u/Curious-Spread-4197

I’ve been testing different R:R structures and I’m starting to question the obsession with fixed 1:2 / 1:3 targets.

A 1:3 setup only needs a 25% win rate to break even mathematically before costs.

But pushing the target further can also create longer losing streaks and lower hit rates.

So I’m wondering:

Would you rather have:

A) 40% WR with 1:3 R:R
B) 55% WR with 1:1.8 R:R
C) 65% WR with 1:1.2 R:R

Assuming similar execution costs and drawdown.

I’m less interested in what sounds best and more interested in what people have actually observed live.

I’ve been testing different R:R structures and I’m starting to question the obsession with fixed 1:2 / 1:3 targets.

A 1:3 setup only needs a 25% win rate to break even mathematically before costs.

But pushing the target further can also create longer losing streaks and lower hit rates.

So I’m wondering:

Would you rather have:

A) 40% WR with 1:3 R:R
B) 55% WR with 1:1.8 R:R
C) 65% WR with 1:1.2 R:R

Assuming similar execution costs and drawdown.

I’m less interested in what sounds best and more interested in what people have actually observed live.

One thing I’ve become much more paranoid about when testing short-term strategies is execution.

A strategy can look fantastic on historical candles and then deteriorate badly once you model:

• spread
• commission
• slippage
• execution delay
• partial fills

Especially with scalping.

I’m curious what assumptions people use for realistic backtesting.

Do you:

• use fixed slippage?
• model volatility-dependent slippage?
• delay entries by 1–2 candles/ticks?
• use actual historical order-book data?

At what point do you consider a backtest credible enough to move into paper/forward testing?

This hits a major concern raised by algo traders: live slippage can materially eat into backtested profits. 

Over the last few months I tried several AI interview tools. They were either expensive, slow, browser-only, or had session limits that didn’t work for long system design interviews.

So I built my own.

Current features:

• Live interview copilot
• Coding interview assistance
• System design support
• Mock interviews
• Resume & ATS analysis
• Company-specific interview prep

I’m launching today and would genuinely love feedback from engineers, students, and anyone interviewing right now.

As a launch offer, I’m giving the first 100 users lifetime access for ₹14,999. After that, it moves to a subscription model.

I’d really appreciate honest feedback—good or bad. What features would make this indispensable for your interview prep?

Over the last few months I tried several AI interview tools. They were either expensive, slow, browser-only, or had session limits that didn’t work for long system design interviews.

So I built my own.

Current features:

• Live interview copilot
• Coding interview assistance
• System design support
• Mock interviews
• Resume & ATS analysis
• Company-specific interview prep

I’m launching today and would genuinely love feedback from engineers, students, and anyone interviewing right now.

As a launch offer, I’m giving the first 100 users lifetime access for ₹14,999. After that, it moves to a subscription model.

I’d really appreciate honest feedback—good or bad. What features would make this indispensable for your interview prep?

Over the last few months, I tried several AI interview tools. They were either expensive, slow, browser-only, or had session limits that didn’t work for long system design interviews.

So I built my own.

Current features:

• Live interview copilot
• Coding interview assistance
• System design support
• Mock interviews
• Resume & ATS analysis
• Company-specific interview prep

I’m launching today and would genuinely love feedback from engineers, students, and anyone interviewing right now.

As a launch offer, I’m giving the first 100 users lifetime access for ₹14,999. After that, it moves to a subscription model.

I’d really appreciate honest feedback good or bad. What features would make this indispensable for your interview prep?