algorithmic-traiding

The research engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.

A curated guide to the tools traders actually use: market data APIs, brokerage and exchange APIs, crypto and on-chain analytics, forex platforms, charting, backtesting, and automation. Compare features, markets, pricing, and Python, Go, and PHP SDKs to build reliable, repeatable trading workflows across global markets

Algorithmic trading (algo-trading) in the stock market with OCaml

Open-source Polymarket AI trading bot: bundle arbitrage (YES+NO≠$1), market making, BTC 15m signals, AI agent & web dashboard. TypeScript.

Self-hosted paper-trading robot for US ETFs on Alpaca: connect a paper account → it trades a 60/40 behind hard risk limits → watch it from your phone. Kill switch · volatility target · idle cash in T-bills · walk-forward, deflated Sharpe & overfitting tests · backtests back to 1970 · dashboard + Telegram bot · Docker home server · paper only

VLLM-based trading system

GEMINI based BTCUSDT Binance Futures trading bot for directional signals.

8-layer regime-aware probabilistic allocation framework. Live validation in progress — 22/30 FTMO trades, 63.6% win rate on process-compliant entries. Mathematical edge question formally open.

Проактивный торговый бот для Bybit. Устойчив к разрывам соединения и заточен под охоту на просадках. 🦾🕸️ #Python #TradingBot #Bybit #Crypto

C++17 portfolio optimization engine with custom Simplex LP solver, exact linear rebalancing, and Markowitz backtesting.

Write trading strategies as state machines (SML), test them in a browser editor, and run them on paper or a brokerage. Early prototype.

ML crypto trading bot — Random Forest + XGBoost ensemble on Binance Futures, with Flask monitoring dashboard

Quant Engine - Architecture - Platform

Python MT5 trading framework for developers — backtest, benchmark, live execution, and local control center. Build your own system on top.

A quantitative simulation for Engineering the Future of Capital Markets, modeling delta-hedging cascades via Zero-Cost Collars, engineered specifically for resource-constrained cloud environments.

Research-driven BTC/USDT trading bot with async infrastructure, ML pipeline, and risk management

Research-grade SMA crossover backtester with walk-forward evaluation, trade logs and multi-ticker performance comparison.

Multi-agent autonomous trading system for IBKR — LLM agents propose, code-enforced rules dispose. Regime filters, bracket orders, and a Trading Bible derived from 5 years of market data.

Systematic trading research from first principles — signal generation, statistical arbitrage, portfolio optimisation, tail risk, and ML signals. Honest about failures.

TA-Lib for Go - easy to use, cross platform, without Cgo