How to Do a Weekly Trading Review: A Step-by-Step Process for Futures Traders
A weekly trading review turns a week of trades into one concrete change. A 45-minute process: the numbers in R, a rule audit, your exits, and one new rule.
TradeProof AI
Practical writing for traders on journaling, risk, and the habits that separate consistent results from lucky ones — plus short videos on how we think about process.
16 articles · newest first
A weekly trading review turns a week of trades into one concrete change. A 45-minute process: the numbers in R, a rule audit, your exits, and one new rule.
There is no single best time to trade NQ, ES or MNQ. Learn how the futures day is structured and how to find your own best hours from your trade data.
Closing winners before your target feels safe, but it can quietly halve your expectancy. Here is why traders take profits too early, how to measure the cost in R, and the exit rules that fix it.
Revenge trading rarely feels like revenge in the moment — it feels like a good setup you can't afford to miss. Here is how to recognise it in your own trade history, measure what it actually costs you in R, and build circuit-breaker rules that still work when you're angry.
Expectancy tells you what a strategy earns per trade on average — the one number that answers whether you have an edge. Here is the formula in dollars and in R, how many trades it takes before the number means anything, and the mistakes that quietly inflate it.
A 50% win rate produces long losing streaks as a matter of arithmetic. Here is how to estimate the streaks your win rate implies, what they cost at your risk per trade, and how to tell normal variance from a strategy that has stopped working.
Position size determines whether a losing streak is survivable or account-ending. Here is the actual formula, worked examples across futures, forex, stocks and crypto, and the mistakes that quietly break it.
Win rate is the first stat every trader checks, and one of the least reliable on its own. Here is the break-even win rate formula, why a high win rate can still lose money, and what to track alongside it.
P&L, win rate, and trade count feel like the obvious things to log — and they are also the least useful for figuring out whether your trading is actually improving. Here is what a trading journal should measure instead.
A green account can hide a broken process, and a red one can hide a good strategy. Here is why PnL is the wrong primary metric, and what to track instead to actually know if your trading is working.
A strategy alone doesn't pass a prop firm challenge. Here's how to build a complete trading plan — risk rules, daily loss limits, entry and exit rules, and a system for tracking whether you actually followed them.
Knowing your rules and following them are two different skills. Here is why traders violate plans they believe in, and how to build a process that makes discipline measurable instead of aspirational.
Traders spend years hunting for a better entry signal when the real leak is somewhere else entirely. Here is why journaling fixes more P&L than any indicator, and what to actually record.
Profit factor is gross profit divided by gross loss. Here is how to calculate it, what range is realistic, and why a very high number is usually a warning sign.
R-multiple measures profit in units of risk instead of dollars. Here is how to calculate it, why it makes trades comparable across markets, and the mistake that quietly ruins the number.
Most trading journals collect data nobody reviews. Here are the fields that change behaviour, the ones that waste your time, and how to review them in ten minutes a week.
TradeProof AI is a trading journal built around the review process these articles describe: log your trades, write your rules once, and see whether your results come from following them.
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