Can the Baidu Index predict realized volatility in the Chinese stock market?

This paper incorporates the Baidu Index into various heterogeneous autoregressive type time series models and shows that the Baidu Index is a superior predictor of realized volatility in the SSE 50 Index.Furthermore,the predictability of the Baidu Index is found to rise as the forecasting horizon increases.We also find that continuous components enhance predictive power across all horizons,but that increases are only sustained in the short and medium terms,as the long-term impact on volatility is less persistent.Our findings should be expected to influence investors interested in constructing trading strategies based on realized volatility.

Estimation of Dynamic VaR in Chinese Stock Markets Based on Time Scale and Extreme Value Theory

The accuracy and time scale invariance of value-at-risk （VaR） measurement methods for different stock indices and at different confidence levels are tested. Extreme value theory （EVT） is applied to model the extreme tail of standardized residual series of daily/weekly indices losses, and parametric and nonparametric methods are used to estimate parameters of the general Pareto distribution （GPD）, and dynamic VaR for indices of three stock markets in China. The accuracy and time scale invariance of risk measurement methods through back-testing approach are also examined. Results show that not all the indices accept time scale invariance; there are some differences in accuracy between different indices at various confidence levels. The most powerful dynamic VaR estimation methods are EVT-GJR-Hill at 97.5% level for weekly loss to Shanghai stock market, and EVT-GARCH-MLE （Hill） at 99.0% level for weekly loss to Taiwan and Hong Kong stock markets, respectively.

Dynamic relationship between volume and volatility in the Chinese stock market:evidence from the MS-VAR model

Since market uncertainty,or volatility,serves as a crucial gauge for assessing the traits of market fluctuations,the link between stock market volume and price continues to be a focal point of interest in finance.This study examines the dynamic,nonlinear correlations between Chinese stock volatility,trading volume,and return using a hybrid approach that combines the Markov-switching regime with the vector autoregressive model(MS-VAR).The empirical findings are as follows:(1)The Chinese stock market can be divided into three regional systems:steady downward,steady upward,and high volatility.The three states have similar frequencies of occurrence,and their corresponding stable probabilities are not high,indicating that the Chinese stock market is unstable.(2)Asymmetric dynamic relationships exist between market volatility,investment return,and trading volume.For different regimes,while the effect of trading volume on volatility and return appears to be insignificant,the impacts of volatility and return on trading volume are considerably strong.(3)A regime-dependent,contemporaneous correlation between volatility and return is observed,which also reflects the behavior of the Chinese stock market“chasing up and down”.However,a positive contemporaneous correlation always exists between volatility and trading volumes in different regimes,indicating that uncertainty in the Chinese stock market is closely related to information inflow.

China’s Monetary Policy Impacts on Money and Stock Markets

This study investigated the impact of China’s monetary policy on both the money market and stock markets,assuming that non-policy variables would not respond contemporaneously to changes in policy variables.Monetary policy adjustments are swiftly observed in money markets and gradually extend to the stock market.The study examined the effects of monetary policy shocks using three primary instruments:interest rate policy,reserve requirement ratio,and open market operations.Monthly data from 2007 to 2013 were analyzed using vector error correction(VEC)models.The findings suggest a likely presence of long-lasting and stable relationships among monetary policy,the money market,and stock markets.This research holds practical implications for Chinese policymakers,particularly in managing the challenges associated with fluctuation risks linked to high foreign exchange reserves,aiming to achieve autonomy in monetary policy and formulate effective monetary strategies to stimulate economic growth.

DOES INVESTOR SENTIMENT PREDICT STOCK RETURNS? THE EVIDENCE FROM CHINESE STOCK MARKET

This paper examines the proxy variables of investor sentiment in Chinese stock market carefully, and tries to construct an investor sentiment index indirectly. We use cross correlation analysis to examine lead-lag relationship between the proxy variables and HS300 index. The results show that net added accounts （NAA）, SSE share turnover （TURN）, and closed-end fund discount （CEFD） are leading variables to stock market. The average first day return of IPOs （RIPO） and relative degree of active trading in equity market （RDAT） are contemporary variables, while number of IPOs （NIPO） is a lagging variable of stock market. Using the sentiment proxy variables with most possible leading order, and forward selection stepwise regression method, the empirical results on monthly stock returns reveal that three leading proxy variables can be used to form a sentiment index. And the out of sample tests prove that this sentiment index has good predictive power of Chinese stock market, and it is robust.

Determinants and features of voluntary disclosure in the Chinese stock market

This paper offers in-depth analysis of the determinants and features of voluntary disclosure based on information in the annual reports of 1066 Chinese firms listed on the Shanghai and Shenzhen Stock Exchanges. This extensive sample represents about 80% of all public companies in China. Our findings suggest that voluntary disclosure in China is positively related to firm size,leverage, assets-in-place, and return on equity and is negatively related to auditor type and the level of maturity or sophistication of the intermediary and legal environments. We also find some evidence to suggest a quadratic convex association between state ownership and voluntary disclosure. However, our analysis provides no evidence that extensive disclosure benefits public companies in China in the form of a lower cost of equity.

Progress in physical properties of Chinese stock markets

In the past two decades, statistical physics was brought into the field of finance, applying new methods and concepts to financial time series and developing a new interdiscipline ＂econophysics＂. In this review, we introduce several commonly used methods for stock time series in econophysics including distribution functions, correlation functions, detrended fluctuation analysis method, de- trended moving average method, and multifractal analysis. Then based on these methods, we review some statistical properties of Chinese stock markets including scaling behavior, long-term correla- tions, cross-correlations, leverage effects, antileverage effects, and multifractality. Last, based on an agent-based model, we develop a new option pricing model -- financial market model that shows a good agreement with the prices using real Shanghai Index data. This review is helpful for people to understand and research statistical physics of financial markets.

Study of Regime Switching in Chinese Stock Market

This paper applies Markov switching techniques to examine the different conditions of Chinese Stock Market from 1995 to 2004, Three contrasting regimes are identified： a bear market, a bull market and a speculative market, This paper also surveys the time period and probability of each regime, The timing of regime switching reflects the strong policy market feature of Chinese stock market.

The effects of COVID-19 on Chinese stock markets:an EGARCH approach

Coronavirus disease 2019(COVID-19),the disease caused by the novel coronavirus SARS-CoV-2,has greatly affected financial markets,economies and societies worldwide.This study focusses on the Chinese stock markets.Based on Google Trends data during the period from 1 January 2020 to 12 April 2020,and using the exponential generalised autoregressive conditional heteroskedastic(EGARCH)model,this study finds that the higher uncertainty resulting from the COVID-19 pandemic is significantly associated with the drop in China’s composite index,but this impact varies by sectors.Simultaneously,the higher uncertainty due to COVID-19 is significantly associated with greater volatility in stock returns for both the composite index and sector indices.

Understanding the Chinese stock market:international comparison and policy implications

The definitions of the bear,sidewalk and bull markets are ambiguous in the existing literature.This makes it difficult for practitioners to distinguish between different market conditions.In this paper,we propose statistical definitions of the bear,sidewalk and bull markets,which correspond to the three states in our hidden semi-Markov model.We apply this analysis to the daily returns of the Chinese stock market and seven developed markets.Using the Viterbi algorithm to globally decode the most likely sequence of the market conditions,we systematically find the precise timing of the bear,sidewalk and bull markets for all the eight markets.Through the comparison of the estimation and decoding results,many unique characteristics of the Chinese stock market are revealed,such as‘crazy bull’,‘frequent and quick bear’and‘no buffer zone’.In China,the bull market is more volatile than in developed markets,the bear market occurs more frequently than in developed markets,and the sidewalk market has not functioned as a buffer zone since 2005.Possible causes of these unique characteristics are also discussed and implications for policy-making are suggested.

Analysis of Stock Splits Based on Risk Theory: Empirical Evidence from the Chinese Stock Markets

The paper first analyzes price change due to stock splits in Chinese stock markets,which shows stock prices typically go up for stock splits.Then theoretical analyses based on risk theory are presented to explain the reason,where the method comes from a new perspective and obtained theoretical conclusions show that stock splits typically make stock price go up if risk-compensation function is convex,and go down if risk-compensation function is concave.Stock prices typically go up for stock splits because risk-compensation functions are mainly convex.The obtained conclusions are consistent with the known results in the last three decades.

Renewed Financial Frenzy Recovered confidence jumpstarts the Chinese stock markets

After a nine-month suspension on all initial public offerings(IPOs), China State Construction Engineering Corp. Ltd.

Baidu index and predictability of Chinese stock returns

A number of studies have investigated the predictability of Chinese stock returns with economic variables.Given the newly emerged dataset from the Internet,this paper investigates whether the Baidu Index can be employed to predict Chinese stock returns.The empirical results show that 1)the Search Frequency of Baidu Index(SFBI)can predict next day’s price changes;2)the stock prices go up when individual investors pay less attention to the stocks and go down when individual investors pay more attention to the stocks;3)the trading strategy constructed by shorting on the most SFBI and longing on the least SFBI outperforms the corresponding market index returns without consideration of the transaction costs.These results complement the existing literature on the predictability of Chinese stock returns and have potential implications for asset pricing and risk management.

Can the Chinese domestic bond and stock markets facilitate a globalising renminbi?

A global renminbi(RMB)needs to be backed by a large,deep and liquid RMB market with a world-class Chinese government bond(CGB)market as its core.It also needs the support from a bigger and more open domestic stock market.China’s CGB market is the sixth largest local currency sovereign bond market in the world.By transforming the non-tradable,captive central bank liabilities into homogeneous and tradable CGBs through cutting the still high Chinese reserve requirements by 1/3,the size of the CGB market can rise by 40%,boosting market liquidity while trimming distortions to the banking system.Also,policy bank bonds may attract foreign investor demand.Finally,a bigger and more open domestic A-share stock market also helps expand the RMB assets in the international investor portfolio.With both bigger bond and stock markets and their higher foreign ownerships following market opening,the combined sum of Chinese domestic bonds and A-shares held by foreign investors may increase five folds during 2018–2025,lifting the RMB asset position in global investor portfolios,facilitating a potential global RMB,while promoting a deeper and more efficient Chinese domestic capital market.This process of liberalising cross-border portfolio capital flows for non-resident investors may bring both risks and benefits to the Chinese economy.

Empirical Analysis of Seasonality Anomalies in Chinese Stock Market Based on Rolling Sample Tests

The paper uses rolling sample tests to investigate calendar effect in Chinese stock market, the method is very suitable for emerging market. We utilize GARCH （1,1）- GED model to identify the time varying nature of calendar effect. Friday effect existed with low volatility at the early stage, but it seems to disappear since 1997, and positive Tuesday effect began to appear then. There is small firm January effect with high volatility.

Whether profitability and investment factors have additional explanatory power compared with Fama-French three-factor model:Empirical evidence on Chinese A-share stock market

Fama and French propose a five-factor model containing the market factor and factors related to size,book-to-market equity ratio,profitability and investment,which outperforms the Fama-French three-factor model in their paper 2014.This study investigates the performance of Fama-French five-factor model and compare with that of Fama-French three-factor model on Chinese A-share stock market.The empirical results show that Fama-French five-factor model explanatory power has differences among different sets of portfolios.Compared with Fama-French three-factor model,the presence of profitability and investment factors donot seem to capture more variations of expected stock returns than the three-factor model except for six value-weighted portfolios formed on size and operating profitability.

The Role of Japanese Candlestick in DVAR Model

The decomposition-based vector autoregressive model （DVAR） provides a new framework for scrutinizing the efficiency of technical analysis in forecasting stock returns. However, its relation- ships with other technical indicators still remain unknown. This paper investigates the relationships of DVAR model with the Japanese Candlestick indicators using simulations, theoretical explanations and empirical studies. The main finding of this paper is that both lower and upper shadows in Japanese Candlestick Granger contribute to the DVAR model explanation power, and thus, providing useful information for improving the DVAR forecasts. This finding makes sense as it means that the infor- mation contained in the lower and upper shadows should be used when modeling the stock returns with DVAR. Empirical studies performed on China SSEC stock index demonstrate that DVAR model with upper and lower shadows as exogenous variables does have informative and valuable out-of-sample forecasts.

Momentum Effect Differs Across Stock Performances:Chinese Evidence

Prior empirical studies find positive and negative momentum effect across the global nations, but few focus on explaining the mixed results. In order to address this issue, we apply the quantile regression approach to analyze the momentum effect in the context of Chinese stock market in this paper. The evidence suggests that the momentum effect in Chinese stock is not stable across firms with different levels of performance. We find that negative momentum effect in the short and medium horizon （3 months and 9 months） increases with the quantile of stock returns. And the positive momentum effect is observed in the long horizon （12 months）, which also intensifies for the high performing stocks. According to our study, momentum effect needs to be examined on the basis of stock returns. OLS estimation, which gives an exclusive and biased result, provides misguiding intuitions for momentum effect across the global nations. Based on the empirical results of quantile regression, effective risk control strategies can also be inspired by adjusting the proportion of assets with past performances.

Which Chinese Markets to Diversify into？

t This paper investigates the correlation and feedback relationships between the Hong Kong Hang Seng Index （HSI）, the Hang Seng Chinese Enterprise Index （CEI） and the S＆P 500 Index （SP）. We divide the indexes into two separate periods, from the inception of the CEI in 1994 to the stock market crash in 2000, and from 2001 to 2011. Our results show that the feedback relationship between the CEI and the SP is stronger after 2000. As the feedback relationship grows stronger, the diversification benefit reduces for US investors who utilizes the CEI as a tool for diversifying into Chinese markets.