Vijay Kumar 👋
A Polyglot Software Developer 💻 with 4+ years of experience, specializing in Event-Driven Architectures, Microservices, Distributed Systems, and building secure and scalable Cloud-Native Solutions.
Project Type:
Algorithmic Trading Experiment
Core Technologies:
Python, Binance API, TA-Lib
(Not Publicly Accessible)
Technical Overview
A personal experiment in algorithmic trading that processes market data and executes trades based on technical indicators. Paper trading only - no real money involved.
Main Components: Market data websocket → Technical indicator calculator → Risk management module → Mock order executor → Performance dashboard.
Key Insight: Learned that network latency matters more than algorithm complexity for small-scale trading.
Technical Challenges
Data Latency
- Problem: Delayed market data making strategies ineffective
- Solution: Moved from REST to WebSocket API and implemented local candle stick calculation
Backtesting
- Problem: Historical data gaps causing inaccurate simulations
- Solution: Built a data validation layer that flags missing time periods
Lessons Learned
- • Trading APIs have strict rate limits
- • Time synchronization across systems is crucial
- • Paper trading ≠real trading psychology
Future Ideas
- • Add more risk management controls
- • Visual strategy builder
- • Social trading features
