Python & Custom Platform Development
Algorithmic Trading Systems Beyond Off-the-Shelf Platforms
When your trading infrastructure needs don’t fit inside a retail platform, you need custom development. Python is the lingua franca of quantitative finance — and the foundation for most institutional trading systems. We build the whole stack.
What We Build
Standalone Trading Systems
End-to-end Python applications that connect to broker APIs, process market data, generate signals, execute orders, and manage risk. No platform dependency. You own the entire codebase.
Research & Backtesting Frameworks
Custom backtesting engines using Backtrader, Zipline, VectorBT, or purpose-built frameworks. When QuantConnect or TradingView’s backtester doesn’t model your strategy accurately, we build what does.
Data Pipelines
Market data collection, cleaning, storage, and delivery. Historical databases, real-time feeds, alternative data integration. PostgreSQL, TimescaleDB, Arctic, or whatever fits your scale.
API Integrations
Broker APIs (Interactive Brokers, Alpaca, Binance, FIX protocol), data providers (Polygon, Quandl, Bloomberg), and internal systems. We build the connectors and handle the edge cases.
Execution Engines
Smart order routing, TWAP/VWAP execution, iceberg orders, latency-optimized order submission. The layer between your signals and the market.
Monitoring & Alerting
Real-time dashboards, P&L tracking, risk metric monitoring, anomaly detection. Know what your system is doing at all times.
Our Expertise
- Core libraries — NumPy, Pandas, SciPy, scikit-learn, statsmodels
- Backtesting — Backtrader, Zipline, VectorBT, custom engines
- Broker APIs — Interactive Brokers (ib_insync), Alpaca, Binance, FIX
- Data — PostgreSQL, TimescaleDB, Redis, Arctic, InfluxDB
- Deployment — Docker, AWS, GCP, Linux VPS, systemd services
- ML/AI — Where it actually adds value. Feature engineering, regime detection, ensemble methods. Not black-box magic.
- Visualization — Plotly, Dash, Streamlit dashboards for monitoring and research
Common Projects
Institutional-Grade Backtesting
You need backtesting that models your actual execution — queue position in limit orders, market impact, funding costs, borrow availability. Retail backtesters don’t do this. Custom engines do.
Multi-Exchange Crypto Systems
Arbitrage, market making, or directional strategies across multiple exchanges. WebSocket feeds, order book management, position reconciliation, and the infrastructure to run 24/7.
Alternative Data Integration
Sentiment analysis, satellite imagery, web scraping, SEC filings — ingested, processed, and turned into tradeable signals. Data engineering meets alpha generation.
Existing System Extension
You have a Python trading system that needs new features, better performance, or additional integrations. We extend what you’ve built rather than starting over.
Custom Platform Development
Beyond Python, we work with teams running proprietary platforms:
- C# / .NET — For teams building Windows-based trading infrastructure
- REST / WebSocket API integration — Connect your strategy logic to any platform with an API
- FIX protocol — Direct market access for institutional execution
- Database design — Time-series optimized storage for tick data and analytics
Deliverables
- Full source code in a private Git repository
- Documentation: architecture overview, setup guide, API reference
- Docker configuration for reproducible deployment
- Test suite (unit and integration tests)
- Deployment runbook
- 30 days of bug-fix support post-delivery
Pricing
Python and custom platform projects typically start at the Professional tier ($8,500) and scale to Enterprise ($15,000–$25,000+) for multi-component systems. The scope varies widely — we’ll give you an accurate quote after understanding your requirements.
Let’s Build Your Trading System
Tell us about your project. We’ll respond within 24 hours with an honest assessment.