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strategy-prioritization

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Strategy Prioritization

交易策略优先级划分

Quick Start

快速开始

When prioritizing strategies:
  1. Inventory all available strategies across codebase
  2. Score each strategy on 4 factors (Performance, Risk, Operations, Business)
  3. Rank strategies by composite score
  4. Generate deployment recommendations
  5. Identify gaps blocking promotion
确定策略优先级时：
  1. 梳理代码库中所有可用策略
  2. 从四个维度（表现、风险、运营、业务）对每个策略评分
  3. 根据综合得分对策略排序
  4. 生成部署建议
  5. 识别阻碍策略推广的短板

Scoring Framework

评分框架

Four-Factor Scoring (1-5 scale, equal weights)

四因子评分法（1-5分制，权重均等）

Composite Score = (Performance + Risk + Ops + Business) / 4
综合得分 =（表现得分 + 风险得分 + 运营得分 + 业务得分）/ 4

1. Performance (25%)

1. 表现（25%）

  • 5: Strong metrics (Sharpe > 2.0, Win Rate > 70%, PF > 2.5)
  • 4: Good metrics (Sharpe > 1.5, Win Rate > 65%, PF > 2.0)
  • 3: Moderate or limited data
  • 2: Weak metrics or no recent backtests
  • 1: No performance data
  • 5分：指标优异（Sharpe比率>2.0，胜率>70%，利润因子（PF）>2.5）
  • 4分：指标良好（Sharpe比率>1.5，胜率>65%，利润因子（PF）>2.0）
  • 3分：指标一般或数据有限
  • 2分：指标薄弱或无近期回测数据
  • 1分：无任何表现数据

2. Risk Readiness (25%)

2. 风险就绪度（25%）

  • 5: Comprehensive controls (stops, sizing, limits, correlation)
  • 4: Good controls (stops, sizing, basic limits)
  • 3: Basic controls (stops only)
  • 2: Minimal controls
  • 1: No risk management
  • 5分：具备全面风控措施（止损、仓位控制、限额、相关性管理）
  • 4分：具备良好风控措施（止损、仓位控制、基础限额）
  • 3分：具备基础风控措施（仅止损）
  • 2分：风控措施极少
  • 1分：无任何风险管理

3. Operational Readiness (25%)

3. 运营就绪度（25%）

  • 5: Fully configured, tested, documented, monitored
  • 4: Configured and tested, minor doc gaps
  • 3: Basic config, needs testing/docs
  • 2: Code exists, not configured
  • 1: Experimental/incomplete
  • 5分：已完成配置、测试、文档编写与监控部署
  • 4分：已配置并测试，仅存在少量文档缺口
  • 3分：基础配置完成，需补充测试与文档
  • 2分：代码已存在，但未配置
  • 1分：处于实验阶段或未完成开发

4. Business Importance (25%)

4. 业务重要性（25%）

  • 5: Explicitly recommended, high priority, proven
  • 4: Important, good business case
  • 3: Moderate value
  • 2: Low priority/experimental
  • 1: Example/research only
  • 5分：明确推荐、高优先级、已验证有效性
  • 4分：重要性高、业务案例充分
  • 3分：价值中等
  • 2分：低优先级/实验性策略
  • 1分：仅为示例/研究用途

Prioritization Process

优先级划分流程

Step 1: Strategy Discovery

步骤1：策略发现

bash
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bash
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Find all strategies

查找所有策略

find openalgo/strategies/scripts -name ".py" -type f find openalgo_backup_/strategies/scripts -name ".py" -type f
find AITRAPP/AITRAPP/packages/core/strategies -name ".py" -type f
find openalgo/strategies/scripts -name ".py" -type f find openalgo_backup_/strategies/scripts -name ".py" -type f
find AITRAPP/AITRAPP/packages/core/strategies -name ".py" -type f

Check documentation

检查文档

grep -r "strategy" *.md | grep -i "priorit|rank|recommend"
undefined
grep -r "strategy" *.md | grep -i "priorit|rank|recommend"
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Step 2: Data Collection

步骤2：数据收集

For each strategy, gather:
Performance Data:
  • Backtest results from 
    openalgo/strategies/backtest_results/
  • Metrics from 
    ALL_STRATEGIES_COMPARISON.md
  • Ranking reports and CSV files
  • AITRAPP backtest engine results
Risk Assessment:
python
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针对每个策略，收集以下信息：
表现数据：
  • 来自
    openalgo/strategies/backtest_results/
    的回测结果
  • ALL_STRATEGIES_COMPARISON.md
    中的指标
  • 排名报告与CSV文件
  • AITRAPP回测引擎结果
风险评估：
python
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Check for risk controls in code

检查代码中的风控措施

grep -r "stop_loss|max_drawdown|position_size|risk_per_trade" strategy_file.py grep -r "daily_loss_limit|weekly_loss_limit|correlation" strategy_file.py

**Operational Check:**
- Config files: `AITRAPP/AITRAPP/configs/app.yaml`
- Deployment scripts: `openalgo/strategies/scripts/`
- Documentation: Strategy `.md` files
- Monitoring: Log files, status endpoints

**Business Value:**
- Check `STRATEGY_PRIORITIZATION_REPORT.md`
- Review `ALL_STRATEGIES_COMPARISON.md` recommendations
- Look for explicit deployment recommendations
grep -r "stop_loss|max_drawdown|position_size|risk_per_trade" strategy_file.py grep -r "daily_loss_limit|weekly_loss_limit|correlation" strategy_file.py

**运营检查：**
- 配置文件：`AITRAPP/AITRAPP/configs/app.yaml`
- 部署脚本：`openalgo/strategies/scripts/`
- 文档：策略对应的`.md`文件
- 监控：日志文件、状态端点

**业务价值：**
- 查看`STRATEGY_PRIORITIZATION_REPORT.md`
- 参考`ALL_STRATEGIES_COMPARISON.md`中的建议
- 查找明确的部署推荐内容

Step 3: Scoring

步骤3：评分

python
def score_strategy(strategy_name, performance_data, risk_data, ops_data, business_data):
    """Score strategy on 4 factors"""
    perf_score = score_performance(performance_data)  # 1-5
    risk_score = score_risk(risk_data)  # 1-5
    ops_score = score_operations(ops_data)  # 1-5
    biz_score = score_business(business_data)  # 1-5
    
    composite = (perf_score + risk_score + ops_score + biz_score) / 4.0
    
    return {
        'name': strategy_name,
        'performance': perf_score,
        'risk': risk_score,
        'operations': ops_score,
        'business': biz_score,
        'composite': composite,
        'gaps': identify_gaps(perf_score, risk_score, ops_score, biz_score)
    }
python
def score_strategy(strategy_name, performance_data, risk_data, ops_data, business_data):
    """Score strategy on 4 factors"""
    perf_score = score_performance(performance_data)  # 1-5
    risk_score = score_risk(risk_data)  # 1-5
    ops_score = score_operations(ops_data)  # 1-5
    biz_score = score_business(business_data)  # 1-5
    
    composite = (perf_score + risk_score + ops_score + biz_score) / 4.0
    
    return {
        'name': strategy_name,
        'performance': perf_score,
        'risk': risk_score,
        'operations': ops_score,
        'business': biz_score,
        'composite': composite,
        'gaps': identify_gaps(perf_score, risk_score, ops_score, biz_score)
    }

Step 4: Ranking and Categorization

步骤4：排序与分类

python
def categorize_strategy(composite_score):
    """Categorize by action needed"""
    if composite_score >= 4.0:
        return "Deploy", "Ready for live trading"
    elif composite_score >= 3.0:
        return "Paper Trade", "Needs validation"
    elif composite_score >= 2.5:
        return "Optimize", "Needs improvements"
    else:
        return "Hold", "Experimental or incomplete"
python
def categorize_strategy(composite_score):
    """Categorize by action needed"""
    if composite_score >= 4.0:
        return "Deploy", "Ready for live trading"
    elif composite_score >= 3.0:
        return "Paper Trade", "Needs validation"
    elif composite_score >= 2.5:
        return "Optimize", "Needs improvements"
    else:
        return "Hold", "Experimental or incomplete"

Step 5: Generate Report

步骤5：生成报告

Create prioritization report with:
  • Ranked table (sorted by composite score)
  • Detailed analysis per strategy
  • Gap identification
  • Deployment roadmap
  • Action items
创建优先级报告，包含：
  • 排序表格（按综合得分排序）
  • 每个策略的详细分析
  • 短板识别
  • 部署路线图
  • 行动项

Key Metrics Reference

关键指标参考

Performance Metrics

表现指标

Sharpe Ratio:
  • Excellent: > 2.0
  • Good: 1.5 - 2.0
  • Acceptable: 1.0 - 1.5
  • Poor: < 1.0
Win Rate:
  • Excellent: > 70%
  • Good: 60-70%
  • Acceptable: 50-60%
  • Poor: < 50%
Profit Factor:
  • Excellent: > 2.5
  • Good: 2.0 - 2.5
  • Acceptable: 1.5 - 2.0
  • Poor: < 1.5
Max Drawdown:
  • Excellent: < 10%
  • Good: 10-15%
  • Acceptable: 15-20%
  • Poor: > 20%
Sharpe比率：
  • 优异：>2.0
  • 良好：1.5-2.0
  • 可接受：1.0-1.5
  • 较差：<1.0
胜率：
  • 优异：>70%
  • 良好：60-70%
  • 可接受：50-60%
  • 较差：<50%
利润因子：
  • 优异：>2.5
  • 良好：2.0-2.5
  • 可接受：1.5-2.0
  • 较差：<1.5
最大回撤：
  • 优异：<10%
  • 良好：10-15%
  • 可接受：15-20%
  • 较差：>20%

Risk Controls Checklist

风控措施检查表

  • Stop loss implemented
  • Position sizing based on risk
  • Daily loss limit
  • Weekly loss limit
  • Max drawdown protection
  • Correlation management
  • Max positions limit
  • Volatility-based sizing
  • 已实现止损
  • 基于风险的仓位控制
  • 每日亏损限额
  • 每周亏损限额
  • 最大回撤保护
  • 相关性管理
  • 最大持仓限额
  • 基于波动率的仓位调整

Operational Checklist

运营就绪检查表

  • Configuration file exists
  • Parameters documented
  • Deployment script available
  • Logging implemented
  • Monitoring integrated
  • Error handling robust
  • Documentation complete
  • Tested in sandbox
  • 配置文件已存在
  • 参数已文档化
  • 部署脚本可用
  • 已实现日志记录
  • 已集成监控
  • 错误处理机制完善
  • 文档完整
  • 已在沙箱环境测试

Integration Points

集成点

With Backtesting

与回测系统集成

  • Use backtest results to score performance
  • Reference 
    backtesting-analysis
    skill for metrics
  • Check 
    openalgo/strategies/backtest_results/
    for data
  • 使用回测结果进行表现评分
  • 参考
    backtesting-analysis
    技能获取指标
  • 从
    openalgo/strategies/backtest_results/
    获取数据

With Strategy Management

与策略管理系统集成

  • Coordinate deployment with 
    strategy-manager
    subagent
  • Check current running strategies before prioritizing
  • Verify strategy status via web UI
  • 与
    strategy-manager
    子代理协同部署
  • 优先级划分前检查当前运行的策略
  • 通过Web UI验证策略状态

With Risk Management

与风险管理系统集成

  • Align with 
    risk-management
    skill requirements
  • Verify risk controls meet standards
  • Check portfolio-level constraints
  • 对齐
    risk-management
    技能的要求
  • 验证风控措施符合标准
  • 检查组合层面的约束

Common Patterns

常见模式

High-Priority Strategies

高优先级策略

Look for:
  • Documented backtests with strong metrics
  • Comprehensive risk controls
  • Fully configured and tested
  • Explicitly recommended in docs
特征：
  • 有文档记录的回测结果，指标优异
  • 全面的风控措施
  • 已完成配置与测试
  • 文档中明确推荐

Strategies Needing Work

需要优化的策略

Identify:
  • Missing backtest data → Run backtests
  • Weak risk controls → Add risk management
  • Configuration gaps → Create configs
  • Documentation gaps → Write docs
识别特征：
  • 缺失回测数据 → 运行回测
  • 风控措施薄弱 → 补充风险管理
  • 配置缺口 → 创建配置文件
  • 文档缺口 → 编写文档

Archived Strategies

归档策略

  • Check 
    openalgo_backup_*/strategies/
    for high-performing archived strategies
  • Consider porting to current location if score is high
  • Verify code compatibility before promotion
  • 检查
    openalgo_backup_*/strategies/
    中的高表现归档策略
  • 若评分高，考虑迁移至当前目录
  • 推广前验证代码兼容性

Report Template

报告模板

markdown
undefined
markdown
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Strategy Prioritization Plan - [Date]

策略优先级计划 - [日期]

Executive Summary

执行摘要

  • Total strategies: X
  • Top 3: [List]
  • Ready to deploy: X
  • Need work: X
  • 策略总数：X
  • 前三名：[列表]
  • 可部署：X
  • 需要优化：X

Ranked Strategies

排序后的策略

RankStrategyPerfRiskOpsBizScoreActionLocation
1Strategy A55454.75Deployopenalgo/strategies/scripts/
排名策略表现风险运营业务综合得分行动位置
1Strategy A55454.75部署openalgo/strategies/scripts/

Detailed Analysis

详细分析

Strategy A

Strategy A

Performance (5/5): [Details] Risk (5/5): [Details] Operations (4/5): [Details] Business (5/5): [Details] Gaps: None Next Steps: Deploy to live trading
表现（5/5）：[详情] 风险（5/5）：[详情] 运营（4/5）：[详情] 业务（5/5）：[详情] 短板：无 下一步：部署至实盘交易

Gaps Blocking Promotion

阻碍推广的短板

  • Strategy X: Missing backtest data
  • Strategy Y: No risk controls
  • 策略X：缺失回测数据
  • 策略Y：无风控措施

Deployment Roadmap

部署路线图

  1. Week 1: Deploy top 3 strategies
  2. Week 2: Paper trade next tier
  3. Month 1: Optimize remaining strategies
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  1. 第1周：部署前三名策略
  2. 第2周：次一级策略进行纸盘交易
  3. 第1个月：优化剩余策略
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Best Practices

最佳实践

  1. Be Conservative: When data is missing, score low and mark as gap
  2. Prioritize Data: Strategies with documented performance rank higher
  3. Actionable Output: Provide specific next steps, not just scores
  4. Regular Updates: Re-prioritize as strategies are tested/deployed
  5. Document Gaps: Clearly identify blockers to enable promotion
  6. Consider Context: Market conditions and instrument types matter
  1. 保守评分：数据缺失时，给予低分并标记为短板
  2. 数据优先：有文档记录表现的策略排名更高
  3. 输出可执行内容：提供具体下一步行动，而非仅评分
  4. 定期更新：策略测试/部署后重新进行优先级划分
  5. 明确短板：清晰识别阻碍推广的问题
  6. 考虑场景：市场环境与标的类型会影响策略优先级

Troubleshooting

故障排除

Missing Performance Data

缺失表现数据

  • Run backtests using 
    backtesting-analysis
    skill
  • Check archived backtest results
  • Look for comparison reports
  • 使用
    backtesting-analysis
    技能运行回测
  • 检查归档的回测结果
  • 查找比较报告

Incomplete Risk Controls

风控措施不完善

  • Reference 
    risk-management
    skill for requirements
  • Add missing controls before promotion
  • Test risk limits in sandbox
  • 参考
    risk-management
    技能的要求
  • 推广前补充缺失的风控措施
  • 在沙箱环境测试风控限额

Configuration Issues

配置问题

  • Check existing configs in 
    AITRAPP/AITRAPP/configs/
  • Create config files following patterns
  • Verify parameters are documented
  • 检查
    AITRAPP/AITRAPP/configs/
    中的现有配置
  • 参考已有模板创建配置文件
  • 验证参数已文档化

Related Resources

相关资源

  • Subagent: 
    strategy-prioritization-planner
    for detailed planning
  • Skill: 
    backtesting-analysis
    for performance metrics
  • Skill: 
    risk-management
    for risk control standards
  • Skill: 
    trading-strategy-development
    for strategy structure
  • Reports: 
    STRATEGY_PRIORITIZATION_REPORT.md
    , 
    ALL_STRATEGIES_COMPARISON.md
  • 子代理：
    strategy-prioritization-planner
    用于详细规划
  • 技能：
    backtesting-analysis
    获取表现指标
  • 技能：
    risk-management
    获取风控标准
  • 技能：
    trading-strategy-development
    获取策略结构
  • 报告：
    STRATEGY_PRIORITIZATION_REPORT.md
    , 
    ALL_STRATEGIES_COMPARISON.md