I’m currently working on a new project in close collaboration with my colleague Aurélien.

It sits somewhere between 3D_NEXUS_META and MT5 Liqbot AI.

I rebuilt the full core of the 3D_NEXUS_META engine inside a standalone Python trading module:

• NEXUS microstructure signals
• Signal Labs logic
• execution pipelines
• order-book and tape analysis
• netting basket management
• adaptive risk controls
• machine-learning, reinforcement-learning and AI research layers
• a clean, user-friendly GUI designed for real operational use

The objective is not to create another black-box bot.
The objective is to build an autonomous research and execution engine capable of studying market states, learning from signal behaviour, measuring risk, and adapting its decisions over time.

The first tests on Gold Futures have been extremely encouraging.

📊 First full MT5 test day:
+$1,041.42 net profit
250 trades
56.40% winning positions
Profit Factor: 1.20
Maximum drawdown: 9.64%

Early-stage demo research, of course. No promises. No victory lap.
But the engine is alive.
The execution layer is stable.
The data is flowing.
The learning process has begun.

For now, this remains an exclusive private project.
It is not available.

There is no access.
There is no public release date.

This is deep work only: automated learning, market-state research, basket behaviour, signal validation and institutional-grade execution studies.

Stay close.

I’ll let you know when the doors open. 🧠📡

#AlgorithmicTrading #MachineLearning #ReinforcementLearning #OrderFlow #MarketMicrostructure #GoldFutures #MT5 #PythonTrading #AITrading #QuantTrading #NEXUSMETA