The greatest investment masters working for you! 19 AI Agents including Buffett, Munger, Cathie Wood... helping you analyze the market

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An open-source GitHub project, ai-hedge-fund, uses 19 AI agents to replicate a hedge fund decision-making room, including Warren Buffett, Charlie Munger, Cathie Wood, and more, to help you judge the market. It has currently accumulated 56,600 stars. (Previous coverage: A lifespan of only 3 months! OpenAI unexpectedly shuts down its research writing platform Prism, pivoting strategically to "no longer pursuing side projects") (Background supplement: With geopolitical risks persisting, why has Bitcoin become a key liquidity target?) Imagine if you could hire Warren Buffett for valuation, Michael Burry to find shorts, Cathie Wood to scan for disruptive opportunities, and Charlie Munger to poke holes in everyone's arguments—would that become the strongest trading team in history? This article introduces an open-source project called ai-hedge-fund, where 13 AI agents mimicking famous investors run simultaneously, outputting signals at the same time... Finally, a portfolio manager synthesizes all opinions into a trading decision (currently accumulated 56,600 GitHub stars). 1. Warren Buffett: "Oracle of Omaha," head of Berkshire Hathaway, buys only quality companies with deep moats and honest management, then lets time do the work. 2. Charlie Munger: Buffett's partner of 60 years, uses interdisciplinary "mental models" from physics, psychology, and biology to dissect business logic. 3. Ben Graham: Father of value investing, Buffett's teacher, core concept is "margin of safety," buying at prices significantly lower than intrinsic value. 4. Peter Lynch: Legendary manager of the Fidelity Magellan Fund, advocates investing in companies you truly understand and looking for "ten-baggers." 5. Phil Fisher: Pioneer of growth investing, requires "scuttlebutt" due diligence before betting, asking customers and employees. 6. Michael Burry: Prototype for The Big Short, a deep-value hunter with contrarian thinking, famously shorted the entire US housing market alone in 2005. 7. Cathie Wood: Founder of ARK Invest, bets heavily on disruptive technologies like genomics, AI, electric vehicles, and space, accepting extreme volatility for over five years. 8. Bill Ackman: Activist investor, takes large positions and then publicly pressures boards for reform, representing the "buy in and force change" approach. 9. Stanley Druckenmiller: Former lead trader for Soros Fund Management, master of macro trading, focuses on asymmetric risk-reward ratios and betting big when right. 10. Nassim Taleb: Author of The Black Swan, does not predict market direction, focuses on identifying undervalued extreme tail risks and anti-fragile structures. 11. Aswath Damodaran: NYU professor and "Dean of Valuation," breaks down every company into a cash flow story, where numbers and narratives are equally important. 12. Mohnish Pabrai: Indian-American investor, calls himself a "copy-paste Buffett," core philosophy is finding low-risk, high-uncertainty bets with "heads I win, tails I don't lose much" (Dhandho). 13. Rakesh Jhunjhunwala: "The Warren Buffett of India," self-made billionaire starting from $100, passed away in 2022, the most iconic long-term investor in the Indian stock market. The remaining 6 are analytical/operational agents that help you make the final decision. The core of this system is a "multi-agent architecture." In plain terms: it's not one AI doing everything, but multiple AIs each performing their own duties, with a coordinator making the final judgment. The 19 agents operate in three layers: - 13 named after famous investors, each assigned to follow a corresponding investment philosophy. - 5 analytical agents responsible for valuation, sentiment, fundamentals, technicals, and risk. - Finally, a portfolio manager integrates the decisions. Users simply input stock tickers, such as AAPL, MSFT, NVDA, and the system triggers all agents to execute synchronously, outputting signal suggestions from each "investment master," which the portfolio manager then integrates into a final position. Technically, it supports mainstream large language models like OpenAI, Anthropic (Claude), DeepSeek, and Groq, and can also be connected to Ollama for local execution. Underlying market data comes from the Financial Datasets API, providing stock fundamentals and financial report information. The interface provides both command-line tools and a visual web application, with Python and TypeScript accounting for 60% and 40% of the code respectively. ai-hedge-fund has spread rapidly in the community recently, not just because of the functionality itself. It demonstrates an increasingly mainstream system design logic: rather than having one large language model act as an omniscient

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