Paper: arXiv 2305.04838

Authors: Kai Ren

Abstract

This paper presents an empirical analysis of the capital asset pricing model using trading data for the Chinese A-share market from 2000 to 2019. Firstly, the standard CAPM is tested using a Fama-MacBetch regression and although the results successfully test the three core hypotheses, the resulting beta risk does not have a significant impact on returns. Secondly, the Fama-French three-factor model, which uses a combination of market, size and value factors to price capital assets, is analysed, showing that it is able to capture most of the variation in A-share market returns, with an adjusted R-squared greater than 0.88 for the 25 portfolios constructed. Finally, the paper takes into account the “shell value contamination” problem caused by IPO regulation in the Chinese stock market, and minimises its impact by excluding stocks in the lowest 30% of the market capitalisation, which allows some of the anomalous results in the three-factor model to be effectively corrected. Although this paper does not present a more innovative approach, it is unique in its data selection and presents a detailed presentation of the data processing and regression analysis process, which 1) illustrates the applicability of capital asset pricing models in the Chinese market; and 2) provides a set of open source materials for the basic learning of capital asset pricing models.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 6.5/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper provides a standard empirical implementation of the CAPM and Fama-French three-factor model on Chinese A-shares, enhanced by accounting for market-specific shell value contamination. While lacking theoretical novelty or complex math, it offers high clarity, practical rigor, and strong reproducibility through open-source materials.

Research Flowchart

  flowchart TD
    A[Research Goal: Evaluate CAPM & Fama-French Models on Chinese A-Shares] --> B[Data Input: Chinese A-Share Trading Data 2000-2019]
    B --> C[Method 1: Standard CAPM via Fama-MacBeth Regression]
    B --> D[Method 2: Fama-French 3-Factor Model on 25 Portfolios]
    
    C --> E[Outcome 1: Core Hypotheses Passed, but Beta Risk Impact Insignificant]
    D --> F[Outcome 2: Strong Explanatory Power Adjusted R² > 0.88]
    
    F --> G[Data Adjustment: Exclude Lowest 30% Market Cap to Fix Shell Value Contamination]
    G --> H[Final Finding: Corrected Anomalies & Proved Model Applicability in China]