--- name: peer-comparison-calculation-300743f3f0f1 description: 用于排名/对比的同类对比计算原子 skill，适用于通用行业金融计算场景。 --- # 同类对比计算 Skill ## 数据来源 本 Skill 支持多种金融数据输入格式，核心数据来源包括： ### 1. 对比对象数据 - **产品数据**：基金、理财产品、投资组合等 - **公司数据**：上市公司、非上市公司等 - **行业数据**：不同行业、板块的数据 - **基准数据**：市场基准、行业基准等 ### 2. 对比指标数据 - **收益率指标**：累计收益率、年化收益率、区间收益率 - **风险指标**：波动率、最大回撤、夏普比率 - **规模指标**：资产规模、市值、营收规模 - **财务指标**：ROE、ROA、净利润率等 ### 3. 分类标签数据 - **行业分类**：所属行业、细分行业 - **风格标签**：价值/成长、大盘/小盘 - **地区标签**：所属地区、市场类型 - **时间标签**：成立时间、存续时间 ### 4. 数据格式要求 - **CSV格式**：标准对比数据，包含对象标识和指标列 - **Excel格式**：支持多工作表对比数据 - **JSON格式**：结构化对比数据 - **数据库连接**：支持SQL数据库直接查询 > 说明：本 Skill 不包含数据采集功能，需要用户提供清洗后的对比数据。建议对比对象数量不少于10个，以便进行有意义的排名和对比分析。 --- ## 功能 本 Skill 提供全面的同类对比分析能力，涵盖多种对比方法： ### 1. 排名分析 - **绝对排名**：按指标值进行绝对排名 - **相对排名**：相对于基准的相对排名 - **分位数排名**：计算指标的分位数排名 - **滚动排名**：计算滚动窗口内的排名变化 ### 2. 对比分析 - **横向对比**：同一时点不同对象的对比 - **纵向对比**：同一对象不同时点的对比 - **分组对比**：按分类标签进行分组对比 - **基准对比**：与基准对象的对比分析 ### 3. 统计指标 - **分位数统计**：计算各分位数的指标值 - **均值对比**：计算均值及与均值的差异 - **标准差对比**：计算标准差及相对位置 - **偏度峰度**：分析指标的分布特征 ### 4. 可视化分析 - **排名图表**：生成排名变化的可视化图表 - **对比图表**：生成对比分析的可视化图表 - **分布图表**：生成指标分布的可视化图表 ### 5. 数据处理能力 - **缺失值处理**：支持前向填充、均值填充等方法 - **异常值检测**：基于统计方法识别和处理异常值 - **数据标准化**：支持不同数据源的格式统一 - **权重调整**：支持按权重进行加权对比 --- ## 使用示例 ### 输出示例 ```json { "comparison_period": "2024-01-01 to 2024-12-31", "total_objects": 50, "ranking": [ { "object_id": "FUND001", "object_name": "基金A", "metric_value": 18.5, "absolute_rank": 1, "percentile_rank": 98, "relative_to_mean": 1.25, "relative_to_median": 1.15 } ], "statistics": { "mean": 14.8, "median": 16.1, "std": 5.2, "min": 5.3, "max": 18.5, "percentile_25": 11.2, "percentile_75": 17.8 }, "group_comparison": { "金融": { "mean": 12.5, "count": 10 }, "科技": { "mean": 16.8, "count": 15 } } } ``` --- ## 注意事项与限制 ### 1. 数据质量要求 - 对比数据需要经过清洗和验证 - 对比对象需要具有可比性 - 指标计算口径需要统一 ### 2. 对比方法选择 - 不同对比方法的结果可能不同 - 排名结果受样本数量影响 - 分组对比需要合理的分类标准 ### 3. 时间序列分析 - 排名和对比结果具有时间依赖性 - 不同时间区间的结果不可直接比较 - 需要考虑市场环境的影响 ### 4. 综合判断原则 - 单一排名指标不能全面反映对象特征 - 需要结合多个指标进行综合分析 - 应结合行业特点和市场环境进行判断 ### 5. 使用限制 - 本 Skill 输出为技术分析结果，不构成投资建议 - 使用者应结合专业判断和具体业务场景 - 对于重大决策，建议咨询专业投资顾问 --- ## 参考资料 - 见 references/ 目录中的相关文档，包括： - 同类对比分析方法手册 - 排名计算方法指南 - 统计分析方法说明 - 数据处理方法说明文档 ## License - 本 skill 代码部分采用 MIT License，详见 `LICENSE` 文件 - 依赖与运行环境以 `requirements.txt` 为准 - 文档内容采用 CC BY 4.0 许可 --- Source attribution: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/archive/peer-comparison-calculation/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/archive/peer-comparison-calculation/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Finance & Accounting Roles: Data Analyst, Financial Analyst, Market Research Analyst Specialties: Specialty not specified Tools: Csv, Excel, Json, Sql Database Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: dd755259dcfc023aec258ab2156ffdbfca8d40729e8c6c7208844f7e87911fd6