alter123-zz/quant-backtest
skills/quant-backtest/SKILL.md
量化策略回测工具。编写、回测和优化交易策略，分析历史表现。Keywords: 量化, 回测, 策略, quant, backtest, trading strategy.
$ install --global
skillsauthnpx skillsauth add alter123-zz/RaccoonClaw quant-backtestInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- quant-backtest
- description:
- 量化策略回测工具。编写、回测和优化交易策略，分析历史表现。Keywords: 量化, 回测, 策略, quant, backtest, trading strategy.
量化策略回测 — 编写和回测交易策略分析历史表现
概述
编写和回测交易策略分析历史表现。适用于量化交易策略开发、历史数据回测验证、策略参数优化、风险指标分析等场景。
触发关键词: 量化, 回测, 策略, quant, backtest, trading strategy
前置依赖
pip install pandas numpy backtrader matplotlib
核心能力
能力1：策略回测引擎——支持均线/MACD/RSI等常见策略
策略回测引擎——支持均线/MACD/RSI等常见策略
能力2：绩效分析——年化收益/最大回撤/夏普比率/胜率
绩效分析——年化收益/最大回撤/夏普比率/胜率
能力3：参数优化——网格搜索最优参数组合
参数优化——网格搜索最优参数组合
命令列表
| 命令 | 说明 | 用法 |
|------|------|------|
| backtest | 回测策略 | python3 scripts/quant_backtest_tool.py backtest [参数] |
| optimize | 参数优化 | python3 scripts/quant_backtest_tool.py optimize [参数] |
| report | 生成回测报告 | python3 scripts/quant_backtest_tool.py report [参数] |
使用流程
场景 1
回测双均线策略标的沪深300
执行：
python3 scripts/quant_backtest_tool.py backtest --strategy ma_cross --symbol 000300 --period 3y
场景 2
优化均线参数
执行：
python3 scripts/quant_backtest_tool.py optimize --strategy ma_cross --fast 5-20 --slow 20-60
场景 3
生成详细回测报告
执行：
python3 scripts/quant_backtest_tool.py report --format markdown
输出格式
# 📊 量化策略回测报告
**生成时间**: YYYY-MM-DD HH:MM
## 核心发现
1. [关键发现1]
2. [关键发现2]
3. [关键发现3]
## 数据概览
| 指标 | 数值 | 趋势 | 评级 |
|------|------|------|------|
| 指标A | XXX | ↑ | ⭐⭐⭐⭐ |
| 指标B | YYY | → | ⭐⭐⭐ |
## 详细分析
[基于实际数据的多维度分析内容]
## 行动建议
| 优先级 | 建议 | 预期效果 |
|--------|------|----------|
| 🔴 高 | [具体建议] | [量化预期] |
| 🟡 中 | [具体建议] | [量化预期] |
| 🟢 低 | [具体建议] | [量化预期] |
参考资料
原有链接
- Backtrader回测框架，量化策略回测
- 腾讯云量化策略开发参考
- Python量化回测实战
GitHub
- GitHub: Python量化回测框架，14k+ stars
HackerNews
- HackerNews: 量化策略回测的常见陷阱
- Reddit r/algotrading: algotrading社区AI相关讨论
微信公众号
- 微信公众号: Python量化策略回测入门到实战
小红书
- 小红书: Python量化策略回测从入门到实战
注意事项
- 所有分析基于脚本获取的实际数据，不编造数据
- 数据缺失字段标注"数据不可用"而非猜测
- 建议结合人工判断使用，AI分析仅供参考
- 首次使用请先安装Python依赖：
pip install pandas numpy backtrader matplotlib
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