An MT5 Python trading bot: twenty-nine numbers go from a MetaTrader 5 robot to a Python server, and one probability comes back. The architecture, what the model file must carry, timeouts, fallbacks, and everything that can go wrong in between.

📚 Free courses with full code and data for subscribers of my Telegram channel Data Lab: https://t.me/lavrinenko_data

🎓 The full course on Udemy, “AI Forex Trading Bot with Machine Learning, Python & MT5”: https://www.udemy.com/course/build-a-machine-learning-trading-bot-in-python/?referralCode=59ABEDBF83EA5E7A1812
📘 My other courses on Udemy:
• Forex Algorithmic Trading: Backtesting Strategies in Python: https://www.udemy.com/course/test-it-before-you-trade-it-backtests-without-curve-fitting/?referralCode=AAFD579BEC179990057A
• Forex Risk Management & Position Sizing for Trading Robots: https://www.udemy.com/course/forex-risk-management-position-sizing-for-trading-robots/?referralCode=90AEC80D7222F92C6E93

Chapters:
0: 00 Intro: 29 numbers from MT5 to Python
1: 03 What goes into the model file
1: 33 Errors are never probabilities
2: 04 Latency: 60 ms
2: 29 The robot’s side in MQL5
3: 00 Fail closed when the server is silent
3: 32 Log every decision
4: 05 Four deployment traps
4: 41 What to test next

I’m Vasyl Lavrinenko. For more than 20 years I’ve been building trading systems for real investors, and my Expert Advisors have won awards at international trading competitions. On this channel I test trading ideas on real market data and show what actually works, and what doesn’t.

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Topics: machine learning trading bot in Python, AI trading bot for forex, algorithmic trading with Python, MT5 expert advisor programming, Python trading strategy, machine learning algo trading.
#tradingbot #machinelearning #forex

Educational content only, not financial advice. Trading involves a risk of loss.