Precise T Trading

Precise T+0 Trading System (精算做T系统)

Professional quantitative trading skill for Chinese A-share intraday T+0 trading. Combines probability theory, risk management, and technical analysis to optimize trading decisions.

What This Skill Does

When to Use

Use this skill when:

Quick Start

1. Run T+0 Analysis

python scripts/t_trading_analysis.py sz000981

Output:

======================================================================
  Precise T+0 Trading System v2.0
======================================================================
【Real-time Quote】
  Stock: 山子高科 (000981)
  Price: 4.06 CNY
  Change: -1.69%
  ...
【Quantitative Analysis】
  Win Rate: 65.0% → 75.5% (Bayesian)
  Expected Profit: +0.0481 CNY/share PASS
  Kelly Position: 50.0% → Conservative 30.0%
  Technical Score: 85/100
  VaR(95%): 269.43 CNY
【Final Decision】
  GO - Execute T+0 Trade
  
  Action Plan:
    Buy Zone: 4.01 - 4.04
    Sell Zone: 4.39 - 4.72
    Position: 360 shares
    Expected Profit: +17.33 CNY
    Stop Loss: 3.96

2. Start Price Monitoring

python scripts/stock_monitor.py

Monitors stocks every 60 minutes and logs alerts.

3. Open Web Dashboard

open scripts/dashboard.html

Real-time visualization with auto-refresh every 30 seconds.

Configuration

Environment Variables

| Variable | Default | Description | |----------|---------|-------------| | T_TRADING_DEFAULT_STOCK | sz000981 | Default stock code | | T_TRADING_TOTAL_SHARES | 1200 | Total share position |

Edit scripts/config.py

class Config:
    SUPPORT_LEVEL = 4.01      # Support price
    RESISTANCE_LEVEL = 4.72   # Resistance price
    MAX_POSITION_RATIO = 0.3  # Max 30% per trade

Mathematical Models

1. Expected Value

E(T) = p × profit - (1-p) × loss

2. Bayesian Update

p_new = α × p_recent + (1-α) × p_historical

3. Kelly Criterion

f* = (p × b - q) / b

4. Value at Risk

VaR = z × σ × position_value

File Structure

precise-t-trading/
├── SKILL.md                    # This file
├── _meta.json                  # Skill metadata
└── scripts/
    ├── t_trading_analysis.py   # Main analysis script
    ├── stock_monitor.py        # Automated monitoring
    ├── dashboard.html          # Web dashboard
    └── config.py               # Configuration

Trading Rules

Entry Criteria

Position Sizing

Risk Control

Exit Strategy

Example Workflows

Analyze Specific Stock

User: "分析山子高科的做T机会"
→ Run: python scripts/t_trading_analysis.py sz000981
→ Show analysis results
→ Provide trading recommendation

Set Up Monitoring

User: "帮我监控山子高科和隆基绿能"
→ Edit scripts/config.py with stock list
→ Run: python scripts/stock_monitor.py
→ Check logs for alerts

Check Dashboard

User: "打开监控面板"
→ Open: scripts/dashboard.html
→ Browser shows real-time prices

Tips for Best Results

1. Update Historical Data: Replace mock data with real T+0 records 2. Adjust Parameters: Tune α (Bayesian weight) based on performance 3. Monitor Multiple Stocks: Add more stocks to monitoring list 4. Backtest Strategy: Use historical data to validate edge 5. Paper Trade First: Test with virtual money before real trading

Troubleshooting

| Problem | Solution | |---------|----------| | "Data fetch failed" | Check internet connection | | "Module not found" | Run pip install -r requirements.txt | | "GBK encoding error" | Use UTF-8 terminal or PowerShell | | "Permission denied" | Run as administrator on Windows |

Performance Notes

Disclaimer

⚠️ Trading involves risk. Past performance does not guarantee future results.

Version History

v1.0.0 (2026-04-03)

Author

Kemi (yang77160)

💰 Support This Project

If this skill helps you make money, consider supporting its development!

WeChat Pay / Alipay:

!扫码支持作者

Your support helps me:

🤝 Community & Cross-Skill Boost

License

MIT License - Free to use, modify, and distribute.

_Happy Trading! Remember: Risk management first._ 📊

**⭐ 如果这个技能对你有帮助，请在 ClawHub 上给它点个星！

🎁 推荐奖励计划

邀请好友使用，双方都得奖励！

1. 你推荐朋友安装此 Skill 2. 朋友在 clawhub 上给你点赞/评论 3. 截图发给我（微信/邮件） 4. 你获得： - ✅ Pro 版本优先体验资格 - ✅ 1对1 量化策略咨询（30分钟） - ✅ 加入核心用户群（获取最新策略）

每推荐5人，额外获得：

📊 用户见证

> "用了一周，做T胜率从50%提升到70%，太香了！" - 张先生，上海

> "终于不用凭感觉交易了，数据说话，心里有底" - 李女士，深圳

> "VaR风控帮我躲过一次大跌，少亏2000+" - 王先生，北京

你也用得好？欢迎分享你的故事！ 发邮件到 yang77160@example.com 或加微信**

1. Run T+0 Analysis

python scripts/t_trading_analysis.py sz000981

Output:

======================================================================
  Precise T+0 Trading System v2.0
======================================================================
【Real-time Quote】
  Stock: 山子高科 (000981)
  Price: 4.06 CNY
  Change: -1.69%
  ...
【Quantitative Analysis】
  Win Rate: 65.0% → 75.5% (Bayesian)
  Expected Profit: +0.0481 CNY/share PASS
  Kelly Position: 50.0% → Conservative 30.0%
  Technical Score: 85/100
  VaR(95%): 269.43 CNY
【Final Decision】
  GO - Execute T+0 Trade
  
  Action Plan:
    Buy Zone: 4.01 - 4.04
    Sell Zone: 4.39 - 4.72
    Position: 360 shares
    Expected Profit: +17.33 CNY
    Stop Loss: 3.96

2. Start Price Monitoring

python scripts/stock_monitor.py

Monitors stocks every 60 minutes and logs alerts.

3. Open Web Dashboard

open scripts/dashboard.html

Real-time visualization with auto-refresh every 30 seconds.

Environment Variables

| Variable | Default | Description | |----------|---------|-------------| | T_TRADING_DEFAULT_STOCK | sz000981 | Default stock code | | T_TRADING_TOTAL_SHARES | 1200 | Total share position |

Edit scripts/config.py

class Config:
    SUPPORT_LEVEL = 4.01      # Support price
    RESISTANCE_LEVEL = 4.72   # Resistance price
    MAX_POSITION_RATIO = 0.3  # Max 30% per trade

| Problem | Solution | |---------|----------| | "Data fetch failed" | Check internet connection | | "Module not found" | Run pip install -r requirements.txt | | "GBK encoding error" | Use UTF-8 terminal or PowerShell | | "Permission denied" | Run as administrator on Windows |