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Most comparisons stop at phase count, but the profit target split, drawdown type, minimum trading days, and consistency rules can all differ between one-step and two-step versions of the same program. Real numbers from FTMO and FXIFY, and a decision framework for which format fits which trader.
Backtesting simulates a strategy against historical price data before any capital is risked; a trading journal records what actually happened once real orders were placed. Why the two are complementary, not interchangeable, and how to use them together.
Revenge trading is placing a trade specifically to recover a recent loss, rather than because the setup meets the trader's own rules. Covers the precise definition, how it differs from a deliberate martingale-style sizing strategy, and how it compares to FOMO and overtrading.
A daily loss limit is a pre-set maximum amount, in dollars or as a percentage of the account, that a trader allows themselves to lose in a single trading day before stopping. Covers how to set one, common trigger types, and how it differs from a prop firm's daily drawdown rule.
Position sizing is the calculation that turns a planned dollar risk and a stop-loss distance into a number of shares, contracts, or units to trade. Covers the formula, a worked example, how it differs from leverage, and fixed fractional versus fixed dollar sizing.
A fixed checklist of what to calculate during a monthly trading review: win rate, profit factor, average R-multiple, drawdown against the account limit, results by setup tag, and the plan-followed rate, plus how many trades before the numbers mean anything.
A short definition of risk-reward ratio, the formula for calculating it from a planned stop and target, a worked example, and how it differs from R-multiple and expectancy, which measure a trade after it closes rather than before entry.
Why a trading journal should log emotional state as a structured, consistent tag before and after every trade, and how to read the pattern against win rate and R-multiple during a monthly review, instead of tracking a single named bias like FOMO or revenge trading.
A practical comparison of Notion and BitStat for logging trades: what Notion's databases, relations, and formulas can do out of the box, what has to be built by hand, and where a dedicated trading journal still saves the setup work.
Rule-breaking usually happens under stress, after a loss, or during a winning streak, because the rule depended on willpower in the moment instead of a structure that requires no decision at all.
A portfolio tracker shows what you hold and its current value. A trading journal records how each trade was entered, managed, and closed, and why. They answer different questions.
Most trading journals fail within a few weeks, not from a missing template but from skipping the review habit after losing sessions. Here is how to build a journaling routine that actually survives a bad week.
