Point-in-time algorithmic-trading research with reproducible backtests, paper-trading parity, and fail-closed promotion gates.
Autonomous defined-risk options trading agent for Alpaca — LLM proposes, code decides. Alpaca AI Trading Agents Hackathon (lablab.ai).
Autonomous defined-risk options desk on Alpaca paper trading. MarketDNA sets what is legal; a deterministic Risk Officer decides whether capital moves. The LLM picks from a shortlist it cannot write.
Paper-trading simulator: start with $100,000 in virtual cash and trade US stocks with market and limit orders at live Alpaca prices, then track holdings, P/L, allocation and historical Value at Risk. FastAPI, Next.js, PostgreSQL, Docker.
Autonomous options-trading agent that trades only when the premium is worth the risk — Alpaca AI Trading Agents Hackathon
Stable Baselines3 DDPG agent for Alpaca paper-trading Bitcoin
This GitHub repository hosts a stock trading bot leveraging ALPACA and Gemini. The bot operates by analyzing market news and events to inform trading decisions.
Local-first Python service for end-of-day U.S. equity screening, SEC offering alerts, email digests, and reproducible point-in-time backtesting.
ASCOM Alpaca server for AstroHaven EtherCAT domes
Self-hosted trading platform: momentum and mean-reversion portfolios on Alpaca and Binance Futures, paper/testnet first. One installation per person. MIT.
Cost-aware 0DTE SPY options agent on Alpaca's MCP server. Prices every candidate net of spread, slippage and fees before it reaches a risk check, and publishes every refusal with the arithmetic behind it.
🤖 AI fully-automated US stock quant trading system — chat in plain language, AI handles research, screening, strategy, backtesting & paper trading. ⬇️ Download desktop app (out-of-the-box): https://github.com/alxmo/soloquant/releases/latest | AI 全自动美股量化交易系统，开箱即用，下载即用：https://github.com/alxmo/soloquant/releases/latest
A Codex workspace template that automates your investing every morning. Rules over emotion. No fear, no FOMO. Ships with 3 default strategies — dip-buying, AI value-chain DCA, and mean-reversion active trading — and helps you build your own if you'd like.
Session-aware Python research and Alpaca paper trading for liquidity sweep, break-of-structure, and fair-value-gap strategies, with CSV replay and SQLite audit trails.
Here I will be doing budget analysis with Plaid, creating a retirement plan with Monte Carlo simulations, and generating a financial report.
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