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A user built an automated trading system using Claude AI that autonomously scanned trades and made $847 profit overnight without manual intervention.
Anton Palkin highlights how affordable AI subscriptions now enable one-person trading operations, while major firms like Citadel and Man Group already deploy AI agents for research, coding, backtesting, and risk management.
Prodigy Research, a YC S26-backed startup, announces its launch as a frontier AI trading research lab, claiming to train a top-tier quantitative finance foundation model that outperforms top traders and major indices.
Promotional post about Horizon, an AI-driven trading strategy platform that lets users backtest and deploy strategies in plain English, citing a professor managing $200M with AI agents and returning 56% last year.
This paper evaluates the ability of large language models to perform technical market analysis for trading, using a benchmark approach.
Agent Arcade launches a platform where LLM-powered agents compete in day-trading hundreds of assets on Hyperliquid, allowing users to copy or counter-trade the winners.
Share how to use Gemini for stock trading, providing 8 prompts for automated stock selection and trading.
This article explores how individual investors can use IBKR's MCP server to let AI take over repetitive tasks in the investment process (such as data collection, profit calculation), thereby focusing on core judgment; it also proposes ideas for building personalized trading systems, and includes a checklist for self-review of the investment process.
A guide on using the TradingView MCP with Claude Code to create custom trading indicators in Pine Script without needing technical skills.
The post claims that quant firms' complex mathematical edge is now accessible via a plain-English chat interface that can describe, backtest, and execute trading strategies, democratizing quant finance.
This article details how to build a personal quantitative trading system using free AI open-source tools (such as OpenBB, Qlib, TradingAgents, etc.), covering five major modules: data, research, backtesting, risk control, and execution, and points out common pitfalls and discipline.
This is a 50k-star open-source project on GitHub that uses AI models to automatically analyze stock quotes, technical indicators, and fundamental data, generating a decision dashboard with trend scores, buy/sell points, and risk alerts. It supports daily automated runs and multi-platform push notifications.
The paper introduces Sealed Joint Search (SJS) and the Agora system, where five specialized LLM agent classes collaborate to evolve alpha factors. On a 91-day CSI 1000 holdout, Agora achieves a portfolio Sharpe of +1.87, significantly outperforming baselines, and the discovered metrics appear as emergent properties of the system.
The tweet predicts that AI-era exchanges will shift to 24/7 operation, API-first design, and sub-second settlement, arguing that the next global exchange will emerge in Silicon Valley, not New York.
Explores whether AI-driven trading is feasible and secure, addressing potential risks and benefits.
Someone open-sourced the 'LOOP ENGINEERING' framework for building an AI-powered hedge fund that can trade 24/7 using Claude code, claiming it prints alpha continuously.
A 29-year-old Chinese salesperson built an ETH price simulation engine using Claude and 6 AI agents, earning $306,000 last month, showcasing the potential of AI in quantitative trading.
A Chinese trader built a trading bot using Claude Fable 5 and released a 31-minute complete free tutorial video with Spanish and English subtitles, guiding how to replicate it.
A Twitter thread sharing high-quality US stock Alpha bloggers, focusing on their unique insights in trading psychology, AI stock analysis, and market frameworks.
An intern in Guangzhou built a trading bot using Claude and netted $63,000 on Polymarket through high-frequency small-spread trades, demonstrating the application of AI-assisted quantitative trading in prediction markets.