Under contemporary market conditions in China, the stock index has been volatile and highly reflect trends in the coronavirus pandemic, but rare scientific research has been conducted to model the nonlinear relations between the two variables. Added, on the advent that covid-related news in one time period impacts the stock market in another period, time delay can be an equally good predictor of the stock index but rarely investigated. This study utilizes high-frequency data from January 2020 to the first week of July 2022 to model the nonlinear relationship between the stock index, new covid cases and time delay under polynomial regression environment. The empirical results show that time delay and new covid cases, when modelled in a polynomial environment with optimal degree and delay, do present better representation (up to 16-fold) of the nonlinear relationship such predictors have with stock index for China. The representative delay model is used to project for up to 17 weeks for future trends in the stock index. From the findings, the prowess of the time delay polynomial regression is heavily dependent on instability in covid-related time trends and that researchers and decision-makers should consider modeling to cover for the unsteadiness in coronavirus cases.

Common institutional ownership can enhance knowledge spillovers by increasing portfolio firms’ awareness about each other’s innovation. By investigating listed electronic hardware firms in China for 2000-2016, we find that when common ownership by mutual funds is higher between a firm pair, it is more likely that these two firms cite each other’s patents. To confirm causality, we show that even the exogenous increase in firms’ common ownership following their inclusion into the stock index still positively influences the citing likelihood. We also find that such citations are taken place in a timely manner. Additionally, this positive effect is robust when the effects of overlapping board members and common ownership by other types of institutional investors are controlled for. This effect is more pronounced among nonneighboring firms, when non-neighboring firms are close to their common owners, when common owners hold shares longer, and when firms’ executives have lower incentive to communicate (i.e., SOEs). Last, we find that common ownership by mutual funds also enhances knowledge spillovers through third-party patents. This paper deepens the understanding of knowledge spillovers among firms in developing countries.

This study examines the price discovery patterns in the three BRICS countries’ stock index futures markets that were launched after 2000 – China, India, and Russia. We detect two structural breaks in these three futures price series and their underlying spot price series, and use them to form subsamples. Employing a Vector Error Correction Model (VECM) and the Hasbrouck (1995) test, we find the price discovery function of stock index futures markets generally improves over time in China and India, but declines in Russia. A closer examination not only confirms the findings of Yang et al. (2012) and Hou and Li (2013) regarding price discovery in China’s stock index markets, but also reveals the inconsistency of futures’ leading role in the price discovery process. Further, we find some evidence of day-of-the-week effects in earlier part of the sample in China, but not in India or Russia. And our GARCH model results show bidirectional volatility spillover between futures and spot in China and India, but only unidirectional in Russia.

This paper studies the presence of informed trading in Taiwan stock index options (TXO) and analyzes the informational role of foreign institutions in incorporating information into Taiwan stock index futures (TX). We have found that only the option-induced part (OOI) of the total TX order imbalance can predict future TX prices, and the OOI calculated from open-buy TXO, defined by Ni et al. (2008), provides incremental predictability. This finding shows that the price predictability stems from the information flow resulting from option transactions rather than from liquidity pressure. We conclude further that option transactions from foreign institutions provide the most significant predictability, out-of-the-money option transactions in particular. These empirical results show that option transactions conducted by foreign institutions have played the primary role in conveying the information inherent in the TXO market to the TX market, foreign institutions being delta-informed traders. Retail investors, the major players in both the TXO and TX markets, have done almost nothing of significance with regard to TXO information transmission into the TX market, with the exception of some near-the-money and out-of-the-money options.

This paper studies the magnet effect of market-wide circuit breakers and examines its possible forms using high-frequency data from the Chinese stock index futures market. Unlike previous studies that mainly analyzed the price trend and volatility, this paper is the first to consider the intraday price jump behavior in studying the magnet effect. We find that when a market-wide trading halt is imminent, the probability of a price decrease and the level of market volatility remain stable. However, the conditional probability of observing a price jump increases significantly, leading to a higher possibility of triggering market-wide circuit breakers, which is in support of the magnet effect hypothesis. In addition, we find a significant increase in liquidity demand and insignificant change in liquidity supply ahead of a market-wide trading halt, suggesting that the deterioration of market liquidity may play an important role in explaining the magnet effect.

In this paper, using a set of zero yield curve data of China’s government bonds and credit bonds, along with China’s aggregate credit risk measures, and macroeconomic variables from 2006 to 2013, we document a puzzle of counter-credit-risk corporate yield spreads. We interpret this puzzle as a symptom of the immaturity of China’s credit bond market, which reveals a distorted pricing mechanism latent in the fundamental of this market. As by-products of our analysis, we also find interesting results about relations between corporate yield spreads and interest rates as well as risk premia and the stock index, and these results are somewhat attributed to this puzzle.

As the launch of the China’s first stock index futures (SIF) approaches with no exact date for its eventual introduction. The Chinese stock market has increased dramatically due to this expectation recently, especially the futures contracts related stocks have raised significantly which are good examples of this influence. As the stock index futures is a new financial product, Chinese investors cannot help wondering whether the launch of the stock index future will have a positive or negative impact upon the underlying stock market. On the other hand, the new instruments which, will be followed by the introduction of other derivatives, will require broker-dealers to upgrade their systems and invest in new technology. Therefore, it has become pertinent to investigate the opportunities and challenges this eagerly awaited derivative instrument has to offer to fund managers in the booming Chinese economy.

This paper investigates market effects associated with China Security Index 300 (CSI 300) reconstitutions with sample period from April 2005 to Feb 2008. Several findings are listed as followings: Firstly, cumulative abnormal returns for added stocks increase slightly after announcements, while the returns for removed stocks decrease significantly though reverse immediately after index reconstitutions. Considering the whole event period, prices for deletions do not fall dramatically; it’s consistent with asymmetric change of investors’ awareness proposed by H Chen et al (2004). Secondly, both the results of cumulative abnormal returns and volume ratios do not provide evidence to support price pressure hypothesis or index membership hypothesis. We attribute those results to few funds tracking stock indices exactly with the same components and weights as which in the underlying indices in emerging markets, i.e., enhanced index funds are more familiar. Thirdly, the percentage of the additions’ (or deletions’) shares held by funds is not affected obviously by CSI 300 reconstitutions. Finally, we examine index change effects due to IPO that frequently occur in emerging markets, and find that additions witness a full reversal after the first trading day.

In this paper, we pay attention to the relationship between stock index and increments of trading accounts in A, B share market and funds. We show that there exists bilateral relationship between A, B index and their trading accounts increments. However, Granger causality only exists from stock index to increments of funds accounts. Regressions show that the investors’ sentiment will be easily driven by the index in the same direction, which imply momentum strategy in a very short period. In comparison, when using weekly data, only increments of funds accounts Granger cause the stock index. These uncover the differences between fund managers and small investors while investing on stock market. We also analyse the relationship between index volatility and trading accounts volatility.

This paper examines a wide variety of popular volatility models for stock index return, including Random Walk model, Autoregressive model, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, and extensive GARCH model, GARCH-jump model with Normal, and Student-t distribution assumption as well as nonparametric specification test of these models. We fit these models to Dhaka stock return index from November 20, 1999 to October 9, 2004. There has been empirical evidence of volatility clustering, alike to findings in previous studies. Each market contains different GARCH models, which fit well. From the estimation, we find that the volatility of the return and the jump probability were significantly higher after November 27, 2001. The model introducing GARCH jump effect with normal and Student-t distribution assumption can better fit the volatility characteristics. We find that that RW-GARCH-t, RW-AGARCH-t RW-IGARCH-t and RW-GARCH-M-t can pass the nonparametric specification test at 5% significance level. It is suggested that these four models can capture the main characteristics of Dhaka stock return index.