𝘍𝘢𝘤𝘵𝘰𝘳 𝘮𝘰𝘥𝘦𝘭𝘴 𝘧𝘰𝘳 𝘊𝘩𝘪𝘯𝘦𝘴𝘦 𝘈-𝘴𝘩𝘢𝘳𝘦𝘴
Highlights
• We compare the performance of asset pricing models on the Chinese A-shares market.
• The q-factor model performs best out of the US-originated factor models.
• Asset pricing models tailored to the Chinese A-shares market perform better.
• A purely data-driven method results in a seven-factor model.
• Including transaction costs changes the model ranking.
https://www.sciencedirect.com/science/ar...192300491X
𝘈𝘯𝘰𝘮𝘢𝘭𝘪𝘦𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘊𝘩𝘪𝘯𝘢 𝘈-𝘴𝘩𝘢𝘳𝘦 𝘮𝘢𝘳𝘬𝘦𝘵
Highlights
• We find that value, risk, and trading anomalies are present in the China A-share market.
• Evidence for the size, quality, and past return categories is weaker, with the exception of residual momentum and reversal.
• We investigate residual reversal, return seasonalities, and connected-firm momentum for the A-share market.
• Short-sale impediments, state-owned enterprises, trading costs, and market reforms do not drive anomaly returns.
https://www.sciencedirect.com/science/ar...8X21001141
𝘔𝘰𝘳𝘦 𝘱𝘰𝘸𝘦𝘳𝘧𝘶𝘭 𝘵𝘦𝘴𝘵𝘴 𝘧𝘰𝘳 𝘢𝘯𝘰𝘮𝘢𝘭𝘪𝘦𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘊𝘩𝘪𝘯𝘢 𝘈-𝘴𝘩𝘢𝘳𝘦 𝘮𝘢𝘳𝘬𝘦𝘵
Abstract
Research into asset pricing anomalies in the China A-share market is hampered given the short time series of available returns. Even when average excess returns on candidate factor portfolios are economically sizeable, conventional portfolio sorting methods lack statistical power. We apply an efficient sorting procedure that combines firm characteristics with the covariance matrix. For the China A-share market, we find that the efficient sorting procedure doubles the t-statistics compared to conventional portfolio sorts, leading to nine instead of three significant anomalies over the post-reform period from 2008 to 2020. We find significant size, value, low-risk, and returns-based anomalies. While portfolio characteristics differ between sorting methods, we find that efficient sorting portfolios highly correlate with equally weighted portfolios and capture the same underlying anomaly.
https://papers.ssrn.com/sol3/papers.cfm?...id=4308694
Highlights
• We compare the performance of asset pricing models on the Chinese A-shares market.
• The q-factor model performs best out of the US-originated factor models.
• Asset pricing models tailored to the Chinese A-shares market perform better.
• A purely data-driven method results in a seven-factor model.
• Including transaction costs changes the model ranking.
https://www.sciencedirect.com/science/ar...192300491X
𝘈𝘯𝘰𝘮𝘢𝘭𝘪𝘦𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘊𝘩𝘪𝘯𝘢 𝘈-𝘴𝘩𝘢𝘳𝘦 𝘮𝘢𝘳𝘬𝘦𝘵
Highlights
• We find that value, risk, and trading anomalies are present in the China A-share market.
• Evidence for the size, quality, and past return categories is weaker, with the exception of residual momentum and reversal.
• We investigate residual reversal, return seasonalities, and connected-firm momentum for the A-share market.
• Short-sale impediments, state-owned enterprises, trading costs, and market reforms do not drive anomaly returns.
https://www.sciencedirect.com/science/ar...8X21001141
𝘔𝘰𝘳𝘦 𝘱𝘰𝘸𝘦𝘳𝘧𝘶𝘭 𝘵𝘦𝘴𝘵𝘴 𝘧𝘰𝘳 𝘢𝘯𝘰𝘮𝘢𝘭𝘪𝘦𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘊𝘩𝘪𝘯𝘢 𝘈-𝘴𝘩𝘢𝘳𝘦 𝘮𝘢𝘳𝘬𝘦𝘵
Abstract
Research into asset pricing anomalies in the China A-share market is hampered given the short time series of available returns. Even when average excess returns on candidate factor portfolios are economically sizeable, conventional portfolio sorting methods lack statistical power. We apply an efficient sorting procedure that combines firm characteristics with the covariance matrix. For the China A-share market, we find that the efficient sorting procedure doubles the t-statistics compared to conventional portfolio sorts, leading to nine instead of three significant anomalies over the post-reform period from 2008 to 2020. We find significant size, value, low-risk, and returns-based anomalies. While portfolio characteristics differ between sorting methods, we find that efficient sorting portfolios highly correlate with equally weighted portfolios and capture the same underlying anomaly.
https://papers.ssrn.com/sol3/papers.cfm?...id=4308694
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