--- name: a-share-event-f16e5bf14d79 description: A股事件驱动分析/公告解读/政策影响评估。当用户说"事件分析"、"公告解读"、"政策影响"、"并购"、"增发"、"回购"、"股权激励"、"XX出了什么公告"、"这个政策对XX有什么影响"、"解禁"、"定增"、"事件驱动"、"event analysis"、"公告分析"、"重组"、"资产注入"、"战略合作"、"利好还是利空"时触发。MUST USE when user asks about event-driven analysis, corporate announcement interpretation, policy impact assessment, M&A analysis, or any event's impact on stock price. 分析公司公告、政策变化、并购重组等事件对股价和基本面的潜在影响，评估事件的正面/负面程度和持续性。通过 cn-stock-data 获取行情和财务数据，结合 web 搜索获取事件详情。支持机构事件点评风格（formal）和个人事件笔记风格（brief）。 --- ### 数据源 ```bash SCRIPTS="$SKILLS_ROOT/cn-stock-data/scripts" # 实时行情（事件发生后的市场反应） python "$SCRIPTS/cn_stock_data.py" quote --code [CODE] # K线（事件前后股价走势对比） python "$SCRIPTS/cn_stock_data.py" kline --code [CODE] --freq daily --start [事件前30日] # 财务指标（评估事件对基本面的影响） python "$SCRIPTS/cn_stock_data.py" finance --code [CODE] # 资金流向（机构对事件的反应） python "$SCRIPTS/cn_stock_data.py" fund_flow --code [CODE] --days 30 ``` 补充 web 搜索：公告原文、政策全文、分析师点评、历史类似事件案例。 ### Workflow (5 steps): **Step 1: 事件识别与分类** | 事件类型 | 子类 | 典型影响方向 | |---------|------|------------| | **公司公告** | 业绩预告/快报 | 取决于超/低预期 | | | 分红方案 | 通常正面 | | | 增发/配股 | 短期偏负面（摊薄） | | | 回购 | 正面（公司认为低估） | | | 大股东增持 | 正面信号 | | | 大股东减持/解禁 | 负面信号 | | | 股权激励 | 通常正面（绑定管理层） | | | 并购重组 | 取决于标的质量和价格 | | | 关联交易 | 需评估是否损害小股东利益 | | **政策事件** | 行业政策（利好） | 板块普涨 | | | 行业政策（利空） | 板块普跌 | | | 货币/财政政策 | 系统性影响 | | | 监管政策 | 取决于具体内容 | | **市场事件** | 指数调整（纳入/剔除） | 纳入正面，剔除负面 | | | 北向资金大幅增减 | 信号意义 | | | 融券/做空 | 负面压力 | **Step 2: 事件详情获取** 1. Web 搜索事件详情（公告原文/政策全文） 2. cn-stock-data 获取事件前后行情数据 3. Web 搜索分析师/媒体的初步解读 **Step 3: 影响评估** **定量评估**： - 事件对 EPS 的影响（增发摊薄多少/并购增厚多少） - 事件对资产负债表的影响（回购减少现金/增发增加净资产） - 事件对估值的影响（新业务带来的估值重塑） **定性评估**： - 影响范围：公司级 / 行业级 / 市场级 - 影响持续性：一次性 / 短期（1-3月）/ 中期（3-12月）/ 长期（>1年） - 影响确定性：高（已落地）/ 中（已公告待执行）/ 低（传闻/预期） - 市场预期差：事件是否已被预期？超出预期程度？ **综合评级**： | 维度 | 评分 | |------|------| | 影响方向 | 正面 / 中性 / 负面 | | 影响程度 | 重大 / 中等 / 轻微 | | 持续时间 | 一次性 / 短期 / 中长期 | | 确定性 | 高 / 中 / 低 | **Step 4: 历史类比**（可选） Web 搜索类似事件的历史案例： - 同公司类似事件的历史反应 - 同行业类似事件的市场反应 - 提供参考但不做简单类推 **Step 5: 输出** ### 风格说明 | 维度 | formal（机构事件点评） | brief（个人事件笔记） | |------|---------------------|---------------------| | 篇幅 | 2-4 页 | 半页 | | 事件描述 | 完整（含公告/政策原文引用） | 一段话概述 | | 定量影响 | 详细计算（EPS/净资产影响） | 核心数字 | | 定性评估 | 完整评级表 | 一句话判断 | | 历史类比 | 2-3 个案例 | 无或 1 个 | | 结论 | 客观分析正反面 | 可加操作建议 | | 免责声明 | 需要 | 不需要 | ### 关键规则 1. **先看公告原文**：所有分析基于公告/政策原文，不基于二手解读 2. **区分"预期内"和"超预期"**：市场已充分预期的事件影响有限 3. **短期反应 ≠ 长期影响**：股价短期反应可能过度，长期取决于基本面实质变化 4. **关注细节**：增发价格/回购价格区间/减持比例/激励条件等细节决定影响程度 5. **不做简单类推**：历史类似事件仅供参考，不能直接预测本次结果 6. **与其他 skill 联动**：事件分析后可用 a-share-earnings-analysis 评估财务影响，用 a-share-thesis 更新投资论点 ## 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-event/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Dave AI. ## 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. # Dave AI resource metadata Creator / publisher: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/a-share-event/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Finance & Accounting, Marketing, Sales Roles: Business Development, Financial Analyst, Growth Marketer, Market Research Analyst, Product Marketer Specialties: API Tools: Cn Stock Data, Web Search Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: f68081b52dffe7f32e50f7f656f1acb1e27a4bb86f0c687190465dda59580bd6