This project explores the potential of artificial financial intelligence - a focused implementation of AI for trading and investing research.
⭐️ first full concise documentation video (watch here)
📀 follow all updates here on youtube: https://www.youtube.com/playlist?list=PLXrNVMjRZUJg4M4uz52iGd1LhXXGVbIFz
⚠️ IMPORTANT: This is an experimental project. There are NO guarantees of profitability. Trading involves substantial risk of loss.
We're researching AI agents for trading that will eventually leverage AFI. With 4 years of experience training humans through our bootcamp, we're exploring where AI agents might complement human trading operations, and later replace trading human operations. This is experimental research, not a profitable trading solution.
AI agents will be able to build a better quant portfolio than humans. i've spent the last 4 years building quant systems & training others to do so. 2025 is about replicating that success but with ai agents doing it instead of me. in 2026 i will release a paper of my findings after a full year of testing ai agents in quant vs the last 4 years of humans.
AI agents might help address common trading challenges: - Emotional reactions - Ego-driven decisions - Inconsistent execution - Fatigue effects - Impatience - Fear & Greed cycles
While we use the RBI framework for strategy research, we're exploring AI agents as potential tools. We're in early stages with LLM technology, investigating possibilities in the trading space.
There is no token associated with this project and there never will be. any token launched is not affiliated with this project, moon dev will never dm you. be careful. don't send funds anywhere
all the video updates are consolidated in the below playlist on youtube 📀 https://www.youtube.com/playlist?list=PLXrNVMjRZUJg4M4uz52iGd1LhXXGVbIFz
There is no token associated with this project and there never will be. any token launched is not affiliated with this project, moon dev will never dm you. be careful. don't send funds anywhere
PLEASE READ CAREFULLY:
Overall trading approach
NO AI agent can guarantee profitable trading
Project updates will be posted in discord, join here: moondev.com
trading_agent.py): Example agent that analyzes token data via LLM to make basic trade decisionsstrategy_agent.py): Manages and executes trading strategies placed in the strategies folderrisk_agent.py): Monitors and manages portfolio risk, enforcing position limits and PnL thresholdscopy_agent.py): monitors copy bot for potential tradeswhale_agent.py): monitors whale activity and announces when a whale enters the marketsentiment_agent.py): analyzes Twitter sentiment for crypto tokens with voice announcementslistingarb_agent.py): identifies promising Solana tokens on CoinGecko before they reach major exchanges like Binance and Coinbase, using parallel AI analysis for technical and fundamental insightsfocus_agent.py): randomly samples audio during coding sessions to maintain productivity, providing focus scores and voice alerts when focus drops (~$10/month, perfect for voice-to-code workflows)funding_agent.py): monitors funding rates across exchanges and uses AI to analyze opportunities, providing voice alerts for extreme funding situations with technical context 🌙liquidation_agent.py): tracks liquidation events with configurable time windows (15min/1hr/4hr), providing AI analysis and voice alerts for significant liquidation spikes 💦chartanalysis_agent.py): looks at any crypto chart and then analyzes it with ai to make a buy/sell/nothing reccomendation.fundingarb_agent.py): tracks the funding rate on hyper liquid to find funding rate arbitrage opportunities between hl and solanarbi_agent.py): uses deepseek to research trading strategies based on the youtube video, pdf, or words you give it. then sends to his ai friend who codes out the backtest.Click the star button to save it to your GitHub favorites
🍴 Fork the Repo
This lets you make changes and track updates
💻 Open in Your IDE
Recommended: Use Cursor or Windsurfer for AI-enabled coding
🔑 Set Environment Variables
.env.example for required variables.env file with your keys:⚠️ Never commit or share your API keys!
🤖 Customize Agent Prompts
/agents folderEach agent has configurable parameters
📈 Implement Your Strategies
/strategies folderThorough testing required before live trading
🏃♂️ Run the System
main.pyBuilt with love by Moon Dev - Pioneering the future of AI-powered trading
The content presented is for educational and informational purposes only and does not constitute financial advice. All trading involves risk and may not be suitable for all investors. You should carefully consider your investment objectives, level of experience, and risk appetite before investing.
Past performance is not indicative of future results. There is no guarantee that any trading strategy or algorithm discussed will result in profits or will not incur losses.
CFTC Disclaimer: Commodity Futures Trading Commission (CFTC) regulations require disclosure of the risks associated with trading commodities and derivatives. There is a substantial risk of loss in trading and investing.
I am not a licensed financial advisor or a registered broker-dealer. Content & code is based on personal research perspectives and should not be relied upon as a guarantee of success in trading.
$ claude mcp add MoonDev-Trading-Ai-Agents \
-- python -m otcore.mcp_server <graph>