China's main stock market index, the SHANGHAI, rose to 3520 points on July 14, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 3.86% and is up 18.35% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

According to a survey conducted by Ipsos on predictions for global issues in 2020, ** percent of Chinese believed it that major stock markets might crash in 2020. The results of the survey showed that Chinese were among the most optimistic regarding the stock market in 2020.

At the end of *************, the Shenzhen Component Index value was *********, an increase of about 1,000 index points from *************. The data clearly shows how the value of the index increased before the stock market crash of 2015 and the following sell-off in the following year. In addition to that, the low year-end index value of 2018 was the result of the worst trading year of the decade on Chinese stock exchanges. Together, stocks on the Shanghai and Shenzhen stock exchanges lost around ** percent in that year.

Emotions are fundamental elements driving humans’ decision-making and information processing. Fear is one of the most common emotions influencing investors’ behaviors in the stock market. Although many studies have been conducted to explore the impacts of fear on investors’ investment performance and trading behaviors, little is known about factors contributing to and alleviating investors’ fear during the market crash (or extremely volatile periods) and their fear regulation after the crisis. Thus, the current data descriptor provides details of a dataset of 1526 Chinese and Vietnamese investors, a potential resource for researchers to fill in the gap. The dataset was designed and structured based on the information-processing perspective of the Mindsponge Theory and existing evidence in life sciences. The Bayesian Mindsponge Framework (BMF) analytics validated the data. Insights generated from the dataset are expected to help researchers expand the existing literature on behavioral finance and the psychology of fear, improve the investment effectiveness among investors, and inform policymakers on strategies to mitigate the negative impacts of market crashes on the stock market.

Chinese listed companies data, encompasses stock price crash risk variables, audit system change records, and other necessary control variables. Date Submitted: 2023-11-18

In 2021, the interest income from margin financing and securities lending business of CITIC Securities amounted to around *** billion yuan, ranking first among China's securities companies. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

This study uses panel data on Chinese A-share listed companies in Shanghai and Shenzhen covering 2014 to 2020 selected through the following screening: first, we exclude listed companies in the finance and insurance sectors; second, we exclude listed companies in ST and *ST (Special Treatment); finally, we exclude samples that lack important data. This approach generates 8,658 valid research sample observations. The data are obtained from several official websites, such as those for CSMAR (China Stock Market & Accounting Research Database), CNRDS (Chinese Research Data Services), and the Shanghai and Shenzhen stock exchanges.In this study, the descriptive and relevance of the final data was tested using Stata software, and baseline regression, threshold regression, and robustness and heterogeneity tests were performed. The final data were tested for descriptiveness and correlation using Stata software, and baseline regression, threshold regression, and robustness and heterogeneity tests were performed.

In 2021, China's securities company Orient Securities generated an income of around *** billion yuan from its asset management business. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

This study examines the market return spillovers from the US market to 10 Asia-Pacific stock markets, accounting for approximately 91 per cent of the region’s GDP from 1991 to 2022. Our findings indicate an increased return spillover from the US stock market to the Asia-Pacific stock market over time, particularly after major global events such as the 1997 Asian and the 2008 global financial crises, the 2015 China stock market crash, and the COVID-19 pandemic. The 2008 global financial crisis had the most substantial impact on these events. In addition, the findings also indicate that US economic policy uncertainty and US geopolitical risk significantly affect spillovers from the US to the Asia-Pacific markets. In contrast, the geopolitical risk of Asia-Pacific countries reduces these spillovers. The study also highlights the significant impact of information and communication technologies (ICT) on these spillovers. Given the increasing integration of global financial markets, the findings of this research are expected to provide valuable policy implications for investors and policymakers.

In 2021, China's securities company CITIC Securities generated over ** billion yuan in its operating income, ranking first among all securities companies in China. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

The growing trend of interdependence between the international stock markets indicated the amalgamation of risk across borders that plays a significant role in portfolio diversification by selecting different assets from the financial markets and is also helpful for making extensive economic policy for the economies. By applying different methodologies, this study undertakes the volatility analysis of the emerging and OECD economies and analyzes the co-movement pattern between them. Moreover, with that motive, using the wavelet approach, we provide strong evidence of the short and long-run risk transfer over different time domains from Malaysia to its trading partners. Our findings show that during the Asian financial crisis (1997–98), Malaysia had short- and long-term relationships with China, Germany, Japan, Singapore, the UK, and Indonesia due to both high and low-frequency domains. Meanwhile, after the Global financial crisis (2008–09), it is being observed that Malaysia has long-term and short-term synchronization with emerging (China, India, Indonesia), OECD (Germany, France, USA, UK, Japan, Singapore) stock markets but Pakistan has the low level of co-movement with Malaysian stock market during the global financial crisis (2008–09). Moreover, it is being seen that Malaysia has short-term at both high and low-frequency co-movement with all the emerging and OECD economies except Japan, Singapore, and Indonesia during the COVID-19 period (2020–21). Japan, Singapore, and Indonesia have long-term synchronization relationships with the Malaysian stock market at high and low frequencies during COVID-19. While in a leading-lagging relationship, Malaysia’s stock market risk has both leading and lagging behavior with its trading partners’ stock market risk in the selected period; this behavior changes based on the different trade and investment flow factors. Moreover, DCC-GARCH findings shows that Malaysian market has both short term and long-term synchronization with trading partners except USA. Conspicuously, the integration pattern seems that the cooperation development between stock markets matters rather than the regional proximity in driving the cointegration. The study findings have significant implications for investors, governments, and policymakers around the globe.

In 2021, China's securities company CITIC Securities managed client monies amounting to around 143 billion yuan, ranking first among all securities companies in China. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

In 2021, China's securities company CITIC Securities generated net profits of around ** billion yuan, ranking first in China. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

In 2021, China's securities company China Merchants Securities generated around ***** million yuan from its investment advisory business, ranking first among all securities companies in China. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

CWT plots comparison of the COVID-19 and the GFC.

In 2021, China's securities company CITIC Securities generated an income of around 764 million yuan from its financial advisory business. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However. Chinese equity market has been gradually picking up since 2019.

This study investigates the dynamic and asymmetric propagation of return spillovers between sectoral commodities and industry stock markets in China. Using a daily dataset from February 2007 to July 2022, we employ a time-varying vector autoregressive (TVP-VAR) model to examine the asymmetric return spillovers and dynamic connectedness across sectors. The results reveal significant time-varying spillovers among these sectors, with the industry stocks acting as the primary transmitter of information to the commodity market. Materials, energy, and industrials stock sectors contribute significantly to these spillovers due to their close ties to commodity production and processing. The study also identifies significant asymmetric spillovers with bad returns dominating, influenced by major economic and political events such as the 2008 global financial crisis, the 2015 Chinese stock market crisis, the COVID-19 pandemic, and the Russia-Ukraine war. Furthermore, our study highlights the unique dynamics within the Chinese market, where net information spillovers from the stock market to commodities drive the financialization process, which differs from the bidirectional commodity financialization observed in other markets. Finally, portfolio analysis reveals that the minimum connectedness portfolio outperforms other approaches and effectively reflects asymmetries. Understanding these dynamics and sectoral heterogeneities has important implications for risk management, policy development, and trading practices.

Between March 4 and March 11, 2020, the S&P 500 index declined by ** percent, descending into a bear market. On March 12, 2020, the S&P 500 plunged *** percent, its steepest one-day fall since 1987. The index began to recover at the start of April and reached a peak in December 2021. As of December 29, 2024, the value of the S&P 500 stood at ******** points. Coronavirus sparks stock market chaos Stock markets plunged in the wake of the COVID-19 pandemic, with investors fearing its spread would destroy economic growth. Buoyed by figures that suggested cases were leveling off in China, investors were initially optimistic about the virus being contained. However, confidence in the market started to subside as the number of cases increased worldwide. Investors were deterred from buying stocks, and this was reflected in the markets – the values of the Dow Jones Industrial Average and the Nasdaq Composite also dived during the height of the crisis. What is a bear market? A bear market occurs when the value of a stock market suffers a prolonged decline of more than 20 percent over a period of at least 2 months. The COVID-19 pandemic caused severe concern and sent stock markets on a steep downward spiral. The S&P 500 achieved a record closing high of ***** on February 19, 2020. However, just over 3 weeks later, the market closed on *****, which represented a decline of around ** percent in only 16 sessions.

Tesla's stock declines amid a market downturn triggered by Moody's US credit downgrade, with challenges in Europe and China impacting growth.