Passed another prop firm challenge with @fundingpips.
This one was different.
I was sitting around -2% drawdown, then one trade from my high-RR model recovered the drawdown and pushed the account through the target.
One trade.
That's exactly why I find high-RR edges interesting in prop firms.
But if you're thinking about building a high-RR / small-edge approach, don't look only at the RR.
Look at the entire distribution:
β’ How many losses can appear before the next winner?
β’ How deep can the normal drawdown become?
β’ How much variance can the account tolerate before reaching the payout?
β’ How does the strategy behave when the market regime changes?
β’ What happens to the model after spreads, commissions and slippage?
β’ How much of the expected return comes from a small number of large winners?
β’ How does position sizing change the probability of reaching the firm's drawdown limit?
β’ What happens when you remove the biggest winning trade from the sample?
β’ Can the edge survive a long period without reaching its full target?
β’ Does the strategy work only for passing, or can it realistically survive multiple payout cycles?
That's the part retail traders often miss.
A 1:5 or 1:10 RR looks attractive on a screenshot.
But the real question is:
Can the distribution survive the firm's rules long enough for the right-tail winners to appear?
Passing a challenge is one objective.
Building a model capable of repeatedly extracting payouts is a completely different problem.
High RR isn't better.
It's a different distribution β and it needs to be modelled differently.
Back to the data. π
The biggest upgrade from retail thinking to quantitative thinking:
Stop asking:
"Where is price going?"
Start asking:
"What process can I repeat that gives me a measurable advantage?"
A retail trader looks at one trade and asks whether it was right or wrong.
A systematic trader looks at hundreds of executions and asks whether the process produces results.
A retail trader changes the strategy after a few losses.
A quantitative trader expects losses to exist inside the distribution and asks whether the underlying process has changed.
A retail trader wants certainty.
A serious trader builds a framework that can operate without certainty.
That's the real shift.
You don't need to predict every move.
You need a process that can survive uncertainty, control risk, and keep producing when your opinion is wrong.
The goal isn't to become better at guessing.
The goal is to build a machine that doesn't need you to guess.
That's how you start thinking beyond retail.
@sailingNQ@Fun_Trades1 This is true but he want to see just winrate as he say ... trading conditions don't change a lot on winrate and other sides like this metrics but it's change on % returns .. dd % and equity curve sharpe..... βοΈ
@Fun_Trades1 For this yes but real returns real dd will be true after real trading conditions . Spread commission slippage ... anyways good luck funtrades to the moon soon π€πͺπ½