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The purpose of this paper is to examine the relationship between the US and China stock markets between 2000 and 2007. This study attempts to categorize the event on February 27, 2007, i.e. 9 per cent plunge in Shanghai stock market followed by the $1.5 trillion global market shake out, as irrational, i.e. herd mentality.

To test for this relationship, the Morgan Stanley Capital International daily price index data was collected from April 15, 2002 to April 12, 2007. Daily Dow Jones Industrial Average (DJIA), Nikkei 225 (Nikkei), Hang Seng Index, and the Shanghai Stock Exchange Composite Index (SSECI) were collected from finance.yahoo.com from January 1, 2000 until April 3, 2007. The running beta and correlation coefficients, defined as the cumulative coefficients, are used to determine the co‐movement of the SSECI and DJIA.

The strength of the relationship between the US and China stock markets has significantly increased since 2005, maybe attributed to China's policy change in 2005 to move toward a more free market economy. Because of the unique characteristics of China's stock market, it is hard to conclude that the $1.5 trillion global market shake out was ignited by the 9 per cent plunge in the Shanghai stock market on February 27, 2007.

China's economic reform is unique since the country followed no blue print for the economic institutions to model after and policies were adopted through experimentation. Fueled by its fast growing economy (10.4 per cent in 2005 and 10.7 per cent in 2006), using past patterns or trends to predict the future of China's financial market requires further research as its stock market emerges. Research in this area requires more observations as China's stock market grows and becomes more transparent.

Results here suggest that the strength of the relationship between the US and China stock markets has significantly increased since 2005 and that China's 2005 policy moves toward a more free market economy are most likely responsible.

A better understanding of the influence of China's emerging stock market on the global stock market offers significant value to portfolio managers worldwide.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).

The authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.

According to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

The main purpose is to explore the impact of major stock markets on China's market where major markets are represented by former G8 nations (current G7 and Russia).

The article makes use of: stationarity tests (ADF and PP unit root); long-run correlation tests (Johansen integration involving trace and maximum eigenvalue); impact of G8 markets on China (VECM test); influence of G8 markets on volatility in China's market (variance decomposition analysis) and, effect from shocks in G8 markets on China (impulse response function).

Using a period of 2009–2019 that avoids detecting linkages caused by interdependencies created by two major international crises, the article offers four major findings. First, except for Germany and Russia, G8 markets have a significant causal influence on China with UK having the greatest. Second, G8 markets are not the major source of short-run fluctuation in China's market but over time exercise a noteworthy collective impact with UK having the greatest impact. Third, there are occasions for international portfolio diversification with China's market providing greater diversification than G8 nations. Fourth, all markets provide a short-run window of abnormal profit.

The indexes used to represent national markets are assumed to be adequate representations.

Short-term abnormal profits exist. Investing in China, compared to G8 countries, offers greater portfolio diversification possibilities.

Removal of trade and investment barriers cause greater market integration.

By using recent data, this study reveals that G8 stock markets influence China's market.

China's stock market, which serves as an example of emerging markets, is steadily maturing in the context of globalization. In order to analyze the pricing mechanism of China's stock market, this paper builds a six-factor model to address the market features that are structurally efficient but not entirely efficient.

This study updates the Fama–French factor model's construction process to account for the unique features of China's stock market before creating a model that incorporates size, volume, value, profitability, and profit-income factors based on institutional investors' trading behavior and research preferences. The SWS three-tier sector stock index's monthly and quarterly data for the years 2016–2021 are used as samples for this study.

The results imply that China's stock market is structurally efficient and exhibits high levels of rationality in the region dominated by institutional investors. Specifically, big-size and high-volume portfolios that perform well in terms of liquidity can receive trading premiums. Growth-style sectors prevail at present, and investing in sectors with strong profitability and reliable financial reporting data can produce better returns.

The research on China's stock market can be extended to improve the understanding of the development process of similar emerging markets, thereby promoting their improvement. To enhance the development of emerging markets, the regulators should attach great importance to the role of local institutional investors in driving the market to maturity. It is crucial to adopt a structured approach to examine the market pricing mechanism throughout the middle stage of the transition from developing to mature markets.

This study offers a structured viewpoint on asset pricing in growing emerging markets by combining the multi-factor pricing model approach with behavioral finance theories.

This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia).

The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis.

The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the stock return, linkage between China and other markets seems to be remarkable during and after the Global Financial Crisis. Notably, the findings also indicate that the stock markets are more substantially integrated into the crisis.

The results have considerable implications for portfolio managers and institutional investors in the evaluation of investment and asset allocation decisions. The market participants should pay more attention to assess the worth of across linkages among the markets and their volatility transmissions. Additionally, international portfolio managers and hedgers may be better able to understand how the volatility linkage between stock markets interrelated overtime; this situation might provide them benefit in forecasting the behavior of this market by capturing the other market information.

This paper would complement the emerging body of existing literature by examining how China stock market impacts on their neighboring countries including Vietnam, Thailand, Singapore and Malaysia. Furthermore, this is the first investigation capturing return linkage and volatility spill over between China market and the four Southeast Asian markets by using bivariate VAR-GARCH-BEKK model. The authors believe that the results of this research’s empirical analysis would amplify the systematic understanding of spillover activities between China stock market and other stock markets.

The purpose of this paper is to examine the evolution of China's securities market regulation from 1980 to 2007 and the dual role of the government in this process.

When the government is simultaneously the owner and regulator of the securities market, the evolution of securities market regulation follows a path of compulsory institutional change. China's Government authorities have played a dual role in this process by acting both as the securities market regulator and the controlling owner of the stock exchanges. The paper uses the evolution of China's securities market regulation from 1980 to 2007 to illustrate this theoretical framework.

Using the case of China, this paper provides unique evidence of how securities regulation evolves in response to government direction and supervision if the government is both the owner and the regulator of the securities market.

The paper offers insight into issues of securities market regulation in China and other emerging markets.

The purpose of this paper is to construct a frequency-domain framework to study the asymmetric spillover effects of international economic policy uncertainty on China’s stock market industry indexes.

This paper follows the time domain spillover model, asymmetric spillover model and frequency domain spillover model, which not only studies the degree of spillover in time domain but also studies the persistence of spillover effect in frequency domain.

It is found that China’s economic policy uncertainty plays a dominant role in the spillover effect on the stock market, while the global and US economic policy uncertainty is relatively weak. By decomposing realized volatility into quantified asymmetric risks of “good” volatility and “bad” volatility, it is concluded that economic policy uncertainty has a greater impact on stock downside risk than upside risk. For different time periods, the sensitivity of long-term and short-term spillover economic policy impact is different. Among them, asymmetric high-frequency spillover in the stock market is more easily observed, which provides certain reference significance for the stability of the financial market.

The originality aims at extending the traditional research paradigm of “time domain” to the research perspective of “frequency domain.” This study uses the more advanced models to analyze various factors from the static and dynamic levels, with a view to obtain reliable and robust research conclusions.

The purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.

The authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.

The findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.

To the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.

This research examines how macroeconomic variables can precisely predict bull/bear stock markets in China and Taiwan.

This paper adopts a two-state Markov switching model to characterize the bull and bear markets spanning from 1994 to 2019 and then conduct a bear stock market predictability test by running regressions between the filtered probabilities of bear markets and a series of macroeconomic variables in turn at different horizons of 1, 3, 6, 12 and 24 months.

This paper shows that inflation rates, changes in real exchange rates, and foreign currency reserve growth are key predictors of bear markets in China, while term spreads, unemployment rates and foreign reserve growth are major factors that can predict bear markets in Taiwan. Remarkably, industrial production growth does not have predictive power for bear markets, which may suggest emerging markets are driven by fund flows rather than real economic activities. Besides, the impact directions of foreign currency reserve growth are opposite, which may be due to different proportions of the financial accounts in their balance of payments.

In practical respect, this paper provides market participants the usefulness, impact direction and implications of bear market predictors when building their market-timing strategies in China and Taiwan stock markets. The government institutions may also thereby make appropriate policies to prevent huge stock market downturns and serious drawbacks.

It highlights the “fund-driven market hypothesis” and “foreign currency reserve effects” that commonly dominate Taiwan and China stock markets since both are highly affected by international funds.

The purpose of this paper is to examine the daily and overnight volatility spillover effects in common stock prices between China and G5 countries and explain their implications on the basis of empirical results.

The analysis utilizes the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model, the cross‐correlation function approach, and realized volatility for daily and intraday stock price data that cover the period from January 5, 2004 to December 31, 2007.

Principally, the paper concludes the following: strong evidence of short‐run one‐way volatility spillover effects from China to the US, UK, German and French stock markets is observed and the test results indicate that Chinese investors were not rational and China's stock market entered a speculative bubble period after the second half of 2006.

Contrary to widespread belief, the empirical results suggest that a small (China) stock market has significant influence on a large (G5) stock market but not vice versa. This paradox is interpreted as a particular phenomenon existing together with the rapid economic development and severe capital regulation in China.