一、评价依据
A financial center is a complex multi-dimensional system, and a single-scale ranking cannot reflect its true standing. This algorithm follows the core principles of the CPPPS evaluation specification—not copying public rankings, computing from underlying data, and adopting the multi-dimensional structure of 'Scale + Quality + Innovation + Contribution':
金融中心是一个复杂的多维度系统，单一规模排序无法反映其真实地位。本算法遵循 CPPPS 评价规范的核心原则——不摘抄公开榜单名次、以底层数据自算、采用"规模 + 质量 + 创新 + 贡献"的多维结构：
- 规模：金融中心首先是"大"。以股票市场总市值、银行体系总资产表征资本集聚与货币创造能力。
- 质量：金融中心的核心功能是"活"。以市场深度与流动性表征定价效率、交易活跃度与风险分散能力。
- 创新：金融中心的生命力在"新"。以金融科技生态（支付、数字金融、科技金融）表征未来竞争力。
- 贡献（CPPPS 特色维度）：金融中心的价值在"用"。以服务实体经济（企业融资、IPO、债券发行）与辐射区域（时区桥、区域枢纽）表征其对真实经济与区域发展的带动作用。
二、数学模型
Each indicator is range-standardized to [0,1]; large-span scale indicators are log-transformed first, then synthesized by dimension-weighted aggregation:
各指标经极差标准化到 [0,1]，规模类大跨度指标先取对数，再分维加权合成：
Market capitalization and banking assets are both first taken the natural logarithm (log1p) and then range-standardized. The purpose of the log transformation is to prevent ultra-large cities such as New York and Beijing from monopolizing the Scale dimension and to smooth the scale gaps.
市值与银行资产均先取自然对数（log1p）再极差标准化。取对数的目的是避免纽约、北京这类超大体量城市对规模维度形成垄断，使规模差距趋于平滑。
The weight design reflects 'scale as the base, quality as the core, innovation as the wings, and contribution as the soul': Quality (0.32) and Scale (0.30) form the basic foundation of a financial center, totaling 62%; Contribution (0.22) highlights this index's orientation toward the real economy and regional value; and Innovation (0.16) reflects the marginal boost fintech gives to the long-term competitiveness of a financial center.
权重设计体现"规模为基、质量为核、创新为翼、贡献为魂"：质量（0.32）与规模（0.30）构成金融中心的基本盘，合计占 62%；贡献（0.22）突出本指数的实体经济与区域价值导向；创新（0.16）体现金融科技对金融中心长期竞争力的边际提升。
三、指标与权重依据
| 指标 | 方向 | 权重 | 所属维度 | 依据 |
|---|
| 股票市场总市值 | 对数·正向 | 规模 0.55 | 规模 | 资本集聚与证券化深度 |
| 银行体系总资产 | 对数·正向 | 规模 0.45 | 规模 | 货币创造与信用中介能力 |
| 市场深度/流动性 | 正向 | 质量 1.00 | 质量 | 定价效率、交易活跃度、风险分散 |
| 金融科技生态 | 正向 | 创新 1.00 | 创新 | 支付、数字金融、科技金融竞争力 |
| 服务实体经济 | 正向 | 贡献 0.50 | 贡献 | 企业融资、IPO、债券发行的支持力 |
| 辐射区域 | 正向 | 贡献 0.50 | 贡献 | 时区桥、区域金融枢纽地位 |
四、数据来源与局限性
Total stock-market capitalization and total banking-system assets are public-knowledge approximations around 2024 (derived from public data of exchanges/regulators); market depth, fintech, serving the real economy and regional radiation are qualitative quantified approximations based on public information, all marked 'subject to official figures'. This model has the following limitations: first, the calibers of market capitalization and banking assets vary by city (New York includes the NYSE and Nasdaq, Beijing includes the headquarters of several large banks), so cross-city comparability is affected by administrative divisions and statistical calibers; second, the qualitative indicators carry subjective errors; third, institutional factors such as the regulatory environment, legal system and currency internationalization are not included. The ranking is for research and reference only and does not constitute any investment or policy advice.
股票市场总市值、银行体系总资产为 2024 年前后公开知识近似值（交易所/监管机构公开数据推算），市场深度、金融科技、服务实体经济、辐射区域为基于公开信息的定性量化近似值，一律标注"以官方为准"。本模型存在以下局限：其一，市值与银行资产的口径因城市而异（纽约包含纽交所与纳斯达克、北京包含多家大型银行总部），跨城可比性受行政区划与统计口径影响；其二，定性指标存在主观误差；其三，未纳入监管环境、法律体系、货币国际化等制度性因素。排名仅供研究与参考，不构成任何投资或政策建议。
五、参考文献
- 世界交易所联合会（WFE）：全球证券交易所市值与成交额统计。
- 国际清算银行（BIS）：Triennial Central Bank Survey 外汇与衍生品成交数据。
- 国际货币基金组织（IMF）：全球金融稳定报告及金融中心相关研究。
- 主要国家中央银行与银行业监管机构：银行体系总资产统计公报。
- 全球金融科技相关行业报告：金融科技生态与数字支付发展研究。
- CPPPS：《自有评价算法规范》，"规模 + 质量 + 创新 + 贡献"四维框架。