Anomalies in Chinese A-Shares

Hsu, Jason C.; Viswanathan, Vivek; Wang, Chenhui; Wool, Phillip

doi:10.2139/ssrn.2955144

Cited by 3 publications

(4 citation statements)

References 132 publications

(73 reference statements)

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“…The size premium, SMB, is positive but not even half as strong, while the profitability, investment, and momentum premiums appear to be completely absent. These findings are consistent with Cheung et al (2015), Guo et al (2017), andHsu et al (2018). The Sharpe ratios for the various factors in China are summarized in Fig.…”

Section: Resultssupporting

confidence: 85%

“…However, due to the very short (1 month) lookback period of these strategies, high implementation costs are an even bigger concern here. 3 Our work is most closely related to Cheung et al (2015) and Hsu et al (2018), who examine the general effectiveness of asset pricing factors in China. Both studies document the existence of a low-volatility anomaly, as in Blitz and van Vliet (2007).…”

Section: Introductionmentioning

confidence: 99%

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The Volatility Effect in China

Blitz¹,

Hanauer

Vliet³

2021

J Asset Manag

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This paper shows that low-risk stocks significantly outperform high-risk stocks in the local China A-share market. The main driver of this low-risk anomaly is volatility, and not beta. A Fama–French style VOL factor is not explained by the Fama–French–Carhart factors, and has the strongest stand-alone performance among all these factors. Our findings are robust across sectors and over time, and consistent with previous empirical evidence for the US and international markets. Moreover, the VOL premium exhibits excellent investability characteristics, as it involves a low turnover and remains strong when applied to only the largest and most liquid stocks. Our results imply that the volatility effect is a highly pervasive phenomenon, and that explanations should be able to account for its presence in highly institutionalized markets, such as the US, but also in the Chinese market where private investors dominate trading.

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Section: Resultssupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

The Volatility Effect in China

Blitz¹,

Hanauer

Vliet³

2021

J Asset Manag

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“…Due to the unique market characteristics, several studies that have been conducted used the earning to price (E/P) ratio as a value measure. Cakici et al (2017), Hsu et al (2018), Zhang et al (2018), and Jianan Liu et al (2019) all documented a significant effect, while Chen et al (2010) and Hu et al (2019) and reported an insignificant presence of value measure.…”

Section: Introductionmentioning

confidence: 92%

The relevance of earning‐to‐price and ROE predictability for explaining Shenzhen stock exchange (SZSE), returns in China: A dynamic panel data approach

Arshad

2021

J Corp Accounting Finance

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The fundamental valuation (FV) perspective has been extended to the Shenzhen Stock Exchange (SZSE) in China by focusing on the role of forecasted earning‐to‐price ratio and return on equity (ROE). Forecasting the variables is being done using a linear dynamic panel data technique. The findings of the two‐step Generalized Method of Moments (GMM) analysis indicate that the forecasted E/P ratio and ROE significantly explain a portion of the variation in the SZSE stock return and remain highly statistically significant after risk proxy variables are included. Additionally, it confirms the existence of size, momentum, liquidity, and dividend yield in the SZSE. This supports the usefulness of an FV perspective based on the unique characteristics of the Chinese equity market in explaining stock returns and their potential utility in forecasting future stock returns.

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“…They acknowledged that it is treated as an order-driven market, strict initial public offering (IPO) process, the dominance of individual investors, invest only in “A” type of stocks, asymmetric information prevails in market and decision regarding the size of market done by the government. Few pieces of research considered earning to price (E/P) ratio as value measure due to unique market features and findings were diverse such as Cakici et al (2017), Hsu et al (2018), Zhang et al (2018), and Jianan Liu et al (2019) documented a significant effect while Hu et al (2019) and Chen et al (2010) reported an insignificant presence of value measure. Zhang et al (2018) and Jianan Liu et al (2019) explored that the E/P ratio as a value measure is a better and comprehensive proxy to represent the Chinese stock market due to the mentioned unique features compared to the world’s other stock markets.…”

Section: Introductionmentioning

confidence: 99%

Forecasted E/P Ratio and ROE: Shanghai Stock Exchange (SSE), China

Arshad

2021

SAGE Open

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This study explores the influence of forecasted earnings to price ratio (E/P) and ROE to explain the part of the variation in the Shanghai Stock Exchange (SSE) returns. The study analyzed the explanatory capacity of fundamental, risk, and combined valuation approaches variables on comparative mode between static and dynamic models with the induction of un-balanced panel data estimation. A linear dynamic panel technique is being undertaken to forecast the variables. The research findings indicate that the forecasted E/P ratio and ROE significantly explain the variation in SSE stock return and remain highly statistically significant after incorporating risk proxy variables. Moreover, the author also confirms the existence of size, momentum, liquidity, and dividend yield in the Shanghai Stock Exchange. The study introduces the fundamental valuation approach to the Chinese market based on its unique features and designs a log-linear model, which comprises forecasted E/P and ROE in addition to current E/P as an estimator for future stock returns. The incorporation of Driscoll and Kraay standard errors (DKSE) and Panel Corrected standard error (PCSE) under static while difference and system GMM under the scope of dynamic panel estimation is considered to be another contribution of the study.

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Anomalies in Chinese A-Shares

Cited by 3 publications

References 132 publications

The Volatility Effect in China

The Volatility Effect in China

The relevance of earning‐to‐price and ROE predictability for explaining Shenzhen stock exchange (SZSE), returns in China: A dynamic panel data approach

Forecasted E/P Ratio and ROE: Shanghai Stock Exchange (SSE), China

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