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We demonstrate that arbitrage risk, constructed using three measures — noise trader risk, trading cost and information uncertainty — can predict the return of stocks cross-sectionally in China. The findings are broadly consistent even when out-of-sample tests are conducted using the Fama-MacBeth cross-sectional regression approach. We also construct hypothetical portfolios using the information arising from arbitrage risk and find the existence of abnormal returns which is robust to the use of various portfolios constructed by re-sampling the observations through multiple approaches (e.g., by market capitalization and by book-to-market ratio). Lastly, we reconstruct our portfolios by considering the unique nature of the Chinese stock market (e.g., the dominance of individual investors). Our trading strategies again successfully obtain abnormal returns, suggesting that arbitrage risk can be useful to construct effective investment portfolios in China. • In- and out-of-sample tests are conducted on the cross-sectional stock return in China. • Arbitrage risk is decomposed into noise trader risk, trading cost and information uncertainty. • These risk components effectively forecast stock returns. • These risk components can be used to construct portfolios with abnormal returns. [ABSTRACT FROM AUTHOR]

This study points out the complexities inherent to stock assessment distortion and how accounting information is priced. We obtain evidence about how investors, who are considered to have bounded rationality, influence the dynamics of the formation of stock prices. This effect was investigated in a Brazilian scenario, an environment of low informational quality, but one that represents an important route for international investments. The results indicate that stock market values do not tend to reflect the accounting information for hard-to-value stocks. In this case, accounting information is priced gradually over time. There is evidence that under more complex conditions, stock prices tend to mainly reflect accounting information related to good news. The results also showed that the adoption of International Financial Reporting Standards (IFRS) in Brazil increased the relevance of accounting information by reducing the complexity involved in stock assessment. Additionally, greater comovement of stock prices was identified for hard-to-value-stocks. • Investors are susceptible to mistakes and judgment biases for hard-to-value stocks; • The Information Uncertainty Effect (IUE) generates anomalies in stock prices; • IFRS increases the relevance of accounting information, attenuating the IUE; • The good news is associated with an attention effect from the mass of investors; • Greater comovement of stock prices was identified for hard-to-value stocks. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of retail attention on stock price crash risk in the Chinese stock market. Developing a composite measure of retail attention emphasizing its dynamic changes, we find that retail attention exacerbates future crash risk, which is robust to numerous checks that accommodate possibly omitted variables, apply the fixed effects model and instrumental variable approach, and adopt a legal interpretation as an exogenous policy shock. Extended analyses show that the impact of retail attention is more pronounced for firms with high information uncertainty under optimistic aggregate states. Moreover, using a sample of attention-grabbing stocks, we find that retail trades offer a crucial linkage from retail attention to crash risk. Overall, our findings are helpful to understand the nature of retail attention and its consequences on trading behavior as well as stock returns. • We construct a composite measure of retail attention emphasizing its dynamic changes. • Retail attention significantly exacerbates future crash risk. • Firm characteristics and aggregate states affect the relationship. • Retail trades offer a crucial linkage from retail attention to crash risk. [ABSTRACT FROM AUTHOR]