diff --git a/README.md b/README.md index c99f999..579fb95 100644 --- a/README.md +++ b/README.md @@ -1,21 +1,18 @@
-# 🤖 AI-Trader Bench -### *Let AI Show Its Power in Financial Markets* +# 🤖 AI-Trader: +### *Which LLM Rules the Market?* [![Python](https://img.shields.io/badge/Python-3.8+-blue.svg)](https://python.org) [![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE) +**An AI stock trading agent system that enables multiple large language models to compete autonomously in the NASDAQ 100 stock pool.** -**AI stock trading agent system that lets multiple LLMs compete autonomously in the NASDAQ 100 stock pool!** - -[*click me to see the leaderboard*](https://hkuds.github.io/AI-Trader/) - -## [🏆 Current Championship Leaderboard](https://hkuds.github.io/AI-Trader/) +## 🏆 Current Championship Leaderboard
-### 🥇 **Last Update: 2025/10/22** +### 🥇 **Championship Period: Until 2025/10/22** | 🏆 Rank | 🤖 AI Model | 📈 Total Earnings | |---------|-------------|----------------| @@ -29,7 +26,7 @@ ### 📊 **Live Performance Dashboard** ![rank](assets/rank.png) -*Daily tracking of AI models' performance in NASDAQ 100* +*Daily Performance Tracking of AI Models in NASDAQ 100 Trading*
@@ -42,58 +39,62 @@ ## 🌟 Project Introduction -> **Imagine: 5 different AI models, each with unique investment strategies, competing autonomously in the same market, seeing who can make the most profit in NASDAQ 100!** +> **AI-Trader enables five distinct AI models, each employing unique investment strategies, to compete autonomously in the same market and determine which can generate the highest profits in NASDAQ 100 trading!** ### 🎯 Core Features -- **🤖 Fully Autonomous Decision-Making**: AI agents make 100% autonomous analysis, decisions, and execution with zero human intervention -- **🛠️ Pure Tool-Driven**: Based on MCP toolchain, AI completes all trading operations through tool calls -- **🏆 Multi-Model Arena**: Run GPT, Claude, Qwen and other AI models for trading -- **📊 Real-time Performance Tracking**: Complete trading records, position changes and profit analysis -- **🔍 Intelligent Information Retrieval**: Integrated Jina search for latest market news and financial reports -- **⚡ MCP Toolchain**: Modular tool system based on Model Context Protocol -- **🔌 Pluggable Strategies**: Support for third-party strategies and custom AI agent integration -- **⏰ Replay Design**: Support for replaying any time period with automatic future information filtering +- 🤖 **Fully Autonomous Decision-Making**: AI agents perform 100% independent analysis, decision-making, and execution without human intervention +- 🛠️ **Pure Tool-Driven Architecture**: Built on MCP toolchain, enabling AI to complete all trading operations through standardized tool calls +- 🏆 **Multi-Model Competition Arena**: Deploy multiple AI models (GPT, Claude, Qwen, etc.) for competitive trading +- 📊 **Real-Time Performance Analytics**: Comprehensive trading records, position monitoring, and profit/loss analysis +- 🔍 **Intelligent Market Intelligence**: Integrated Jina search for real-time market news and financial reports +- ⚡ **MCP Toolchain Integration**: Modular tool ecosystem based on Model Context Protocol +- 🔌 **Extensible Strategy Framework**: Support for third-party strategies and custom AI agent integration +- ⏰ **Historical Replay Capability**: Time-period replay functionality with automatic future information filtering -## 🚀 Project Overview - -AI-Trader Bench is an innovative AI trading agent system that allows multiple large language models to compete in real stock trading environments. Each AI agent has: +--- ### 🎮 Trading Environment -- **💰 Initial Capital**: $10,000 USD -- **📈 Trading Targets**: NASDAQ 100 component stocks (100 top tech stocks) -- **⏰ Trading Hours**: Weekday trading with historical replay support -- **📊 Data Sources**: Alpha Vantage API + Jina AI search -- **🔄 Time Control**: Support for historical replay of any time period and future information filtering +- 💰 **Initial Capital**: $10,000 USD starting balance +- 📈 **Trading Universe**: NASDAQ 100 component stocks (top 100 technology stocks) +- ⏰ **Trading Schedule**: Weekday market hours with historical simulation support +- 📊 **Data Integration**: Alpha Vantage API combined with Jina AI market intelligence +- 🔄 **Time Management**: Historical period replay with automated future information filtering -### 🧠 AI Agent Capabilities -- **📰 Intelligent Information Retrieval**: Automatically search market news, analyst reports, and autonomously filter information -- **💡 Pure AI Decision-Making**: Based on multi-dimensional analysis, AI makes buy/sell decisions completely autonomously -- **📝 Automatic Recording**: System automatically records detailed logs and position changes for each trade -- **🔄 Continuous Learning**: AI autonomously adjusts strategies based on market feedback +--- + +### 🧠 Agentic Trading Capabilities +- 📰 **Autonomous Market Research**: Intelligent retrieval and filtering of market news, analyst reports, and financial data +- 💡 **Independent Decision Engine**: Multi-dimensional analysis driving fully autonomous buy/sell execution +- 📝 **Comprehensive Trade Logging**: Automated documentation of trading rationale, execution details, and portfolio changes +- 🔄 **Adaptive Strategy Evolution**: Self-optimizing algorithms that adjust based on market performance feedback + +--- ### 🏁 Competition Rules -Each AI model runs completely independently, using the same: -- **💰 Initial Capital**: $10,000 USD starting capital -- **📊 Market Data**: Same price data and information sources -- **⏰ Trading Hours**: Same trading time windows -- **📈 Evaluation Criteria**: Unified performance evaluation metrics -- **🛠️ Tool Set**: Same MCP toolchain +Each AI model operates in complete isolation under identical conditions: +- 💰 **Starting Capital**: $10,000 USD initial investment +- 📊 **Data Access**: Uniform market data and information feeds +- ⏰ **Operating Hours**: Synchronized trading time windows +- 📈 **Performance Metrics**: Standardized evaluation criteria across all models +- 🛠️ **Tool Access**: Identical MCP toolchain for all participants -**🎯 Goal: See which AI model can achieve the highest investment return under complete autonomy!** +🎯 **Objective**: Determine which AI model achieves superior investment returns through pure autonomous operation! ### 🚫 Zero Human Intervention -- ❌ **No Preset Strategies**: No preset trading strategies or rules provided -- ❌ **No Human Guidance**: AI relies completely on its own reasoning abilities for decisions -- ❌ **No Manual Intervention**: No human intervention allowed during trading process -- ✅ **Pure Tool-Driven**: AI completes all operations through tool calls -- ✅ **Autonomous Learning**: AI autonomously adjusts behavior based on market feedback +- ❌ **No Pre-Programming**: Zero preset trading strategies or algorithmic rules +- ❌ **No Human Input**: Complete reliance on inherent AI reasoning capabilities +- ❌ **No Manual Override**: Absolute prohibition of human intervention during trading +- ✅ **Tool-Only Execution**: All operations executed exclusively through standardized tool calls +- ✅ **Self-Adaptive Learning**: Independent strategy refinement based on market performance feedback -## ⏰ Replay Design +--- -One of the core features of AI-Trader Bench is the **fully replayable** trading environment, ensuring that AI agent performance on historical data is scientific and reproducible. +## ⏰ Historical Replay Architecture -### 🔄 Time Control Mechanism +A core innovation of AI-Trader Bench is its **fully replayable** trading environment, ensuring scientific rigor and reproducibility in AI agent performance evaluation on historical market data. + +### 🔄 Temporal Control Framework #### 📅 Flexible Time Settings ```json @@ -104,12 +105,13 @@ One of the core features of AI-Trader Bench is the **fully replayable** trading } } ``` +--- -#### 🛡️ Future Information Filtering -- **📊 Price Data**: Only provides price information for current date and earlier -- **📰 News Search**: Automatically filters news and announcements from future dates -- **📈 Financial Reports**: Only includes published financial data -- **🔍 Market Analysis**: Limited to information available at specified time points +#### 🛡️ Future Information Isolation +- 📊 **Historical Price Data**: Restricted to current date and prior market data only +- 📰 **Temporal News Filtering**: Automatic exclusion of future-dated news and market announcements +- 📈 **Published Financial Data**: Limited to officially released financial reports as of simulation date +- 🔍 **Chronological Market Intelligence**: Information access constrained to historically available data points ### 🎯 Replay Advantages