Yo brothers 🤝,

As you know, I’ve spent (and I’m still spending) countless hours fine-tuning, coding, testing, learning, teaching, doing things manually, automating them, pushing deep learning, reinforcement learning... and with the rise of AI over the last few years, I’ve been able to take things very far – and very hard. 🚀

Then came my switch to full auto trading (scalping) on MT5 with Python... and here’s what I realized:

1️⃣ LESS IS MORE
2️⃣ The more my bot learns, the better it gets – all by itself
3️⃣ The more its trading frequency drops… but in exchange, the quality, growth, and risk management get insanely better

That’s when I thought: OK... let’s strip this down even more. Let’s go back to the core LIQBOT concept, then rebuild it directly in MQL5, the native MT5 language.

Guess what? I did it. ✅
I transformed my Python bot into a real EA – a self-contained trading machine.

Originally, my goal was to create a “Rolls Royce Phantom” of trading systems – something that works on pretty much any instrument, under almost any market condition.

But let’s be honest… I’m more of a Peugeot or a Lancia guy. 😏

So yeah, I did a massive job with AI – training an algorithm, the MT5 Liqbot v6.3 – capable of learning by itself, evolving with each trade, with every piece of market data it processes. On top of that, it decides by itself whether to go GO WITH or FADE, adapting in real time to volatility.

👉 We’re way past simple automation here. This is a form of true AI trading intelligence.

And the results? Honestly… mind-blowing. ⚡

The bot is even connected to an autonomous GPT-4.1 agent, constantly prompted with its own user guide, receiving all trades in real time. Yeah, I know – I rebuilt a gas factory. I love gas factories 💥, but I also know not everyone does.

So… the real question is:
Is the goal here just to flex – to prove it works on every instrument, under all conditions, with all brokers, with all capital sizes, with every money management style – while sprinkling AI everywhere just to make it look ultra-sexy and ridiculously profitable?

Or is it simply to find the ONE instrument, the ONE set of market conditions, time windows, and parameters where the strategy really shines?

That’s why I went back to backtesting. Real, serious, tick-by-tick backtesting.

I rebuilt a brand-new EA in MQL5, based on the raw Liqbot AI 6.3 codebase, and I started hammering it with tests: different timeframes, different instruments, different periods, frequencies, risk/reward settings, HUNT / GO WITH / FADE sensitivities…

But here’s the kicker 👀 :
I ended up locking down the “perfect” parameters that I personally found to be the most consistent and profitable… on one very specific instrument. You’ve probably guessed it already:

👉 The DAX (DE40 at IC Markets, Eurex).

Even more specifically, the pre-market phase + Frankfurt open up until the London session (10am CET). That’s it. Just 3-4 hours per day. And trust me, the results are ridiculous.

Backtests done on real ticks (tick by tick), with execution delay emulated at 120ms, including slippage modeling, using “Each Tick based on Real Ticks”.

The outcome? 🔥 Just insane.

Sometimes, you just gotta let time do its thing.

Now, here’s the deal:
I wasn’t even sure I wanted to share this. But for the real ones who’ve been following me for a while, I’m opening the doors to a pure early access drop.

⚡ Price: 89€ only (for now)
You get:
✅ The MQL5 EA
✅ The source code
✅ My best settings (locked and loaded for the DAX pre-market)

No fluff. No marketing BS. No “guru course”.
👉 Just an EA that works, in its specific conditions – and crushes it.

Here’s the link 👇
👉 https://py.pl/4DuegF5PLPA

⚠️ First come, first served. I might keep it private after this first wave.
This is your shot at being part of the lab before the doors close.

Patience. Work. Quality. Time.
That’s what pays. Always.

🔥 So… who’s ready to unleash the Liqbot on the DAX?