阅读|股票定价的高阶矩：来自中美市场的证据
High-order moments in stock pricing: evidence from the Chinese and US markets
股票定价的高阶矩：来自中美市场的证据
Yifan Chen
School of Economics and Management, Tsinghua University, Beijing, China
Zilin Chen
Department of Macro Research and Asset Allocation, China Southern Asset Management Co., Ltd., Shenzhen, China
Huoqing Tang
School of Finance, Renmin University of China, Beijing, China
Citation:
Chen, Y., Chen, Z. and Tang, H. (2019), "High-order moments in stock pricing: evidence from the Chinese and US markets", China Finance Review International, Vol. 10 No. 3, pp. 323-346. https://doi.org/10.1108/CFRI-06-2019-0070
关键词
Asset pricing model, High-order moment, Joint distribution
摘要
Purpose
The purpose of this paper is to introduce an augmented high-order capital asset pricing model (AH-CAPM) as a new risk-based model to price stocks.
Design/methodology/approach
The AH-CAPM is defined as a linear model with high-order marginal moments and co-moments from the joint distributions of the sorted stock portfolio returns and the market return.
Findings
The performance of the AH-CAPM is tested in the Chinese and US stock markets. Empirical results show that the high-order marginal moments and co-moments from the joint distributions in AH-CAPM contain the risk and return information implied by the Fama–French factors, indicating it as a better risk measurement. Moreover, the AH-CAPM performs better than the Fama–French three-factor model and the Carhart four-factor model in both the Chinese and US stock markets.
Originality/value
Overall, this study introduces a new asset pricing model with better measurements to incorporate risk information in the stock market.
文章结构
Introduction
Data set and portfolio construction
Methodology
3.1 AH-CAPM
3.2 New interpretation for factor model
3.3 Other competing model: downside-risk CAPM
Empirical performance of the AH-CAPM
Comparisons of the AH-CAPM and the factor models
Conclusion
研究成果
Summary statistics of US stock portfolios
Summary statistics of China’s A-share stock portfolios
Performance of CAPM and DR-CAPM in the US and Chinese stock markets
Model comparisons in the US stock market
Model comparisons in China’s stock market
Performance of 3-order AH-CAPM, AH-CAPM and Fama–French three factor model in the US stock market
Performance of 3-order AH-CAPM, AH-CAPM and Fama–French three-factor model in China’s stock market
Model comparisons in the US stock market for sub-periods
Model comparisons in China’s stock market for sub-periods
Risk premium time-series regression
主要结论
Market anomalies are major challenges for current pricing models. This paper introduces a new model, i.e., AH-CAPM, and employs a polynomial to adjust the gauge of risk with higher-order marginal moments and co-moments. The AH-CAPM emphasizes the highorder co-moments of the excess returns of portfolios joint with the market returns. This is a generalized model that contains the classic CAPM and the H-CAPM as special cases. The empirical results show that the AH-CAPM performs well in both the Chinese and US stock markets. It further shows this model’s applicability in both developed and emerging markets. Moreover, the empirical evidence suggests that the AH-CAPM explains the cross-section of stock returns better than the CAPM, H-CAPM, DR-CAPM, the Fama–French three-factor model and the Carhart four-factor model.
One explanation of the poor performance of factor models in the markets outside the US may be the misspecifications and vagueness of the risk measurement. However, high-order marginal moments and co-moments have clearer definitions and include more effective information. The joint distributions in the AH-CAPM reflect co-movement relations of the portfolios and the market, especially the asymmetry relation, which is neglected by traditional measurements. Moreover, the high-order marginal moments and co-moments are not simply econometric measures. The third-order co-moments (co-skewness) in the AHCAPM reflect investor preferences. The fourth-order moments characterize the tail asymmetry in the distribution. The co-skewness and fourth-order co-moments as well as marginal third, fourth-order moments are incorporated into the AH-CAPM to include effective market information about individual stocks as well as their interactions with the entire market. Furthermore, the size, the value and the momentum effects all can be explained by the marginal moments and co-moments in the AH-CAPM. To sum up, this paper shows that the information in the joint distributions explains the cross-sectional variation in expected returns and the factors in the factor models.
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