We construct a stock learning index in China A-share market, which is based on a theoretical model of information and investment choice. The higher the learning index value, the more thoroughly the individual stock is learned. Our study shows that a stock with a high learning index will have a lower expected future return compared to a stock with a low learning index. Additionally, decomposition of predictive power shows that the predictive power of the learning index mainly comes from the persistence of its own predictive power, while the rest cannot be explained by changes in the volume of news (proxy for information flow). Moreover, the learning index can explain many market anomalies in China A-share market.

This study focuses on the relationship between individual stocks’ systemic tail risk and future returns. Analyzing data from China's A-share market, we document an abnormal negative crosssectional relationship between stocks’ systemic tail risk and returns, which cannot be explained by firm-specific characteristics. We show that the joint effect of investor expectation of stock return persistence and investor sentiment contributes to the systemic tail risk anomaly. Investors tend to underestimate the loss persistence of stocks that have suffered large losses in the most recent period and overprice such stocks, leading to a strong negative relationship between stock systemic tail risk and return. In addition, constraints on short selling exacerbate individual stocks’ systemic tail risk and also explain the systemic tail risk anomaly.

We study the role of marriage for women's intergenerational mobility during the Ming-Qing (1368-1911) period. Using status information based on the timing of marriage from family histories in Central China, already in the early 1500s it is the case that daughters from rich families attain higher status over their lifetime than daughters from poorer families. This intergenerational status persistence is partly due to marital sorting because daughters from highstatus families tend to become the wives of sons who themselves come from rich families. Quantitatively, the correlation of 0.6 between the status of biological and in-law families means that marriage accounts for more than one third of total intergenerational status transmission, while not accounting for marriage overestimates mobility by more than 20 percent. Further underscoring the importance of marriage, typically the status of the in-law family plays a larger role for intergenerational status transmission than the child's biological grandparents. Over the period 1500 to 1900, the degree of marital sorting falls, as does intergenerational persistence. Lower investments in the marriage market to find a good match for a daughter go hand in hand with the fall in the returns to son education due to the decline of China's civil service examination.

This paper proposes the two-component realized EGARCH model with dynamic jump intensity (hereafter REGARCH-C-DJI model) to model and forecast stock market volatility. The key feature of our REGARCH-C-DJI model is its ability to exploit the high-frequency information as well as to capture the long memory volatility and jump dynamics. An empirical application to Shanghai Stock Exchange Composite (SSEC) index data shows the presence of high persistence of volatility and dynamic jumps in China’s stock market. More importantly, the REGARCH-C-DJI model dominates the GARCH, EGARCH, REGARCH and REGARCH-C models in terms of out-of-sample forecast performance. Our findings highlight the importance of accommodating the realized volatility, volatility components and jump dynamics in forecasting stock market volatility.

This paper is the first study to systematically discuss the predictive power of crosssectional asset pricing anomalies on aggregate market excess return time series in the Chinese A-share market. The paper summarizes the anomalies and uses linear methods with different shrinkage techniques to extract predictive information from highdimensional long-short anomaly portfolio returns datasets. We find that long-short anomaly portfolio returns show highly significant out-of-sample predictive power of aggregate market excess returns, both statistically and economically. Unlike similar studies on U.S. stocks, the predictive power stems from stronger limits of arbitrage in the short-leg when using bid-ask spread as a proxy but from stronger limits of arbitrage in the long-leg when idiosyncratic volatility or market capitalization is used as proxies.

We uncover a signiffcant relationship between the persistence of marketing and investment skills among U.S. mutual fund companies. Using regulatory filings, we calculate the share of marketing-oriented employees to total employment and reveal alarge heterogeneity in its level and persistence. A framework based on costly signaling and learning helps explain the observed marketing decision. The model features a separating equilibrium in which fund companies’ optimal marketing employment share responds to their past performance differently, conditional on the skill level. We confirm the model prediction that the volatility of the marketing employment share negatively predicts the fund companies’ long-term performance.

We provide an easy method to identify purchases and sales initiated by retail investors using recent, widely available U.S. equity transactions data. Individual stocks with net buying by retail investors outperform stocks with negative imbalances by approximately 10 basis points over the following week. Less than half of the predictive power of marketable retail order imbalances is attributable to order flow persistence; contrarian trading (a proxy for liquidity provision) and public news sentiment explain little of the remaining predictability. There is suggestive (but only suggestive) evidence that retail marketable orders contain firm-level information that is not yet incorporated into prices.

We empirically investigate the relation between anomaly portfolio returns and market return predictability in the Chinese stock market. Using 132 long-leg, short-leg, and long-short anomaly portfolio returns, we employ several shrinkage-based statistical learning methods to capture predictive signals of the anomalies in a high-dimensional setting. We find statistically and economically significant return predictability using long- and short-leg anomaly portfolio returns. Moreover, high arbitrage risk enhances forecasting performance, supporting that the predictability stems from mispricing correction persistence. Unlike the U.S. stock market, we find little evidence that the long-short anomaly portfolios can help predict market return due to the low persistence of asymmetric mispricing correction. We provide simulation evidence to sharpen our understanding of the differences found in the U.S. and Chinese stock markets.

This paper examines whether there is evidence of spillovers of volatility from the Chinese stock market to its neighbours and trading partners, including Australia, Hong Kong, Singapore, Japan and USA. China's increasing integration into the global market may have important consequences for investors in related markets. In order to capture these potential eects, we explore these issues using an Autoregressive Moving Average (ARMA) return equation. A univariate GARCH model is then adopted to test for the persistence of volatility in stock market returns, as represented by stock market indices. Finally, univariate GARCH, multivariate VARMA-GARCH, and multivariate VARMA-AGARCH models are used to test for constant conditional correlations and volatility spillover eects across these markets. Each model is used to calculate the conditional volatility between both the Shenzhen and Shanghai Chinese markets and several other markets around the Pacic Basin Area, including Australia, Hong Kong, Japan, Taiwan and Singapore, during four distinct periods, beginning 27 August 1991 and ending 17 November 2010. The empirical results show some evidence of volatility spillovers across these markets in the pre-GFC periods, but there is little evidence of spillover eects from China to related markets during the GFC. This is presumably because the GFC was initially a US phenomenon, before spreading to developed markets around the globe, so that it was not a Chinese phenomenon.

This paper applies a variety of short‐run and long‐run time series techniques to data on a broad group of Asia‐Pacific stock markets and the United States extending to 2010. Our empirical work confirms the importance of crises in affecting the persistence of equity returns in the Asia‐Pacific region and offers some support for contagion effects. Post‐Asian financial crisis quantile regressions yield substantial evidence of long‐run linkages between the Shanghai market, the US market and many regional exchanges. Cointegration is particularly prevalent at the higher end of the distribution. Our results suggest that the enormous growth of the Shanghai market in the new millennium has been accompanied by a meaningful level of integration with other regional and world markets in spite of ongoing capital controls.