My Crypto Experiments
Over the past months, I have been actively experimenting with crypto trading automation.
Starting from scalping strategies on demo accounts, I’ve been building and refining a multi-tenant Java trading bot that integrates with platforms like Bybit (with plans for MEXC, GateIO, and BingX).
Some highlights of these experiments include:
- Connecting external signals from TradingView directly into execution logic.
- Designing modular integrations per exchange with clean abstraction layers.
- Handling advanced trading commands:
buy,sell, stop loss, take profit, position closing, and even balance checks. - Deploying lightweight infrastructure on AWS EC2 (t2.micro, free tier eligible) with MongoDB Atlas for persistence.
Through this journey, I’ve seen how fragile trading strategies can be, but also how powerful automation becomes when paired with proper risk management.
Cooperation and Collaboration
I see these crypto experiments not only as a personal project, but also as an open invitation to cooperate.
I am especially open to collaboration in the following directions:
- Trading Strategies: Working with traders who want to automate their signal-based strategies.
- Exchange Integrations: Expanding support beyond Bybit to platforms like MEXC, GateIO, and BingX.
- Open-Source Tools: Sharing modular components of the bot for others to adapt, extend, or contribute to.
- AI & LLMs in Trading: Exploring how machine learning and LLMs can support strategy evaluation, anomaly detection, or even sentiment-driven trading.
Why Cooperation?
I believe the future of trading—and software in general—lies in collective intelligence.
Just as my work on the Borg Unity Software Privacy License emphasizes the merging of human and machine intelligence into a technosphere, I want my crypto projects to follow the same path: shared, open, evolving together.
📬 If you’re interested in discussing, experimenting, or building together—I’m open for cooperation.