China's main stock market index, the SHANGHAI, fell to 3560 points on August 1, 2025, losing 0.37% from the previous session. Over the past month, the index has climbed 3.04% and is up 22.53% 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 August 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.

Russia's main stock market index, the MOEX, fell to 2729 points on August 1, 2025, losing 0.12% from the previous session. Over the past month, the index has declined 3.07% and is down 5.87% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Russia. Russia Stock Market Index MOEX CFD - values, historical data, forecasts and news - updated on August of 2025.

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.

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.

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.

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.

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

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.

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.

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.

In 2021, China's securities company CITIC Securities managed client monies amounting to around *** 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.

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.

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Automotive Event Data Recorder Market Size 2024-2028

The automotive event data recorder market size is forecast to increase by USD 979.6 million at a CAGR of 4.5% between 2023 and 2028.

The automotive event data recorder (EDR) market is experiencing significant growth due to several key factors. The increasing number of road accidents worldwide is driving the demand for EDRs as they provide valuable data for accident investigation and insurance claims. Additionally, the growing popularity of dashboard cameras for event recording is boosting the market as these devices often come equipped with EDR technology. However, the high investments required to install EDRs and their supporting technologies may limit market growth for some consumers and organizations. Despite this challenge, the long-term benefits of improved safety and accident analysis make EDRs an attractive investment for the automotive industry.

What will be the Size of the Automotive Event Data Recorder Market During the Forecast Period?

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The automotive event data recorder (EDR) market encompasses the production and sale of systems that record and store vital vehicle data during normal operation and in response to specific events, such as crashes or vehicle diagnostic alerts. EDRs, also known as black boxes, are increasingly integrated into various automotive systems, including electronic stability program (ESP) and anti-lock braking system (ABS), to enhance vehicle safety and support accident investigation. General safety regulations mandate EDR installation in diesel trucks and electric vehicles, ensuring personal safety and reducing insurance claims. Automotive OEMs leverage real-time monitoring capabilities to optimize vehicle performance and improve maintenance cost estimation.
EDR data is crucial for accident reconstruction and insurance claim assessment, providing valuable insights into driving behavior and vehicle conditions. Autonomous vehicles are poised to significantly expand the market, as their advanced safety systems rely on EDR data for accident investigation and analysis. EDR reports play a critical role in understanding the circumstances leading to car crashes and accidents, ensuring accountability and promoting continuous safety improvements withIn the automotive industry.

How is this Automotive Event Data Recorder Industry segmented and which is the largest segment?

The automotive event data recorder industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  Passenger cars
  Commercial vehicles


Geography

  North America

    US


  Europe

    Germany


  APAC

    China
    Japan
    South Korea


  South America



  Middle East and Africa

By Application Insights

The passenger cars segment is estimated to witness significant growth during the forecast period.

The automotive event data recorder (EDR) market is witnessing significant growth due to increasing adoption by automotive original equipment manufacturers (OEMs) in major markets, particularly In the US. EDRs, which are integrated into airbag modules, collect vital data before and after vehicle accidents. Collaborations between automotive manufacturers and global EDR market companies ensure the development of customized devices for various vehicle models. This market expansion is driven by the integration of EDRs in passenger cars, which accounted for the largest market share in 2023 and is anticipated to remaIn the leading segment. The growing emphasis on vehicle safety, commission from automotive insurance, and the implementation of usage-based insurance models contribute to the market's growth.

Additionally, advancements in autonomous vehicle technologies, capacity expansions, and mergers are expected to further boost market growth. EDR installation and maintenance costs, real-time monitoring, accident investigation, and accident reconstruction are essential aspects of the market. Vehicle insurance companies utilize EDR data to assess insurance premiums and provide discounts, making this technology increasingly valuable.

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The Passenger cars segment was valued at USD 2600.70 million in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 37% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The Automotive Event Data Recorder (EDR) market

From the Summer of 2007 until the end of 2009 (at least), the world was gripped by a series of economic crises commonly known as the Global Financial Crisis (2007-2008) and the Great Recession (2008-2009). The financial crisis was triggered by the collapse of the U.S. housing market, which caused panic on Wall Street, the center of global finance in New York. Due to the outsized nature of the U.S. economy compared to other countries and particularly the centrality of U.S. finance for the world economy, the crisis spread quickly to other countries, affecting most regions across the globe. By 2009, global GDP growth was in negative territory, with international credit markets frozen, international trade contracting, and tens of millions of workers being made unemployed.

Global similarities, global differences

Since the 1980s, the world economy had entered a period of integration and globalization. This process particularly accelerated after the collapse of the Soviet Union ended the Cold War (1947-1991). This was the period of the 'Washington Consensus', whereby the U.S. and international institutions such as the World Bank and IMF promoted policies of economic liberalization across the globe. This increasing interdependence and openness to the global economy meant that when the crisis hit in 2007, many countries experienced the same issues. This is particularly evident in the synchronization of the recessions in the most advanced economies of the G7. Nevertheless, the aggregate global GDP number masks the important regional differences which occurred during the recession. While the more advanced economies of North America, Western Europe, and Japan were all hit hard, along with countries who are reliant on them for trade or finance, large emerging economies such as India and China bucked this trend. In particular, China's huge fiscal stimulus in 2008-2009 likely did much to prevent the global economy from sliding further into a depression. In 2009, while the United States' GDP sank to -2.6 percent, China's GDP, as reported by national authorities, was almost 10 percent.

The linkages between the US and China, the world’s two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.