In this paper, we examine the January effect in China’s A-share stock market from January 1995 to December 2019 using both the solar and lunar calendars. We find consistent with the existing literature the absence of a traditional January effect in the solar calendar; however, we observe a...

We studied the IPO price and long-term performance in China after the adoption of the book-building pricing mechanism. Using comparable firm value, we separated the IPO initial returns into pre-market deliberate underpricing and aftermarket overpricing. This separation enables us to clearly test...

This paper investigates how institutional investors matter for asset pricing by using daily institutional trading data and a natural experiment, the split–share structure reform in China. This reform required all listed companies to convert their non-tradable shares to tradable shares after...

In this paper we examine the information content of extreme trading activity in the Chinese stock market. We find that zero-investment portfolios that are constructed by buying high-volume and selling low-volume stocks do not generate positive returns (high-volume return premium), which is...

A recent theory of information uncertainty (IU) postulates a negative (positive) relationship between IU and future returns (momentum returns). We extend this theory by showing that its predictions could be conditioned by differences in behavioral biases induced by culture. We find that greater...

Listed Chinese companies can issue A-shares that are held mainly by domestic investors and B-shares that are held mainly by foreign investors. Although these twin shares have identical cash flow rights and are traded in the same location, A-shares are almost always priced higher than B-shares....

This paper investigates the predictability of the firm news tone on stock return in Chinese market. We find that the news tone significantly positively predicts the cross-sectional future return in both short and long horizon. Beyond this, we generally find while the online news could predict...

Exploiting novel data from Guba forum in China, we analyze the return extrapolation in the cross-section comprehensively and relate it to return predictability and market quality. We find that investors extrapolate from past returns to form their beliefs with exponentially decaying weight and...

Based on Jiang, Kelly, and Xiu (JKX, 2021), we propose a new machine learning model to predict future returns using the price images in the Chinese stock market. We show that our model can achieve a more accurate out-of-sample prediction of a stock’s future return than a traditional model. The...

We estimate the relative signal jump variance (RSJV) as the difference between the realized positive half-variance and negative half-variance divided by the realized variance using high-frequency intraday data and investigate its role in the cross-sectional pricing in the Chinese stock market....