AITradingSimulator: Utilizes LLM to build a cryptocurrency quantitative trading simulation environment, supporting customized strategies and real-time performance analysis.

🚀 AITradingSimulator: A large-model-driven intelligent trading simulation platform

AITradingSimulator is an intelligent decision-making system that deeply integrates Large Language Models (LLM) with quantitative trading. It not only provides a simulated trading environment but also builds a complete quantitative research and teaching platform, allowing users to customize trading strategies, track market fluctuations in real time, and verify strategy feasibility through professional-grade performance analysis tools.

This system visualizes the AI's thought process through an interactive trading dashboard, allowing users to intuitively compare the trading performance of different models, greatly improving the learning efficiency and research depth of quantitative trading.

Quick access:
Official website:https://trade.easy2ai.com
Open source address:GitHub – AITradingSimulator

Core Functions Explained

🧠 AI Intelligent Decision Engine

• Highly customizable strategiesUsers can write personalized prompts for different models to create AI traders with unique trading styles.
• Multi-dimensional technical analysisIt integrates more than 15 professional technical indicators such as SMA, EMA, MACD, RSI, and Bollinger Bands to provide AI with accurate market analysis basis.
• Transparency of the reasoning processThe system fully records and displays the AI's thought process, making the decision-making process for each transaction clearly visible.
• Automated Trading CycleIt supports making decisions every 3 minutes, covering long/short operations and leverage adjustment from 1 to 20 times.

📊 Real-time market data and performance quantification

• Mainstream currency coverageReal-time monitoring of prices for major cryptocurrencies such as BTC, ETH, SOL, BNB, DOGE, and XRP.
• Professional-level indicator analysisIntroducing quantitative indicators such as Sharpe Ratio, Sortino Ratio, and Calmar Ratio to objectively evaluate strategy quality.
• Visualized data dashboardsIt uses ECharts to build profit curves, strategy rankings, and detailed backtesting reports.
• Risk control systemBuilt-in position monitoring and stop-loss/take-profit mechanisms simulate the risk management process of real trading.

🔐 Security Architecture and User Experience

• Account security managementIt has a complete registration and login system and session management, supports Linux DO OAuth login, and achieves data isolation and privacy protection.
• Financial-grade UI designIt adopts a professional visual style similar to Bloomberg/TradingView and supports responsive layout and dark mode.
• High-performance real-time updatesMarket data is automatically refreshed every 5 seconds to ensure the smoothness and timeliness of trading data.
• Flexible deploymentSupports one-click deployment with Docker and is compatible with mainstream AI interfaces such as OpenAI, DeepSeek, Claude, and Kimi.

Applicable Scenarios

• AI strategy stress testCompare the logical capabilities of different models such as GPT-4, Claude, and DeepSeek in trading scenarios under a risk-free environment.
• Quantitative Trading TeachingLearn the application of technical indicators, risk control, and performance backtesting methods through a visual interface.
• Multi-model horizontal comparisonCreate multiple strategy models and select the optimal trading logic through a performance ranking list.
• Financial AI DemoDemonstrating to others the entire process of large-scale models in the financial field, from data analysis to decision execution.

Technology Implementation Stack

Summary: Key Highlights

AITradingSimulator will "AI Reasoning" and"Quantitative Analysis"This perfect combination, its core value lies in transforming the black-box nature of AI decision-making into visible, quantifiable, and comparable trading experiments. It provides a low-barrier yet professional experimental environment for both researchers looking to explore the potential of AI trading and beginners eager to quickly get started with quantitative trading.