u/Active_Version2665

One thing I’m starting to understand much better under live FTMO conditions is that the performance gap compared to broker backtests is not just about leverage.

I kept noticing that FTMO backtests consistently produced weaker results than RoboForex, even while running the exact same EA logic.

What confused me was that on RoboForex, both the current version of the EA and several older versions matched live trading results surprisingly closely.

So I always assumed the FTMO difference came mostly from the lower 1:30 leverage.

Now I’m realizing that’s probably only part of the story.

Swap costs, execution behavior, overnight holding costs, margin constraints, and recovery speed under lower leverage seem to have a much larger impact than I initially expected.

For people running algos on prop firms:

What other hidden differences have you noticed between prop firm environments and regular broker backtests?

Starting a 100k FTMO challenge under 1:30 leverage conditions.

The main goal here isn’t speed-running the challenge, but stress-testing the system under stricter prop firm constraints:

drawdown behavior

margin control

execution stability during volatility

multi-strategy risk management

The EA will begin with a few very small trades first, just to verify that execution, margin behavior, and order handling are working correctly under live FTMO conditions before moving to normal risk sizing.

Currently running 46 strategies simultaneously on EURUSD.

Will post daily updates.

I’ve been developing a swing trading EA in MQL5 for quite a while now and the codebase has grown to around 19k lines.

Since it’s swing-based and average trades target around 30 pips, live execution has been completely fine so far.

The issue is backtesting speed.

I’m using real ticks in the MT5 strategy tester, but longer backtests are becoming painfully slow as the system gets more complex.

For those building large EAs in MQL5:

What optimizations made the biggest difference in backtest speed for you?

(architecture changes, indicator handling, tick filtering, caching, etc.)