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