I build high-performance automated trading systems, trading bots, and quantitative strategies for hedge funds, crypto traders, and fintech startups. From backtesting to live deployment — I deliver production-ready solutions.
A proven four-step process to turn your trading idea into a live, profitable automated system.
We discuss your trading goals, preferred markets, risk tolerance, and strategy concept in a free consultation call.
I design the algorithmic logic and run extensive backtests on historical data to validate performance metrics.
I build the trading bot with your chosen exchange APIs and run it in a paper trading environment for validation.
We deploy to production with full monitoring, alerting, and ongoing support to ensure smooth 24/7 operation.
End-to-end algorithmic trading development, from strategy design to live deployment and monitoring.
Custom automated trading bots for crypto and equity markets. Real-time execution, multi-strategy support, and robust error handling for 24/7 operation.
Quantitative strategy development including market making, arbitrage, trend following, mean reversion, and ML-based predictive models.
Seamless integration with Binance, Bybit, Coinbase, Kraken, and more. WebSocket streaming, REST order management, and rate limit handling.
Comprehensive historical backtesting with walk-forward optimization, Monte Carlo simulation, and detailed performance reporting.
Advanced risk controls including position sizing, stop-loss, take-profit, portfolio diversification, and drawdown limits.
Real-time performance dashboards with live P&L tracking, order history, system health monitoring, and Telegram alerts.
Trusted by hedge fund managers, crypto traders, and fintech founders worldwide.
"Alex built a market-making bot for our fund that consistently outperformed our benchmarks. His understanding of exchange mechanics and risk management is exceptional. Highly recommended."
"The arbitrage bot Alex developed for my crypto portfolio generates consistent returns across Binance and Bybit. Professional communication and on-time delivery — a rare combination."
"Alex helped us build the entire trading infrastructure from scratch. From strategy backtesting to live deployment with monitoring dashboards — he delivered a complete, production-ready system."
Flexible engagement models tailored to your project scope and budget.
Common questions about algorithmic trading, trading bots, and my development process.
Algorithmic trading uses computer programs to execute trades based on predefined rules and mathematical models. It removes emotional bias, operates across multiple markets simultaneously, and can run 24/7. Strategies range from simple moving average crossovers to complex machine learning models. For a deeper understanding, visit the Algo Trading Knowledge Base.
A basic single-exchange trading bot typically takes 2-4 weeks from concept to paper trading. A full-featured production system with advanced risk management, multi-exchange support, real-time dashboards, and alerting can take 6-12 weeks depending on strategy complexity and integration requirements.
I have extensive experience integrating with Binance, Bybit, Coinbase Pro, Kraken, OKX, KuCoin, and FTX. Each integration includes secure API key management, WebSocket streaming for real-time order books and trades, REST API for order placement, and comprehensive error handling for network issues and rate limits.
Yes, comprehensive backtesting is a core part of my service. I use historical tick and OHLCV data to simulate strategy performance, measuring key metrics like Sharpe ratio, maximum drawdown, win rate, profit factor, and Calmar ratio. Walk-forward optimization and out-of-sample testing ensure robust strategy validation before any live deployment.
My tech stack centers on Python with Pandas, NumPy, and CCXT for data analysis and exchange connectivity. For high-frequency applications I use Node.js. Infrastructure is Docker-based, deployed on AWS with Redis for caching and PostgreSQL for trade logging. I follow the comprehensive Algo Trading Knowledge Base best practices.
Absolutely. I develop ML-powered strategies using scikit-learn, TensorFlow, and XGBoost for tasks like price direction prediction, volatility forecasting, regime detection, and anomaly detection. Proper feature engineering, cross-validation, and out-of-sample testing are critical to prevent overfitting and ensure strategy generalisation.
Paper trading executes simulated orders using real-time market data without risking capital. It validates strategy logic, slippage assumptions, and system reliability. Live trading uses real funds and requires additional safeguards: latency optimisation, position synchronisation, kill switches, and continuous monitoring to handle real-world market conditions.
Reliability is built into every system I create. This includes multi-layered error handling, automatic restart on failure, redundant WebSocket connections, health-check endpoints, and real-time alerting via Telegram and email. Production bots run in Docker containers with automated monitoring, logging, and backup infrastructure for 99.9% uptime.
Core technologies, platforms, and domains I work with daily.
Let's discuss your algorithmic trading project. Free consultation — no obligation. I'll help you choose the right approach for your goals.