--- name: a-share-cross-market-a9613fa7aa82 description: 跨市场联动分析（A股/港股/美股/大宗商品）。当用户说"跨市场"、"联动"、"A股和美股"、"港股联动"、"AH溢价"、"中概股"、"美股跌了A股会跌吗"、"原油对A股影响"、"汇率影响"、"cross market"、"人民币贬值利好什么"、"跨市场联动"、"全球市场"时触发。MUST USE when user asks about cross-market correlation, AH premium, how US/HK markets affect A-shares, or commodity/FX impact on Chinese stocks. 分析A股与全球主要市场（美股/港股/商品/汇率）的联动关系、AH溢价、中概股映射、大宗商品传导。支持研报风格（formal）和快速参考风格（brief）。 --- ### 数据源 ```bash # cn-stock-data 统一层获取行情（跨市场用 snowball 路由） python -c " import subprocess, json # A股主要指数（通过 cn-stock-data → efinance 路由） # 上证指数 000001, 沪深300 000300, 创业板指 399006 # 用 cn-stock-data skill 的 quote/kline 接口 # 港股（snowball 路由，HK 前缀） # 恒生指数 HK00001, 恒生科技 HKHSTECH, H股指数 HK00011 # 美股（snowball 路由，US 前缀） # 标普500 US.SPX, 纳斯达克 US.IXIC, 道琼斯 US.DJI # 需要 pysnowball token 才能获取港美股数据 import pysnowball as ball # ball.set_token('your_token') # ball.quotec('SH000001,HKHSI,.DJI,.IXIC,.INX') # 跨市场报价 # ball.kline('SH000001', period='day', count=-120) # K线数据 " # AH 股比较数据（akshare 直接调用） python -c " import akshare as ak # AH 股比价 df = ak.stock_a_ah_comparison_em() print(df.head(20).to_string()) # 返回字段：代码/名称/A股价格/H股价格/比价(A/H)/溢价率 " # 大宗商品（akshare） python -c " import akshare as ak # 国际原油 df = ak.futures_foreign_hist(symbol='CL') # WTI原油 # 伦敦金 df = ak.futures_foreign_hist(symbol='GC') # COMEX黄金 # LME铜 df = ak.futures_foreign_hist(symbol='HG') # COMEX铜 print(df.tail(5).to_string()) " ``` 补充 web 搜索：美股收盘情况、大宗商品实时价格、美元指数、离岸人民币汇率、美联储议息会议纪要、全球央行动态。 ### Workflow (5 steps): **Step 1: 多市场数据获取** 根据用户需求确定分析范围： - **全面联动**："跨市场分析" → A股指数 + 美股三大指数 + 恒指 + 商品 + 汇率 - **双市场对比**："A股和美股联动" → 聚焦 A 股与美股 - **AH 溢价**："AH溢价分析" → 聚焦 A+H 双上市公司 - **商品传导**："原油对A股影响" → 聚焦特定商品 → A股传导链 - **汇率影响**："人民币贬值影响" → 聚焦汇率 → 行业影响 获取数据（近 60-120 个交易日）： | 市场 | 标的 | 数据源 | |------|------|--------| | A股 | 上证/沪深300/创业板指 | cn-stock-data (efinance路由) | | 美股 | S&P500/纳斯达克/道琼斯 | cn-stock-data (snowball路由) | | 港股 | 恒生指数/恒生科技/H股指数 | cn-stock-data (snowball路由) | | 商品 | 原油/黄金/铜/铁矿石 | akshare futures | | 汇率 | 美元指数/离岸人民币 | web搜索 | **Step 2: 相关性与领先滞后分析** **相关系数计算**： - 取日收益率序列，计算 Pearson 相关系数（近 60 日/120 日） - 相关系数解读：|r|>0.7 强相关, 0.4-0.7 中等, <0.4 弱相关 **领先滞后关系**： - 计算滞后 1-5 日的互相关系数 - 判断谁领先谁：隔夜美股 → 次日 A 股开盘是最常见的领先关系 - 注意：领先关系会随市场阶段变化，非固定规律 **联动强度变化**： - 对比近期（20日）vs 中期（60日）相关系数，判断联动是否在加强/减弱 - 高联动阶段通常对应：全球风险事件、美联储政策转向、流动性冲击 **Step 3: AH 溢价分析（如涉及）** 通过 `ak.stock_a_ah_comparison_em()` 获取 AH 股数据： - **整体溢价水平**：恒生 AH 溢价指数（HSAHP）历史区间 100-160，均值约 130 - **个股溢价排序**：找出溢价最高/最低的股票 - **溢价变动趋势**：近期溢价是扩大还是收窄 - **套利信号**：极端溢价个股可能存在价值回归机会（但需考虑汇率/流动性/制度差异） | 溢价区间 | 市场状态 | 含义 | |---------|---------|------| | <110 | 罕见低溢价 | A股相对低估或港股相对高估 | | 110-130 | 正常区间 | 反映制度差异溢价 | | 130-150 | 偏高 | A股情绪偏热或港股承压 | | >150 | 极端高溢价 | A股显著高估，关注回归风险 | **Step 4: 传导机制分析** **资金流传导**： - 北向资金（沪深港通）→ A股直接影响 - 全球流动性（美联储政策）→ 新兴市场资金流向 → A股 - 美元强弱 → 人民币汇率 → 北向资金意愿 **情绪传导**： - 隔夜美股大涨/大跌 → A股开盘跳空 - VIX 恐慌指数飙升 → 全球risk-off → A股承压 - 中概股异动 → A股对标公司联动 **基本面传导**： - 原油上涨 → 化工/航空成本上升，油服/煤化工受益 - 铜价上涨 → 有色板块受益，新能源成本承压 - 美国经济衰退 → 中国出口承压 → 出口链公司 - 人民币贬值 → 出口企业受益，航空/造纸（美元债）承压 **政策传导**： - 美联储加息/降息 → 中美利差 → 资金流向 - 美国关税政策 → 贸易摩擦 → 相关行业 - 全球央行协同/分化 → 汇率波动 → 跨境资金 **Step 5: 输出** ### 风格说明 | 维度 | formal（机构跨市场研究） | brief（快速跨市场参考） | |------|----------------------|----------------------| | 篇幅 | 4-8 页 | 1-2 页 | | 市场覆盖 | A股+美股+港股+商品+汇率全覆盖 | 聚焦用户关心的2-3个市场 | | 相关性分析 | 完整相关系数矩阵+滞后分析 | 定性描述联动方向和强度 | | AH溢价 | 完整AH溢价表+历史对比 | 整体溢价水平+异常个股 | | 传导机制 | 详细多路径分析 | 核心传导链1-2条 | | 历史对比 | 类似历史情景回顾 | 不需要 | | 免责声明 | 需要 | 不需要 | ### 关键规则 1. **相关不等于因果**：两个市场同涨同跌不代表存在因果关系，可能受同一因素驱动 2. **联动强度因阶段而异**：A股受外盘影响程度在不同市场阶段差异显著（牛市中后期更独立，恐慌阶段高度联动） 3. **AH溢价有制度基础**：AH溢价不会归零，因为A/H两地存在投资者结构、流动性、交易制度的系统性差异 4. **汇率影响因行业而异**：人民币贬值对出口型企业利好，对进口依赖型/美元债较多企业利空，不可一概而论 5. **时差与交易时间**：美股收盘→A股开盘有时差，需注意盘后/盘前信息；港股与A股交易时间有重叠 6. **数据来源标注**：跨市场数据来源多样，务必标注每项数据的来源和时间点 7. **与其他 skill 联动**：跨市场分析结论可指导 a-share-sector（受影响行业）、a-share-northbound（北向资金分析）、a-share-macro（宏观政策背景） ## 使用示例 ### 示例 1: 基本使用 ```python # 调用 skill result = run_skill({ "param1": "value1", "param2": "value2" }) ``` ### 示例 2: 命令行使用 ```bash python scripts/run_skill.py --input data.json ``` --- Source attribution: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/a-share-cross-market/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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See the License for the specific language governing permissions and limitations under the License. # Mega AI Hub resource metadata Creator / publisher: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/a-share-cross-market/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Finance & Accounting, Marketing, Product Management Roles: Data Analyst, Financial Analyst, Growth Marketer, Market Research Analyst, Product Manager Specialties: API, Database Tools: Akshare, Pysnowball Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: d5cb1312d9d0af9f7d718f8efdd40790030b540914e5baa543a73e99cf97aabc