G2量化交易策略技能

> 基于21组策略回测验证的最优A股量化交易系统

3,891 stars

byopenclaw

View on GitHub Installation ↓

Best use case

G2量化交易策略技能 is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

> 基于21组策略回测验证的最优A股量化交易系统

Teams using G2量化交易策略技能 should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/g2-trading-strategy/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/austin0208/g2-trading-strategy/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/g2-trading-strategy/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How G2量化交易策略技能 Compares

Feature / Agent	G2量化交易策略技能	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

> 基于21组策略回测验证的最优A股量化交易系统

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

AI Agents for Marketing

Discover AI agents for marketing workflows, from SEO and content production to campaign research, outreach, and analytics.

AI Agents for Startups

Explore AI agent skills for startup validation, product research, growth experiments, documentation, and fast execution with small teams.

AI Agents for Coding

Browse AI agent skills for coding, debugging, testing, refactoring, code review, and developer workflows across Claude, Cursor, and Codex.

SKILL.md Source

# G2量化交易策略技能

> 基于21组策略回测验证的最优A股量化交易系统
> 版本: v6.0-g2-optimal | 回测收益: +26.7% | 夏普比率: 1.12

## 📋 技能概述

本技能提供一套完整的A股量化交易解决方案，基于v5.2评分体系优化而来，经过301天历史回测验证（2025-01-03~2026-04-03），在沪深300成分股中实现：

- **总收益**: +26.7%（年化+21.2%）
- **夏普比率**: 1.12
- **最大回撤**: 15.2%
- **超额收益**: +23.6%（跑赢大盘）

## 🎯 核心特性

### 1. 智能选股系统
- v5.2九维度综合评分（位置/量能/趋势/筹码/业绩/均线/换手率/情绪/超跌反弹）
- 量比>1.2硬过滤（确保资金活跃入场）
- 评分≥40分筛选

### 2. 严格风控体系
- 固定2%止损纪律
- 固定25%止盈纪律
- 最大3持仓，单只25%仓位

### 3. 尾盘交易策略
- 14:00扫描市场
- 14:30-15:00尾盘买入
- 避免盘中波动风险

## 📊 评分维度详解

| 维度 | 权重 | 评分规则 |
|:---|:---:|:---|
| 超跌反弹 | 20% | 近21日跌幅>30%→+20分, >25%→+15分 |
| 量能 | 15% | 量比>1.5→+15分, >1.2→+10分 |
| 位置 | 12% | 距60日均线<20%→+20分, <30%→+15分 |
| 业绩 | 12% | 净利润增长→加分 |
| 趋势 | 10% | MACD金叉+KDJ金叉→+15分 |
| 筹码 | 10% | 底部缩量+低位→+15分 |
| 均线 | 8% | MA5>MA20>MA60→+10分 |
| 换手率 | 8% | 4%~12%→+10分 |
| 情绪 | 5% | 涨跌幅2%~6%→+5分 |

## 🚀 使用方法

### 基础命令

```bash
# 扫描潜力股
python3 stock_analysis_v5.py

# 执行交易
python3 trading_workflow.py

# 查看持仓
cat positions.json
```

### 配置文件

所有策略参数在 `trading_unified_config.json` 中统一管理：

```json
{
  "version": "v6.0-g2-optimal",
  "filter_criteria": {
    "min_score": 40,
    "vol_ratio_min": 1.2
  },
  "trading_rules": {
    "stop_loss_pct": 2.0,
    "take_profit_full_pct": 25.0
  }
}
```

## 📁 文件结构

```
g2-trading-strategy/
├── SKILL.md                 # 技能定义文件
├── README.md                # 详细文档
├── trading_unified_config.json  # 统一配置文件
├── stock_analysis_v5.py     # v5.2分析系统
├── trading_workflow.py      # 交易工作流
├── positions.json           # 持仓记录
├── scripts/
│   ├── stock_api_tencent.py # 腾讯API数据源
│   └── auto_backup.py       # 自动备份
└── backtest_cache/          # 历史数据缓存
```

## ⚠️ 风险提示

1. 本策略回测结果不代表未来收益
2. A股市场波动大，请控制仓位
3. 建议先用模拟盘验证
4. 严格遵守止损纪律

## 📜 版本历史

- v6.0-g2-optimal (2026-04-05): 加入量比硬过滤，回测+26.7%
- v6.0-multi-agent (2026-04-03): 多代理系统
- v5.2 (2026-03-30): 九维度评分体系

## 💡 技术支持

如有问题，请提交Issue或联系技术支持。

---

**本技能定价: ¥199/次下载**

作者: 投资大师 (Investment Master)

Related Skills

---

3891

from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891

from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891

from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891

from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891

from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891

from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891

from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891

from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891

from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure