15-strategy algorithmic paper trading platform on AWS EC2 — systemd-supervised Python services, risk engine with kill-lines, market regime detection, and automated analytics pipeline

A high-performance algorithmic trading system built in Rust for backtesting, live trading, and strategy optimization with Binance & MT5 support, parallel execution, advanced risk management, and extensible architecture.

Survivability-first quantitative research system. An AI council debates every architecture decision before code; deterministic, tested strategies do the trading. Walk-forward + purged CV + deflated Sharpe. LLMs never place trades.

A Python framework for testing trading strategies against the ways backtests mislead: look-ahead audits, matched-exposure controls, and block-bootstrap significance tests. The tester is itself tested - a property fuzzer plus mutation testing (4 planted engine bugs, all caught). Includes three case studies of rejected ideas.

Quantitative strategy validation pipeline HMM regimes, walk forward cost aware backtesting

AI multi-agent system for stock market signal generation using LangGraph, GPT-4, and Qdrant vector search. Achieved 42.8% backtest return vs. 24.5% buy-and-hold, 78% win rate on high-consensus signals. 🥇 Best Use of AI/ML, UB Hacking 2024.

End-to-end automated crypto trading workflow featuring market scanning, signal generation, paper trading, risk management, Telegram alerts, PostgreSQL analytics, and Google Sheets reporting.

Cost-aware time-series momentum on a $20 IBKR account

Personal research project combining software development, behavioural analysis and quantitative review to transform discretionary trading decisions into an auditable dataset.

AI-powered multi-agent quant signal generation engine. Uses LangGraph to orchestrate 4 LLM agents (News Analyst, Trading Analyst, Risk Analyst, Manager) that collaborate to generate risk-adjusted BUY/SELL/HOLD signals using real-time news, vector memory, and backtesting.

Systematic multi-factor equity strategy using momentum, liquidity and volatility signals with reproducible backtesting and Fama–French validation.

Small-account systematic trading bot for Alpaca — built live, diagnosed a losing strategy with real backtests, and rebuilt it.

Opening-range breakout on Nasdaq-100 futures with a full audit of how simulation conventions move the result.

Advanced IDX Market Intelligence & Screener Platform featuring AI-powered Reasoning, Deep Broker Flow Detection, and Automated Trading Journal.

Backtesting Engine 2026 – Test trading strategies on historical data. RSI, MACD, SMA, Bollinger Bands, and custom strategies. No real money involved. Setup.exe included.

Quantitative AI hedge fund platform: Flask backend, ML/RL trading models, React web and React Native mobile clients.

Automated multi-asset mispricing bot for Kalshi BTC/ETH price-level markets — log-normal pricing, adaptive vol calibration, Kelly risk sizing, full replay/audit trail.

OKX AlphaPilot — AI Quant Trading Platform for OKX. Auto Alpha Factor Mining via Reinforcement Learning & Transformer. Supports Multi-Factor Portfolio Fusion, OKX v5 WebSocket Feed, Backtesting & Live Risk-controlled Trading.⚡ OKX AlphaPilot | 面向 OKX 交易所的全链路 AI 量化交易中枢。基于强化学习（REINFORCE）与 Transformer 自动挖掘 Alpha 因子算子公式，支持多因子组合融合、WebSocket 实时行情/持仓推送、离线

Sanitized public case study of AlphaQuant V12: systematic trading architecture, risk governance, QMS testing, safe demo code, and CI.