date.

Common Weekly Review Mistakes

Reviewing only the losing trades

Winners can contain oversized risk, broken exits, and accidental gains. Excluding them trains the review to confuse profit with good execution.

Changing the strategy every week

Small samples are noisy. Weekly reviews work best for monitoring execution and collecting testable observations. Major strategy changes need a larger, relevant sample and clear version control.

Optimizing several variables together

Changing the entry trigger, stop, target, and position size at once produces a new strategy with no clean comparison. Change one variable per test.

Using vague tags

Tags such as “bad psychology” or “good setup” are difficult to apply consistently. Record the visible behavior: entered within 10 minutes of a loss, moved the stop, exceeded planned size, or closed before the target condition.

Treating the best backtest result as the answer

Testing many variations increases the chance that one will fit the reviewed history by accident. Keep the rule simple, document how many alternatives were tried, and validate the candidate on later trades that were not used to choose it.

Make the Review Easy to Repeat

The weekly process depends on the quality of the daily record. Log the plan before the outcome is known. Keep tags stable. Record costs. Attach the chart while the context is still fresh.

UltraTrader keeps trades, notes, screenshots, strategy tags, mistakes, and performance metrics in one journal so you can filter comparable trades instead of rebuilding the week in a spreadsheet. For exit-specific research, Amvo can replay eligible closed trade history under alternative exit rules and show the hypothetical result beside the original. Historical scenarios do not predict future performance.

Schedule the review at the same time each week. Stop after choosing the next test. The journal can keep collecting evidence while you trade.

Educational content only. It is not investment advice. Trading involves risk of loss. Historical and hypothetical results do not guarantee future performance.