trading

Orus is a platform that uses Claude for investing in perpetuals, featured on Product Hunt.

A free GitHub repository with 4.8K stars releases a 'loop engineering' framework for building self-running quantitative trading agents, detailing 12 steps from strategy intent to rerun.

This article introduces 10 free open-source GitHub repos covering financial data, backtesting, trade execution, etc., enabling retail investors to access tools like those used by Wall Street hedge funds at a low cost.

anorth_chen announced becoming a founding partner of OKX.AI, sharing the practice of abstracting trading abilities onto a cloud-based AI agent, and believes that the agent economy will drive the next crypto bull market.

A trader built a trading journal in Obsidian and used Claude to analyze six months of entries, revealing that 71% of losing trades contradicted notes already in the vault. The post shares the journal structure and insights from the AI-assisted analysis.

An educational thread explaining the mathematical foundations used by quantitative trading firms like Renaissance Technologies, covering concepts from Bernoulli to Brownian motion.

Introduces patternfetch, an MCP server + REST API that provides a token-compact market-state brief instead of raw OHLCV data for trading agents, reducing token usage and hallucinations.

A developer demonstrates running Gemma 4 26B MoE model locally on an 8GB RTX 4060 with Hermes agent to fully automate backtesting of trading strategies, highlighting the growing capability of local LLMs as autonomous agents.

Recommended several bloggers focusing on AI, US stocks, cryptocurrencies, quantitative trading, etc., and briefly introduced their characteristics and achievements.

A deterministic guardrail tool is needed between an AI agent's decision and its irreversible actions such as trades or sending funds, to ensure safety.

A thread introducing Loop Engineering as a solution to the common problem of quant strategies that backtest perfectly but fail in live trading, emphasizing the need for iterative optimization.

Goldman Sachs open-sourced a quantitative trading framework used internally, including Claude AI skills, enabling users to build trading strategies.

TradingAgents is a multi-agent trading framework that uses multiple AIs working together to automate crypto and stock trading, supporting real-time data ingestion, automatic strategy generation, and continuous optimization. It has gained nearly 90k stars on GitHub.

Coinbase has launched a feature allowing AI agents to trade and make payments using its platform, expanding the capabilities of autonomous agents in the crypto space.

This paper reviews and audits execution realism in LLM-based trading research, proposing clearer reporting standards for reproducibility and evaluation comparability.

An open-source framework simulates a real trading floor with multiple AI agents performing fundamental, sentiment, technical, and risk analysis, compatible with major LLMs like GPT-5, Claude 4, and Gemini 3.

A user reports on giving Julius AI $1K on Robinhood to manage a portfolio, noting that despite providing tools, the AI still requires extensive context. The AI made one trade (AMD).

A curated list of 10 open-source projects that provide powerful AI and developer capabilities, often replacing costly commercial software—including AI trading agents, multi-model chat interfaces, video generation, voice cloning, and more.

Limitless released a full developer stack designed for coding agents to operate prediction market trading, aiming to replace manual wiring with autonomous agent execution.

An analysis of how autonomous AI agents are beginning to trade, negotiate, and manage crypto assets 24/7, and why privacy technologies like zero-knowledge proofs are critical to prevent front-running and surveillance in this emerging agentic trading market.