Two "1% risk" trades can be a 2% risk trade in disguise. Correlation is the risk management leak nobody accounts for.

If you're long EURUSD and long GBPUSD at the same time, you're not running two independent 1% bets — both pairs move against the dollar together most of the time, so a broad USD rally against you hits both positions at once. Your actual exposure to "USD strengthens" is closer to 2% than 1%, even though your position sizing math says otherwise.

This shows up constantly in prop firm evaluations because traders scan multiple pairs for setups and take every valid signal without checking whether the signals are actually independent. Four "different" trades across EURUSD, GBPUSD, AUDUSD, and NZDUSD longs isn't diversification — it's one trade with four times the position size, dressed up as separate decisions.

The fix isn't complicated: before adding a second position, ask what happens to both trades if the dominant currency in the pair — usually the USD — makes a strong move. If the answer is "they'd both lose," size the combined position for that reality, not for each trade in isolation. A firm's daily loss limit doesn't care that you meant to diversify.

This matters even more on evaluation accounts with tight daily drawdown caps — a single correlated move across "unrelated" trades is a common way disciplined-looking traders blow a daily limit in one session.

Anyone actively hedge or cap correlated exposure across pairs, or is this mostly ignored until it costs someone a challenge?

A 40% win rate can outearn a 70% win rate. Most traders never run this math, and it quietly wrecks their strategy selection.

Expectancy is win rate times average win, minus loss rate times average loss. A system that wins 40% of the time with a 3:1 reward-to-risk ratio has an expectancy of (0.4 × 3) − (0.6 × 1) = 0.6R per trade. A system that wins 70% of the time but only takes 1:1 trades has an expectancy of (0.7 × 1) − (0.3 × 1) = 0.4R per trade. The "worse" system is actually more profitable per trade taken.

This is why chasing a high win rate is often the wrong optimization target. High win rate strategies usually cut winners early and let losers run a little to avoid "being wrong" — which caps reward-to-risk near 1:1 or worse. Low win rate strategies that respect a wider stop and let winners run can post a much higher expectancy with a worse-looking record.

The psychological trap: a 40% win rate means you're "wrong" more often than you're "right," and that's uncomfortable to sit with even when the math favors you. Traders abandon positive-expectancy systems constantly because the losing streaks feel like evidence the system is broken, when a 40% win rate guarantees streaks of 4-5 losses in a row on a fairly regular basis — that's not bad luck, that's the distribution working as designed.

Before judging any strategy — yours or someone else's — ask for reward-to-risk alongside win rate. One number alone tells you almost nothing.

What's your actual win rate vs. average R multiple? Curious if people here skew toward high-win-rate/low-R or low-win-rate/high-R setups.

A losing trade and a bad trade are not the same thing. Most traders conflate them, and it wrecks their process.

A bad trade is one where you broke your own rules — moved your stop, sized bigger than planned, entered on impulse, ignored your setup criteria. A losing trade is one where you followed your process exactly and the market simply didn't cooperate. Every valid strategy loses some percentage of the time — that's not a flaw, it's the cost of being in the market at all.

The problem is emotional accounting treats both the same way: a loss feels bad regardless of whether it was earned honestly or not. So traders start "fixing" trades that didn't need fixing — tightening stops after a clean loss, hesitating on the next valid setup, second-guessing a strategy that's actually working within its normal variance.

Here's the fix: grade every trade on process, not outcome, immediately after it closes. Two categories only — "followed the plan" or "didn't." If you followed the plan and lost, that's data, not a mistake. If you didn't follow the plan and won, that's a mistake that got lucky, and it's more dangerous long-term than a clean loss because it reinforces the wrong behavior.

Funded account traders especially need this distinction — a firm's drawdown rule doesn't care why you lost, but your ability to keep trading calmly after a loss absolutely depends on knowing whether it was a process failure or just variance.

What's your actual criteria for "followed the plan"? Curious how granular people get with this.

Everyone quotes "risk 1% per trade" like it's gospel. Here's the math nobody explains: why the number matters less than what happens after a losing streak.

A 10% drawdown needs an 11% gain to recover. A 20% drawdown needs 25%. A 50% drawdown needs 100%. The recovery curve isn't linear — it's exponential against you. That's the entire argument for small, consistent risk: not because 1% is magic, but because the deeper the hole, the more disproportionate the climb out.

This is exactly where prop firm rules and personal accounts diverge. Most evaluations cap max drawdown at 8-10% total and daily loss at 4-5%. If you're risking 2% per trade, three losses in a row puts you within one bad day of a breach. Traders who "know the rules" but still get bounced almost always fail here — not because their strategy is bad, but because their position size was calibrated for a personal account's psychology, not a funded account's hard floor.

Practical takeaway: size your risk to the account's actual constraint, not a number you read somewhere. On a funded eval with a 5% daily loss limit, risking more than 1% a trade means a single bad session can end the challenge regardless of your win rate.

Curious how others here size down specifically for evaluation phases vs. funded/live accounts — same % or do you cut it further once real payouts are on the line?