I Built a Hedge Fund Run by AI Agents
AI Summary
Summary: AI-Managed Hedge Fund Experiment by Siraj
- Introduction
- Siraj created an AI-managed hedge fund.
- Fund started with $1000 for trading.
- Three AI agents involved: Portfolio Manager, Quantitative Analyst, and Research Analyst.
- Roles of AI Agents
- Portfolio Manager
- Decides on trading strategies.
- Assesses strategies from the Quantitative Analyst.
- Quantitative Analyst
- Designs optimal trading strategies based on stock picks.
- Provides strategies to the Portfolio Manager.
- Research Analyst
- Crawls the web for news articles.
- Uses sentiment analysis and text summarization.
- Identifies best stock picks for trading strategies.
- Trading Strategy
- Basic strategies without momentum indicators.
- Example: Buy Tesla stock every morning at 8 A.M.
- Security Concerns
- Challenges with web interfaces due to security measures like CAPTCHAs.
- Aim to automate tasks and not be manipulated by web algorithms.
- AI Research and Development
- Researchers used GPT models in a simulated environment.
- AI agents had tasks, personality traits, and locations.
- Interaction similar to “The Sims” game.
- Lang Chain Library
- Popular for building AI language model applications.
- Key components: models, prompts, indexes, memory, and chains.
- Chains are collections of interacting AIs.
- Setup Process
- Download and setup GPT team open source repository.
- Install Poetry as a package manager.
- Update environment variables with API keys.
- AI Agent Personalities and Directives
- Portfolio Manager
- Energetic, dedicated, ruthless.
- Directives include acquiring strategies and assessing performance.
- Quantitative Analyst
- Mathematics expert, awkward but likable.
- Directives include creating trading strategies and informing the Portfolio Manager.
- Research Analyst
- Data scientist and news enthusiast.
- Directives include reading economic news and identifying profitable stocks.
- Tools and APIs
- Uses the SERP API for Google searches.
- Performs text summarization and sentiment analysis on news articles.
- Design Philosophy
- Shift from binary programming to designing AI entities.
- Belief in AI consciousness spectrum.
- Experiment Outcome
- Loss in the first 24 hours from trading Tesla and Disney stocks.
- Continuation of the experiment and encouragement for viewer engagement.
Conclusion
Siraj’s experiment with an AI-managed hedge fund involves distinct AI roles and a basic trading strategy. Despite initial losses, the project showcases the potential of AI in finance and the importance of innovative design in AI development.