Hi.
I have one question.
If I share my FTMO investor password (read-only) here, is it against FTMO rules?
Investor password is only for watching. Nobody can open trades or change anything.
I looked in FTMO rules but I couldn't find clear answer.
Does anybody know?
The hardest part of trading isn't finding an edge. It's leaving it alone.
After 15 years of trading, I realized something surprising.
Most of my biggest mistakes didn't come from bad entries.
They came from interfering with good trades.
Moving my stop.
Taking profits too early.
Closing positions because I got nervous.
Ironically, my results improved when I stopped trying to "manage" every trade and simply let my plan play out.
These days my system executes my trading plan automatically, and I rarely even look at the charts. I found that the less I interfere, the better my long-term results become.
Has anyone else experienced the same thing?
​
Balance: $100,225.94
Equity: $100,197.73
Floating PnL: -$28.21
Another quiet day.
My objective hasn't changed: preserve capital, keep drawdown as low as possible, and let the portfolio compound over time.
I'm not trying to pass the challenge quickly. I'm trying to build a system that can survive for years.
Consistency over excitement. 📈
Another quiet day. The account is still around +$180, with almost no floating drawdown.
My portfolio is already built. Around 100 independent strategies are running together as 46 trading systems, and my EA handles all execution automatically.
Today was interesting because the EA detected its first strong signal since the challenge started. The AI State reached 238 with 99% confidence, meaning the system considered it a very high-probability bullish move, so it automatically increased the position size according to its risk model.
Everything is still going according to plan. Slow, consistent, and focused on capital preservation rather than chasing quick profits.
​
Balance: $100,076.01
Equity: $99,930.43
Floating P/L: -$145.58
Still following the plan. No manual trades, no strategy changes, no chasing the market.
The objective hasn't changed: protect capital first, let the EA do its job, and give it enough time to prove itself.
Slow is fine. Consistency matters more than excitement.
​
Small drawdown today, nothing unusual.
Balance: $100,205.21
Equity: $100,114.53
The plan hasn't changed. The goal is still the same: pass with the lowest drawdown possible, not as fast as possible.
Still sticking to the plan.
FTMO Challenge – Day 12
Another steady day.
Current equity: $100,148
Floating PnL: -$47
Nothing exciting today, and that's perfectly fine. The goal isn't to make money every day—it's to protect capital and let the portfolio do its job over time.
Still sticking to the plan.
I'm curious what people here think.
Not on paper. Not after 20 trades.
I mean over thousands of trades, with realistic spreads, commissions, slippage, and real market conditions.
If your answer is yes, have you actually seen one with a verified longterm track record?
Or do you think it's theoretically possible but extremely rare?
Id love to hear your experience.
I'm curious what people here think.
Not on paper. Not after 20 trades.
I mean over thousands of trades, with realistic spreads, commissions, slippage, and real market conditions.
If your answer is yes, have you actually seen one with a verified longterm track record?
Or do you think it's theoretically possible but extremely rare?
Id love to hear your experience.
11 trading days completed.
Current results:
Closed Profit: +$187.63
The account remains well within all FTMO risk limits.
What interests me more than the profit itself is the internal activity of the portfolio.
QuantFusion currently consists of 96 independent strategies designed to operate under different market conditions.
During the second week:
Around 40% of the portfolio has now been activated.
More strategy groups have started generating signals as market conditions changed.
Trend-following, reversal, and breakout systems have all participated in the portfolio.
The portfolio is behaving exactly as expected. Different market conditions are gradually activating different systems instead of relying on a single strategy.
My expectation is that after approximately one month, nearly all strategy groups will have had an opportunity to activate at least once. Only then will the portfolio begin operating close to its intended long-term equilibrium.
At that point, if market conditions remain reasonably diversified, the portfolio is expected to approach its projected long-term average return of around 1.8% per month, while maintaining conservative risk.
For me, watching the portfolio gradually "come alive" is currently far more important than the short-term profit figure itself. The goal isn't to have every strategy trading every day—it's to have the right strategy become active when the market environment suits it.
Day 11 – FTMO Swing Challenge
Day 11 complete.
Current status:
Balance: $100,187.63
Equity: $100,128.38
Open P/L: -$59.25
The portfolio is still in profit despite open positions fluctuating. Today the AI State is Neutral (5) with 57% confidence, so the EA is staying patient instead of forcing trades.
One thing I've learned after years of building automated systems: not every day needs aggressive exposure. Sometimes preserving capital is the best trade.
I'm continuing to let the EA do its job without manual intervention. I'll keep posting daily updates as the challenge progresses.
Live trading and YouTube updates are available through the link in my Reddit profile. Feel free to watch and share your thoughts.
FTMO Swing – Day 10
Still taking it slow.
Balance is up $96.91, while current equity is +$19.22 with open positions.
The goal hasn't changed: protect the account first, let the portfolio do the work.
I'm not trying to win every day. I'm trying to build a system that can survive for years.
Small gains. Small drawdowns. Consistency over excitement.
QuantFusion AI – 96 strategies, one portfolio.
FTMO Swing Challenge - Day 9
Balance: $100,175.36
Equity: $100,050.70
Floating P/L: -$124.66
Still above the starting balance, but giving back some of the recent gains.
One thing I've learned after years of trading is that protecting capital matters more than chasing returns. Drawdowns are part of the process. The goal is to survive them and stay consistent.
For transparency, I'm now streaming my trading setup live 24/7 on YouTube. No signals, no promises, just the real process, including the boring days and the drawdowns.
Good luck to everyone on their own trading journey.
​
Most traders hate spreads.
​
Everyone wants lower spreads.
​
But here's my question:
​
If your broker offered zero spread trading tomorrow, would you trust it?
​
Why or why not?
What information on a chart is actually "real" and what information is something we've created ourselves?
​
My personal view:
​
Raw Data:
​
- Bid
- Ask
- Time
- Commission
- Swap
​
Near-Raw Data:
​
- Tick Arrival Rate (ticks per second/minute)
- Tick Volume
​
Aggregated Data:
​
- Open
- High
- Low
- Close
- Candles
​
Derived Data:
​
- RSI
- MACD
- Moving Averages
- ATR
- Ichimoku
- Bollinger Bands
​
Interpretations:
​
- Trends
- Ranges
- Support & Resistance
- Market Structure
- Supply & Demand
- Order Blocks
- Fair Value Gaps
​
Some people may disagree, but I think Bid, Ask and Time are the closest things we have to raw market data. Almost everything else is either an aggregation, transformation, or interpretation of those variables.
​
I don't even consider candles to be raw data. A candle is simply a compression algorithm applied to thousands of individual ticks.
​
I also don't consider tick frequency to be raw data, but I think it's much closer to actual market activity than most indicators because it measures how quickly new information is arriving rather than transforming price into another formula.
​
As a system developer, I often ask myself:
​
How much of my edge comes from actual market information, and how much comes from transformations and interpretations of that information?
​
Most traders spend years studying indicators while almost completely ignoring commission, swap, execution quality, and market microstructure, even though those variables directly affect every trade they take.
​
If you had to delete everything from your chart except one source of information, what would you keep and why?
​
​
One thing I've noticed after building and backtesting a large number of trading strategies is that most strategies don't suddenly stop working.
​
They go through periods of underperformance.
​
A trend-following strategy can perform well for years, then struggle for months when the market becomes choppy, and later recover when trends return.
​
The common advice is:
​
"Know when to stop using a strategy and move to the next one."
​
My question is:
​
How do you know the difference between:
​
​
​
​
​
​
If you disable it too early, you might be turning it off right before it starts performing again.
​
This is one of the reasons I prefer a portfolio approach.
​
Instead of trying to predict which strategy will work next, I run many independent strategies simultaneously:
​
Trend-following
​
Mean-reversion
​
Breakout
​
Range trading
​
​
When trend strategies struggle, mean-reversion strategies may perform well, and vice versa.
​
In my experience, the goal is not to find one strategy that works forever. The goal is to build a collection of strategies that can compensate for each other's weak periods.
​
If 20 strategies are underperforming but 80 others are profitable enough to cover those losses and still generate positive returns, the problem is largely solved.
​
So rather than predicting market regimes or constantly replacing strategies, the portfolio adapts naturally through diversification.
​
Curious what others think.
​
Do you actively disable strategies when performance drops, or do you trust diversification and let the portfolio handle regime changes? 🚀
FTMO Challenge – End of Week 1
​
6 trading days completed.
​
Current results:
​
• Closed Profit: +$23.35
• Floating PnL: +$16.77
• Maximum Drawdown: 0.5%
• Deposit Load: 4.4%
• Win Rate: 45.8%
​
What interests me more than the profit itself is the internal activity of the portfolio.
​
QuantFusion currently consists of 96 independent strategies designed to operate under different market conditions.
​
During the first week:
​
• 24 different strategies were activated
• Around 25% of the portfolio started working
• 59 trades were executed across the active systems
​
Strategy activation by category:
​
• Reversal Systems: Most active
• Trend-Following Systems: Second most active
• Breakout / Pattern Systems: Limited activity
• Range Systems: No activity
​
Active strategy IDs during Week 1:
​
48101, 48104, 48117, 48118, 48119, 48123, 48132, 48140, 48142, 48147, 48148, 48149, 48150, 48151, 48152, 48153, 48161, 48162, 48163, 48164, 48166, 48167, 48168, 48169
​
The most interesting observation is that the market environment changed significantly during the week.
​
The initial EURUSD selloff triggered several trend-following systems, while the subsequent recovery activated a larger number of reversal systems.
​
Instead of relying on a single strategy, the portfolio allowed multiple independent systems to participate as market conditions evolved.
​
The objective is not to predict which strategy will perform best next week.
​
The objective is to build a diversified portfolio where different strategies activate under different market conditions.
​
After only 6 trading days, 24 out of 96 strategies have already generated signals, producing 59 trades while keeping maximum drawdown at just 0.5%.
​
For me, understanding which systems activate under changing market conditions is more valuable than the current profit figure itself.
FTMO Challenge – Day 6
​
Starting Balance: $100,000
Profit Target: $110,000 (+10%)
​
Current Equity: $100,046
Progress: 0.046%
​
Daily Drawdown Limit: -5%
Overall Drawdown Limit: -10%
​
Focus: Consistency first. Profit second.
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.