一、评价依据
A stock index is a composite carrier of market breadth and depth, and the evaluation of an index rests on three groups of grounds. First, theoretical grounds—the Efficient Market Hypothesis (Fama, 1970) reveals the relationship between the efficiency with which prices reflect information and market maturity; the idea of index investing and low-cost passive investing (Bogle) shows that the quality of an index itself (representativeness, investability, transparency) bears on resource-allocation efficiency. Second, functional grounds—among the three functions of capital markets (fundraising, pricing and resource allocation), the "financing function" directly serves the real economy and is the core dimension for measuring a market's "contribution". Third, evaluation-methodology grounds—the four iron rules followed by this index (public weights, public algorithm, public data sources, reproducibility) and the CPPPS four-layer indicator framework (objective, reputation, expert, contribution).
股票指数是市场广度与深度的综合载体，对指数的评价建立在三组依据之上：其一，学理依据——有效市场假说（Fama，1970）揭示价格对信息的反映效率与市场成熟度的关系；指数化投资与低成本被动投资的思想（Bogle）表明，指数本身的质量（代表性、可投资性、透明度）关乎资源配置效率；其二，功能依据——资本市场三大功能（筹资、定价、资源配置）中，"融资功能"直接服务于实体经济，是衡量市场"贡献"的核心维度；其三，评价方法论依据——本指数所遵循的四条铁律（权重公开、算法公开、数据源公开、可复现）与 CPPPS 四层指标框架（客观、声誉、专家、贡献）。
Based on the above grounds, this algorithm deconstructs a stock index into four measurable dimensions:
基于上述依据，本算法将股票指数解构为四个可测度的维度：
- 规模（Scale）：总市值与上市公司（成分股）数量——反映市场体量与广度，市值是定价权与抗冲击能力的基础。
- 质量（Quality）：成交活跃度（日均成交额）与近 10 年年化收益——流动性是市场深度的核心，长期回报是投资者真实获得感。
- 创新（Innovation）：科技股占比——反映市场产业结构的前瞻性与对新兴生产力的承载能力。
- 贡献（Contribution）：年度股权融资额（IPO+再融资）——反映市场把储蓄转化为企业资本、服务实体经济的能力，是 CPPPS 特色维度。
二、模型的数学结构
Each underlying indicator is first unified into the 0–1 range via min-max standardization, and large-span indicators (total market capitalization, number of listed companies, average daily turnover, equity financing volume) first take the natural logarithm to curb head monopoly:
各项底层指标首先经 min-max 标准化统一至 0–1 区间，大跨度指标（总市值、上市公司数、日均成交额、股权融资额）先取自然对数以抑制头部垄断：
The four-dimensional sub-scores are defined as follows:
四维子得分定义如下：
Here ′ denotes the 0–1 value after min-max standardization. The four dimensions are weighted and summed, and mapped to a 0–100 composite score:
其中 ′ 表示经 min-max 标准化后的 0–1 值。四维按权重加权求和，映射为 0–100 综合得分：
The weight design embodies the orientation of "equal emphasis on scale and quality, combined with both innovation and contribution": Scale accounts for 30% (volume is the foundation), Quality for 30% (liquidity and returns determine the market's quality), Innovation for 20% (the advancement of industrial structure), and Contribution for 20% (the financing function is the essence of a market serving the real economy). The four weights sum to 1, ensuring the scores are normalized and comparable.
权重设计体现"规模与质量并重、创新与贡献兼备"的导向：规模占 30%（体量是基础），质量占 30%（流动性与回报决定市场成色），创新占 20%（产业结构先进性），贡献占 20%（融资功能是市场服务实体经济的本质）。四项权重之和为 1，保证得分归一可比。
三、指标与权重依据
| 指标 | 方向 | 处理 | 权重 | 维度 | 依据 |
|---|
| 总市值 | 正向 | 对数 | 规模 0.60 | 规模 | 市场体量与定价权；Fama 有效市场 |
| 上市公司/成分股数 | 正向 | 对数 | 规模 0.40 | 规模 | 市场广度与多样性 |
| 日均成交额 | 正向 | 对数 | 质量 0.50 | 质量 | 流动性/成交活跃度；市场深度 |
| 近 10 年年化收益 | 正向 | 线性 | 质量 0.50 | 质量 | 长期回报；投资者真实获得感 |
| 科技股占比 | 正向 | 线性 | 创新 1.00 | 创新 | 产业结构前瞻性；承载新兴生产力 |
| 年度股权融资额 | 正向 | 对数 | 贡献 1.00 | 贡献 | 筹资功能；服务实体经济 |
四、数据来源与局限性
The total market capitalization, number of listed companies / constituents, average daily turnover, annualized return over the past 10 years, share of technology stocks, and annual equity financing volume used in this ranking are all estimates based on public knowledge (publicly known approximate values from the public materials of exchanges, index companies and financial data service providers), not item-by-item officially audited data, uniformly marked "subject to official figures" to clarify their traceable and revisable boundaries. The model has the following limitations: first, the constituent scope and compilation caliber of indices differ (for example, the Dow Jones Industrial Average has only 30 constituents, while the Nasdaq Composite covers thousands), so direct comparison involves caliber differences; second, the CSI 300 overlaps in constituents with the Shanghai Composite and the Shenzhen Component, and the relevant market capitalization and financing volume are approximated under their respective calibers, resulting in double counting; third, the definition of the technology-stock share (information technology + communication services vs. broad technology) varies with the caliber, and long-term returns are heavily influenced by the starting point of statistics; fourth, min-max standardization is sensitive to extreme values. This ranking is provided for research reference only and does not constitute any investment or resource-allocation advice.
本排名所采用的总市值、上市公司/成分股数、日均成交额、近 10 年年化收益、科技股占比及年度股权融资额，均为基于公开知识（各交易所、指数公司与财经数据服务商公开资料的常识近似值）的估计值，非逐项官方审计数据，统一标注"以官方为准"以明示其可追溯与可修正的边界。模型存在以下局限：其一，各指数成分范围、编制口径不同（如道琼斯工业平均仅 30 家成分股，纳斯达克综合覆盖数千家），直接比较存在口径差异；其二，沪深300 与上证综合、深证成份存在成分重叠，相关市值与融资额按各自口径近似，存在重复计入；其三，科技股占比的定义（信息科技+通信服务 vs. 广义科技）随口径不同而变化，长期回报受统计起点影响较大；其四，min-max 标准化对极端值敏感。本排名仅供研究参考，不构成任何投资或资源配置建议。
五、参考文献
- Fama, E. F.（1970）："Efficient Capital Markets: A Review of Theory and Empirical Work"，Journal of Finance。
- Bogle, J. C.（2007）：《The Little Book of Common Sense Investing》——指数化投资与低成本被动投资。
- Malkiel, B. G.（1973）：《A Random Walk Down Wall Street》——市场效率与指数表现。
- 世界交易所联合会（WFE）：年度统计（总市值、成交额、上市公司数、融资额口径参照）。
- 标普道琼斯指数、MSCI、富时罗素：指数编制方法学（成分与行业分类口径参照）。
- 各交易所（纽约证券交易所、纳斯达克、上海证券交易所、深圳证券交易所、香港交易所、东京证券交易所等）：公开市场数据。
- 上海证券交易所、深圳证券交易所：《股票市场统计月报》（融资额、市值、成交额口径参照）。