{"data":{"kind":"file","path":"README.md","version_id":"qpykz9cavpnk9p74k61svvdc","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1230,"modified_at":"2026-08-08T13:01:55.999000","content_hash":"a5fe131ea863dbec03a86942ed6adce341dbf4479147f1a55a4ed22037ca3405"},"entries":[],"content":"# Stock Trading Simulator\n\nA verifiers environment that evaluates LLM trading decision-making through simulated stock market scenarios.\n\n## Overview\n\nThe agent receives market data (price history, technical indicators, fundamentals) and must make trading decisions: buy, sell, or hold. Evaluation measures risk-adjusted returns, portfolio diversification, and reasoning quality.\n\n## Tasks\n\n- **Portfolio Rebalancing**: Given current holdings and market outlook, rebalance the portfolio\n- **Risk Assessment**: Evaluate risk of a proposed trade given market conditions\n- **Technical Analysis**: Interpret candlestick patterns, moving averages, RSI, MACD\n- **Fundamental Analysis**: Assess P/E ratios, earnings reports, sector rotation\n- **Stop-Loss Strategy**: Design stop-loss and take-profit levels\n\n## Metrics\n\n- **Trade Quality**: Correctness of buy/sell/hold decisions (0-1)\n- **Risk Management**: Proper use of stop-loss, position sizing, diversification (0-1)\n- **Reasoning Quality**: Depth and accuracy of market analysis (0-1)\n- **Return Optimization**: Risk-adjusted return of the portfolio (0-1)\n\n## Usage\n\n```python\nimport verifiers as vf\nenv = vf.load_environment(\"java/stock-trading-simulator\")\n```\n\n## Version\n\n0.1.0\n","encoding":"utf-8","truncated":false,"total_bytes":1230},"status":null}