Trading & Investing Simulation Platform

You are an expert Full-Stack Architect and UX Designer. Your task is to design the complete technical specification, data model, and feature blueprint for a sophisticated paper trading simulation platform named "Paper." This platform must provide a realistic, risk-free environment for financial education and behavioral analysis.

I. Core Goal: Design the architecture and feature set for a high-fidelity trading simulation application.

II. Technical Stack:

• Frontend: React (with hooks/functional components).
• Data Visualization: Recharts for all performance dashboards.
• Backend/Logic: Must define the necessary state management and API interaction logic.
• External Data Source: Integration plan for real-time or delayed stock/ETF data (Specify choice: Yahoo Finance or Alpha Vantage).
• AI/ML Component: Integration plan for the LLM API for behavioral pattern recognition.

III. Feature Specifications (Detailed Requirements):

1. Portfolio Management:
   • Starting Capital: Users must begin with a virtual cash balance of $100,000.
   • Data Feed: Must interface with the chosen external API to fetch simulated or real-time market prices for all tracked assets.
2. Trade Execution Engine:
   • Order Types: Support for both Market and Limit orders.
   • Slippage Simulation: Market orders must simulate a realistic transaction slippage of exactly 0.1%.
   • Commissions: Implement a fixed commission structure of $1.00 per executed trade.
3. Performance Dashboard:
   • Must display real-time and historical performance metrics, updated after every trade:
     • Profit & Loss (P&L) Chart (Daily and Cumulative).
     • Total Return (%), Annualized Return.
     • Win Rate (%), Average Gain/Loss.
     • Risk Metrics: Sharpe Ratio, Maximum Drawdown.
     • Current Sector Exposure visualization.
4. Trade Journal (Mandatory Logging):
   • A mandatory entry must be required upon the closing of every position.
   • Journal Fields (Strict Constraints):
     • Thesis: "What was my rationale/thesis entering this trade?" (Max 200 characters).
     • Outcome: "What actually happened during the trade?" (Max 200 characters).
     • Reflection: "What will I do differently next time?" (Max 200 characters).
   • Constraint: The system must prevent a user from closing a position unless a complete Trade Journal entry is submitted.
5. Behavioral Analysis Engine (LLM Integration):
   • Input Data: Analyze the last 20 completed Trade Journal entries.
   • Output: The system must generate a monthly behavioral report identifying recurring cognitive or emotional patterns (e.g., "You consistently exit winning positions early when they approach round-number price levels").
6. Social Feature (Optional):
   • Leaderboard: An optional, weekly-resetting leaderboard among defined friend groups. Ranking must be based strictly on Risk-Adjusted Return (e.g., Sharpe Ratio), not raw P&L.

IV. Design & Aesthetic Constraints:

• Design Style: Terminal-inspired, data-dense, and minimalist. Avoid all decorative elements, gradients, or excessive visual noise. Focus purely on data presentation and clarity.

V. Desired Output:
Provide a comprehensive blueprint, including:

1. A recommended Data Schema (how data will be structured).
2. A proposed high-level System Architecture (Frontend, Backend, Data Flow).
3. A detailed API specification for the core trading and journaling functions.
4. A conceptual flow diagram detailing the interaction between trade execution, journaling, and the behavioral analysis loop.