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In this paper, we first proposed a statistical test for the detrended multiple moving average cross-correlation coefficient DMMC (s). The DMMC (s) mainly was used to analyze the correlation between the dependent variable y and other n independent variables x i . We proved that DMMC (s) approximately obeys the chi-square distribution. We studied the statistical properties of the DMMC (s) between normally distributed random sequences and power-law ARFIMA long memory random sequences. Furthermore, we discussed the influence of the cross-correlation among the target variable and independent variables on DMMC (s). Finally, we further study the application of DMMC (s) to China's stock markets and China carbon emission trading markets to investigate multiple cross-correlation. The empirical results show that there is a strong multiple correlation between China's Shanghai, Shenzhen and Hong Kong stock markets, while the correlation between China's carbon markets is not significant. This paper provides new ideas and theoretical support for exploring the correlation between multiple variables, which has implications for investors and policymakers. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak and the implementation of peak and carbon neutral policies have severely impacted oil price volatility and the industrial sector. Exploring the impact mechanisms between oil prices and industries is particularly important for accurate forecasting of crude oil prices. As one of the world's largest commodity consumers, China's crude oil market is more representative and susceptible to external factors than that of developed countries. In this paper, we propose an analytical forecasting framework based on the causal effects between Shanghai crude oil prices and various industries in China to improve the forecasting accuracy of crude oil prices. Information geometric causal inference (IGCI) is applied to detect causal relationships between 31 different industries in China and Shanghai crude oil prices in the three time periods before, during and after COVID-19, and industries with strong causal information effects on crude oil prices in the long run are screened out as additional features. An oil price forecasting model based on Gray Wolf Optimization and Extreme Learning Machine (GWO-ELM) is proposed. Considering the small amount of data for Shanghai crude oil, this paper proposes a cross-learning data approach to solve the problem. Experimental results show that the GWO-ELM model outperforms RF, LSTM, GRU, and migration learning-based Tr-LSTM and Tr-Adaboost models in the task of Shanghai crude oil futures price prediction, and find that industry characteristics with long-term causal effects on oil prices can improve the model prediction accuracy. Our proposed analytical prediction can capture the oil price trend more accurately through the information of the industry and solve the problem of insufficient training data for the model. The application of this framework is expected to provide new methods and ideas for data mining of crude oil and other futures prices. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 shocked financial markets globally, including China's crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China's first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [ABSTRACT FROM AUTHOR]

Providing a scientific basis and method to ensure the smooth functioning of the Chinese crude oil market would be hugely significant to China's future economic development and security. To this end, attempts have been made to both internationalize the Shanghai crude oil market and minimize financial risks. This paper selects three crude oil markets (INE, WTI and Brent) and five Chinese financial markets (the futures, bond, fund, stock and foreign exchange markets) as the research objects. The Diebold and Yilmaz spillover index model and the multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) method are used to study the volatility spillover effect and the asymmetric cross-correlation between crude oil markets and financial markets. When the volatility spillover effect and the asymmetric relationship that exists between the financial markets are examined, the volatility spillover of the oil market to the financial market is found to be significantly higher than that of the financial market to the oil market. In particular, the spillover effect was even more significant from late-2019 to early-2020. Analysis demonstrates an asymmetric cross-correlation between crude oil markets and the abovementioned five Chinese financial markets. In particular, the impact of the Chinese crude oil market on the stock market is greatest, especially with respect to the Brent and WTI crude oil markets. Except for the bond market, when the INE and Brent markets are increasing, the risk exposure to financial markets is more significant. Among financial markets, INE-Bond market asymmetry is stronger than WTI-bond market asymmetry, but weaker than that of the Brent-Bond market when there are large fluctuations. [ABSTRACT FROM AUTHOR]

This paper aims at discussing the applicability of the three-factor model in China's multiple security markets. The monthly returns of Shenzhen Main Board Market, Shanghai Stock Market, GEM Securities Market and Small and Medium Board Securities Market from January 2012 to December 2016 are selected as samples. The following conclusions are drawn: the three-factor model is applicable in Shenzhen Main Board Market, that is, the change of stock return is proportional to market factor, book-to-market ratio factor, and inversely proportional to scale factor. Moreover, in terms of the explanatory power of the change of stock return, the market factor is the highest, the scale factor is the second, and the book-to-market ratio factor is the lowest. But in the other three markets, the two-factors model that excludes the ratio of book market value can explain the change of stock return better. In addition, the explanatory power of market factor is better than scale factor. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate whether the adoption of convergent-International Financial Reporting Standards (IFRS) in China affects the audit fees of initial public offerings (IPO) firms. An empirical regression analysis using panel data for 1,094 nonfinancial IPOs (excluding season equity offers) of A-shares listed on the Shanghai and Shenzhen Stock Exchanges between 2003 and 2012 is adopted. The results reveal that audit fees increase following convergent-IFRS adoption in China and additionally suggest that convergent-IFRS adoption eases the intense price competition that previously existed in China's audit market and thus has important policy implications for regulators. To the best of the authors' knowledge, this study represents the first reported attempt to adopt the IPO setting to examine the effects of convergent-IFRS adoption on audit fees and fills the gap in literature. Using a setting of IPOs enables this paper to further exclude the influence of quasi-rents derived from low-balling after initial audit engagement when testing audit fees. [ABSTRACT FROM AUTHOR]

The medical savings account (MSA) model of health care financing is viewed as a health care cost containment strategy. Yet, health care expenditure in Shanghai has increased sharply since the adoption of the MSA system. This paper looks into the health care reforms in Shanghai, especially since the introduction of the MSA scheme. From the Labor Insurance Scheme and Government Insurance Scheme to the Medical Savings Account scheme, ordinary Shanghai residents have not benefited from the most recent health care reforms. They have found medical care much less affordable. Disparity in access to health care access has become more evident than ever. Meanwhile, health care cost has increased sharply. China has benefited from an emphasis on prevention and primary care, but the government's recent policies give a high priority to catastrophic disease. This is not a cost-effective approach. Shanghai's health care system needs to break socioeconomic class boundaries if it is to construct a harmonious society. Shanghai's decision makers and various stakeholders have the resources and wisdom to face the challenge. [ABSTRACT FROM AUTHOR]

This paper studies the model risk; the risk of selecting a model for estimating the Value-at-Risk (VaR). By considering four GARCH-type volatility processes exponentially weighted moving average (EWMA), generalized autoregressive conditional heteroskedasticity (GARCH), exponential GARCH (EGARCH), and fractionally integrated GARCH (FIGARCH), we evaluate the performance of the estimated VaRs using statistical tests including the Kupiec's likelihood ratio (LR) test, the Christoffersen's LR test, the CHI (Christoffersen, Hahn, and Inoue) specification test, and the CHI nonnested test. The empirical study based on Shanghai Stock Exchange A Share Index indicates that both EGARCH and FIGARCH models perform much better than the other two in VaR computation and that the two CHI tests are more suitable for analyzing model risk. [ABSTRACT FROM AUTHOR]

In 2022, highly restrictive measures were imposed in China to contain the less deadly Omicron variant of SARS-CoV-2 virus or the COVID-19 virus. This study argues that these measures stemmed from a move away from pragmatic authoritarianism and towards totalitarianism since 2013 and that the lockdown of scores of cities such as Shanghai in 2022 carried quintessential features of totalitarianism. Revived totalitarianism in China has helped explain the longest and likely the most comprehensive strict epidemic control among all nations during the COVID-19 pandemic. The politics and the end of zero-COVID policy in China in 2022 are analysed. [ABSTRACT FROM AUTHOR]

In this paper, using a moving window to scan through every stock price time series over a period from 2 January 2001 to 11 March 2011 and mutual information to measure the statistical interdependence between stock prices, we construct a corresponding weighted network for 501 Shanghai stocks in every given window. Next, we extract its maximal spanning tree and understand the structure variation of Shanghai stock market by analyzing the average path length, the influence of the center node and the p-value for every maximal spanning tree. A further analysis of the structure properties of maximal spanning trees over different periods of Shanghai stock market is carried out. All the obtained results indicate that the periods around 8 August 2005, 17 October 2007 and 25 December 2008 are turning points of Shanghai stock market, at turning points, the topology structure of the maximal spanning tree changes obviously: the degree of separation between nodes increases; the structure becomes looser; the influence of the center node gets smaller, and the degree distribution of the maximal spanning tree is no longer a power-law distribution. Lastly, we give an analysis of the variations of the single-step and multi-step survival ratios for all maximal spanning trees and find that two stocks are closely bonded and hard to be broken in a short term, on the contrary, no pair of stocks remains closely bonded for a long time. [ABSTRACT FROM AUTHOR]

In this paper, we propose a framework to estimate the yield curve in the illiquid market. Within this framework, seven different curve-fitting models are compared from four aspects with the trading data of government bonds listed in the Shanghai Stock Exchange (SSE) of China. We find that the exponential spline model is optimal for this market. The characteristics and reasons underlying SSE interest rate fluctuations in the past two years are also analyzed. [ABSTRACT FROM AUTHOR]

In 1949 Shanghai was the leading international financial center (IFC) in Asia. Recently the push of Shanghai to regain its long lost status of a regional IFC has begun to attract widespread interest. This paper first draws upon the IFC literature to highlight the factors that are considered to be important in determining the potential of a city to emerge as an IFC. Shanghai's progress is then measured against these criteria and is also placed in a comparative perspective by measuring against Hong Kong and Singapore. [ABSTRACT FROM AUTHOR]

In this paper, we apply IAAFT to generate surrogate time series of measured multivariate time series. A quantitative method to detect nonlinearity in multivariate time series is proposed using the generalized redundancy and linear redundancy as the significance test statistic. The null hypothesis of a multivariate linear Gaussian random process is tested using the multivariate surrogate data. The validity of this method is demonstrated using two types models (linear and nonlinear) and applied to Shanghai stock market. [ABSTRACT FROM AUTHOR]

In this paper, we test for causal relationship between China's stock markets by using returns and a measure of volatility for the Shanghai Composite index, the Shenzhen Composite Subindex, and the Hong Kong Hang Seng Index. We also show that the stock index series are nonstationary and that cointegrating vectors and error correction models do not exist for the series. Based on these tests, for the return series, we conclude that Shenzhen Granger caused Shanghai before 1994. For the volatility data, we find that there exists a positive feedback relationship between Shanghai and Shenzhen stock markets, and that Hong Kong volatility Granger causes Shanghai volatility, but not vice versa. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]

This paper identifies a wide incidence of poverty in Shanghai using relative measures. It is estimated that 12 percent of the Shanghai population was poor in 1996, a figure which is far greater than that of official estimates. Two sets of objective social indicators are used to indicate the conditions for including a comparative component into the poverty measure. Despite the magnitude of poverty in Shanghai. the financial implications for its eradication amount to only 0.6 percent of the citi's gross domestic product. [ABSTRACT FROM AUTHOR]

Since 2013, China has become the world's largest gold producer and consumer. To gain the corresponding global pricing power in gold, many actions have been taken by China in recent years, including the International Board at Shanghai Gold Exchange, Shanghai-Hong Kong Gold Connect and Shanghai Gold Fix. Our work studies the dependence structure between China's and international gold price and examines whether these moves are changing the dependence structure. We use GARCH-copula models to detect the dynamic dependence and tail dependence. The research period is set to contain the Financial Crisis in 2008, the dramatical plunge of gold price in 2013 and a series of black swan events in 2016. The empirical study shows that some event driven dependence structure breaks are statistically insignificant. And the time-varying Symmetrized Joe-Clayton copula is the best copula to model the dependence structure based on AIC value. Finally, an example of applications of this dependence structure is given by estimating the VaR of an equally weighted portfolio with a simulation-based method. [ABSTRACT FROM AUTHOR]

The Hurst exponent derived by the R/S analysis method of Shanghai stock market's logarithmic return series is about 0.6298. This shows that the Shanghai stock market exhibits fractal features, and a long memory cycle of about one-and-a-half years. With the reconstruction of phase space, the Shanghai Stock attractor dimension converges to 1.335, which means that the Shanghai stock market has chaotic features, and constructing a dynamic system of the Shanghai stock market needs at least two variables. The findings from the principal component analysis support the conclusion of the existence of chaotic features of the Shanghai stock market. The fractal and chaotic features of the Shanghai stock market reveal the nonlinear properties of the Chinese stock market, and the nonlinearity perspective will be more conducive to the formulation of countermeasures for the development of the Chinese stock market. [ABSTRACT FROM AUTHOR]

This study examined the determinants of foreign bank location decisions in Shanghai markets over the period of 1990 to 2009. The growing foreign presence in Shanghai was found to be related to two different policy regimes: Pudong development area foreign enterprise clustering period after China opened Pudong, and "deposit-loan-match principle" implementing period after China joined WTO. The current location pattern was found to be correlated to deposit potential in each district. It is evident that the foreign bank location decisions were influenced by those of domestic banks while the reverse did not hold. These findings provide a valuable platform for theoretical modeling and further analysis. [ABSTRACT FROM AUTHOR]

Due to the quick advancement of science and technology, the services sector which has a high content of knowledge and technology has experienced globally expeditious development in the past decade. Development in general and the growth of Knowledge Intensive Business Services (KIBS) such as Information and Communication Technology services (ICT services) in particular are at the core of the major trends that are restructuring the economic landscape of not only German but also Chinese economies. In Germany, in the new era of service economy, more emphases are put on KIBS instead of the traditional giant clusters of steel manufacturing and auto manufacturing. Especially in Bavaria, high technology clusters are prospering. The ICT services in Bavaria accounts for 40% of all software companies in Germany. A lot of ICT services clusters can be found, including IT Speicher, FIWM, BICC-NET, etc. Similar cases can be found in Shanghai, where a number of government driving as well as market pulling ICT services cluster are also coming into being. Previous empirical evidence shows an asymmetric bipolarity in the location behavior of KIBS. There is a general predominance of low concentration due to equal diffusion of these services in many regions, and a high concentration in some regions located at the top of the spatial hierarchy, particularly capital cities. The current exploratory research, drawing upon cluster theory and network theory, aims at discovering the cluster features both from the perspective of the company executives in the cluster. Using the data collected through interviews and questionnaire surveys from company managers, incorporated with current theoretical framework and, through integration and analysis, important features of the cluster such as network mechanism are calculated both in Bavaria and Shanghai. We check the supply side as well as the demand side of the reasons why clusters are formulated in the first place, and they both have a positive effect on the network mechanism of the cluster. The network mechanism has a positive effect on innovation performance of the ICT service companies. The reasons are also discussed. Suggestions are provided for policy making about the KIBS cluster forming for both regions and the cooperation in these fields, especially in terms of service outsourcing relationship. Valuable implications for deciding the location for a KIBS company on the firm level are also provided. [ABSTRACT FROM AUTHOR]

Rallying its units for an impending spin-off from General Motors, the Delphi Automotive Systems division cleared the Delphi Delco Electronics (Delphi-D) unit to begin planning for entry into China in 1994. Delphi saw China as ideal for leveraging its technological and innovation capabilities as well as the enormous General Motor heritage and reputation from years of experience delivering quality products to the automotive industry. Delphi-D found a perfect partner in Shanghai Changjiang YiBiao Factory (SCY) (name disguised to protect the firms) that held nearly 50% of the Chinese automobile instrument cluster market. SCY was keen on acquiring new technology to meet increasingly sophisticated customer demands in order to retain market lead as well as to tap into the international market. After rounds of negotiation the two firms formed a fifty-fifty joint venture, Shanghai Delco Electronics Ltd. (SDE) in August 1996. However, SDE started experiencing problems almost immediately. The Delphi-D team at SDE assumed their SCY counterparts would willingly integrate proposed technology and the requisite processes at the joint venture. However, the SCY team resisted prescriptions from the Delphi-D team that they sometimes perceived as "haughty". Broiled in culturally-loaded misunderstanding in a market that was becoming complex by the day as the government legislated new regulations and other manufacturers jostled for a piece of the market, SDE's management sought focus by developing a five-year plan that captured the partners' goals in 1998. However, as the end of 2002 approached, SDE's five-year plan remained largely unrealized. This case shows how implementation challenges can affect the realization of joint venture objectives and illustrates specific challenges that can mar even a well-formulated technology intensive international joint venture strategy. [ABSTRACT FROM AUTHOR]