Automated Trading Bot — Stocks & Forex

I built several automated trading systems for forex, stocks, and commodities to address two recurring problems I observed in a day-trading community: emotion-driven decisions and the time required to trade effectively.

Why I built this

• Pain points: Traders struggle with emotions (fear/greed) and lack time to monitor markets.
• Opportunity: Consistent rules and automation reduce emotional mistakes and can execute ideas 24/7 across time zones.

Forex / MetaTrader bot (MQL)

After learning the Fair Value Gap (FVG) candle strategy, I decided to implement an automated version in MetaQuotes Language (MQL). I built the bot from the ground up and iterated it with feedback from friends in the group.

Key capabilities:

• Implements Fair Value Gap and complementary candle/indicator filters
• Executes trades automatically (buy/sell), 24/7
• Automated take-profit and stop-loss management
• Automatic lot sizing based on risk rules, removing manual lot calculations
• Exports trade logs for comparison against expert day-trader decisions

Advanced features added later:

• Trend recognition (higher highs / higher lows) to filter trades against the trend
• Adaptive take-profit targets that reference recent swing highs/lows
• News-awareness database: the bot avoids opening and will close positions around high-impact events, just as a human would

Why these matter:

• Automatic lot sizing removes a frequent source of human error
• Trend filtering improves signal quality and reduces losing trades taken against momentum
• News-aware behavior prevents large slippage and unexpected volatility

Python bots for stocks & commodities + signal aggregator

I also developed multiple Python bots for equities and commodities using indicator and candle-based strategies. A community member suggested adding curated Telegram signal groups to our portfolio, which introduced a new challenge: extracting structured trade instructions from narrative text.

What I built:

• A Telegram signal scraper that follows 20+ public groups
• A ChatGPT-based parser (I used GPT-4 at the time) that converts narrative signals into discrete, machine-readable trade instructions
• A Discord relay and two Discord bots: one to post parsed signals to our group, and another to automatically place trades from those messages

Outcomes:

• The system takes >90% of trades signalled by the monitored groups automatically
• It captures opportunities while we sleep (we’re based in Europe/Asia) and avoids emotion-based hesitation
• Using public tools and models enabled rapid prototyping and a surprisingly high-value outcome

Results & learnings

• Automation substantially reduced missed trades and emotional mistakes.
• Combining signal sources (indicators + curated groups) improved diversification of ideas.
• Parsing narrative signals required an LLM layer to convert human language into precise instructions.
• Proper risk controls (auto-sizing, stop-loss, news filters) are essential for long-term robustness.

Why I enjoy this work

I love automating repetitive, error-prone tasks so we can focus on creative and strategic work. Building these bots satisfied that itch while delivering tangible value to a community of traders.

I would love to explain in detail!

If you’d like, we can talk more in detail at hi@nicmation.com. And if you have a trading idea and want to make it run by itself, contact me to talk about it!