Chinese Financial Industry Research Articles

Research on Chinese Financial Industry Application Scenarios based on ChatGPT

The emergence of the artificial intelligence ChatGPT has brought a huge information impact to the traditional industry, promoting the deep integration of ChatGPT and financial institutions, stimulating its innovation vitality, and comprehensively empowering financial services. This technology is the key to promote the digital intelligence transformation of the financial industry. Based on the systematic study of the integration scenario of ChatGPT and innovative application in the financial industry and related limitations, this paper constructively puts forward suggestions and expectations for the future development of the financial industry under the background of artificial intelligence, to make some innovative exploration for the application of ChatGPT in the financial industry. According to the research, ChatGPT-like artificial intelligence's powerful natural language processing, data sorting, and analysis capabilities have great application value for financial institutions covering customer service, operation, marketing, risk control, investment and budget, etc., but there are also problems such as high cost, low credibility and security, and technical limitations. Finally, this paper puts forward effective empowerment suggestions based on three aspects: government policy, institutions and technology development.

Research on the Performance of the ARIMA Model in the Stock Market

With the rapid development and upgrading transformation of Chinese financial industry and increasing investment quality, the investment enthusiasm of the masses has been improved. The prediction of stock price has an effective reference for investors to determine investment strategies. In this paper, ARIMA model is used to compare the model performance of Shanghai Composite Index, Shenzhen Composite Index and Science and Technology Innovation Board. This model is also fitted to the normal period and the shock period of the stock market respectively. The study found that the Shanghai Composite Index is the most mature market, and the fitting performance of the stock market in the normal period is better than that in the shock period. From the middle of 2015 to the beginning of 2016, the Shanghai Composite Index and Shenzhen Composite Index fluctuated significantly. This study not only helps investors to adopt more reasonable investment strategies, but also has important reference value for market regulators to guide the market effectively, avoid violent fluctuations in the stock market and maintain market stability.

Chinese corporate fraud risk assessment with machine learning

Corporate fraud is becoming a vital concern of Chinese financial industry in recent years. However, manual investigation of certain suspicious companies could result in mass consumption of resources. Aside from financial variables which were widely used in previous research, this paper has included novel features to assess Chinese corporate fraud, such as transfer of shares and Institutional Shareholdings, and these features are proven to be effective. We also present an efficient and accurate framework for corporate fraud detection that could be used as a fraud risk early warning system for financial institutions and regulatory authorities. Five machine learning methods have been implemented in the experiment and are compared using six metrics. Among these methods, XGboost has relatively higher performance overall in comparison to other models. Feature analysis has also been performed to analyze the influences of different groups of features in different models. This result illustrates that the models would achieve the best performance when all features are included, while financial condition has the most important impact among these groups. In addition, since the dataset being used is public, the result is simple for other researchers to reproduce and improve.

Presidential Attack Risk

The prevalence of social media has inspired multiple researchers to investigate the value of information on various platforms. However, most studies focus on integrating individual views (the wisdom of the crowd), and few studies investigate just one person's effect. To close this gap, this article investigates the impact of Trump's tweets on stock markets. Based on intraday stock market data, this study uses an event study to test the immediate reaction of the stock markets in both the Chinese and U.S. markets. Next, with ordinary least squares (OLS) regression, this study testes the effect of tweets' content features on the returns and volatility of the Chinese and U.S. indices. The results show that Trump's tweets impacted the financial market, especially the returns of the U.S. stock market during the COVID-19 pandemic. With additional analyses based on industry indices and time frequencies, the researchers found that Trump's sentiment on Twitter affected the Chinese financial industry during the trade war and impacted the Chinese pharmaceutical industry during the pandemic.

The Role of Risk Forecast and Risk Tolerance in Portfolio Management: A Case Study of the Chinese Financial Sector

Portfolio decisions are affected by the volatility of financial markets and investors’ risk tolerance levels. To better allocate portfolios; we introduce risk tolerance into the portfolio management problem by considering the risk contribution of portfolio components. In this paper, portfolio weights are allocated to two stages. In the first stage, the portfolio risks and the risk contribution of each share are forecasted. In the second stage, we put forward three weighting techniques—“aggressive”, “moderate” and “conservative”, according to three standard levels of risk tolerance. In addition, a new risk measure called “joint extreme risk probability” (JERP), with risk tolerance taken into account, is proposed. A case study of the Chinese financial industry is conducted to verify the performance of our methods. The empirical results demonstrate that weighting techniques constrained by risk tolerance lead to higher gains in a normal market and less loss when a market is risky. Compared with risk-tolerance-adjusted strategies, the relationship between the performance of the traditional conditional value at risk (CVaR) minimization method and the market risk level is less obviously demonstrated. Viewed from the results, JERP functions as an effective signal that helps investors to deal with potential market risks.

Research on the Agglomeration Effect of Financial Industry in Free Trade Zone

Since the 1970s, with the rapid development of economic integration and the rapid flow of financial resources, Chinese economic development of has accelerated, financial institutions have become closer, and financial agglomeration has become increasingly obvious, showing regional attributes. In the process of economic development, the leading position of finance is becoming more and more unshakable, and financial agglomeration has become an important form of modern financial industry organization and development. The free trade zone has served as a key role in breaking through traditions, reforms and innovations in China. Based on the free trade zone, Chinese economy can develop more prosperously. 18 free trade zones established in China headed by Shanghai have made excellent achievements in Chinese economic reform. The establishment of the free trade zone has attracted a large number of financial institutions to settle in with its reform and innovation advantages. The embryonic form of financial industry agglomeration has emerged. With the continuous development of the free trade zone, Chinese financial industry agglomeration effect has also appeared. Based on this, this article studies the agglomeration effect of the financial industry in Chinese free trade zone.

The rise of tech giants in the fund sales industry: an example of how information and digital technology rebuild platform economy

Unlike its American counterpart, the Chinese financial industry has been challenged by tech giants through their digital platforms. As the entrance of the asset management industry, the fund sales industry is at the center of the revolution, with commercial banks and tech giants fighting for its control. Some scholars have discussed the competition, but none of them discussed the competition by comparing their common features as platforms. Moreover, the competition is in a two-sided multihoming market that has long been ignored by scholars but will prevail in the future. With similar coverage rates for both fund managers and investors, how do fintechs use information and digital technology gobbling a big chunk of commercial banks’ profit. This article filled the gap by examining the common features of commercial banks and tech giants as platforms, including membership externality, usage externality, and multihoming behavior. Usage externality is crucial in this competition. It promoted market efficiency by unlocking the scale effect and using big data analysis. However, unlike the competition between other platforms, membership externality has little impact on the competition among commercial banks and tech giants. With prevailing multihoming behaviors to a high degree, newly entered platforms provided almost no additional membership externality.

How state and market logics influence firm strategy from within and outside? Evidence from Chinese financial intermediary firms

We study how state and market logics, which operate both internal and external to the firm, jointly influence firm strategy. In the context of the Chinese financial intermediary industry, we argue that the level of state ownership in a firm has an inverted U-shaped relationship with the firm’s financial portfolio diversification. This is because firms prioritize financial investment options that serve the dominant logic. As a result, their financial portfolios are more diversified when the multiple logics are balanced than when either logic dominates. This relationship is attenuated by the prevalence of market logic in the regional institutional environment and amplified by industry regulation aimed at correcting market failure. We test these arguments using panel data of Chinese trust companies during a period of de-regulation and re-regulation and find empirical support for the moderated curvilinear effect of state ownership. Our findings demonstrate the relevance of the institutional logics to analyzing firms in contemporary China and highlight how institutional logics at multiple levels jointly shape corporate strategy.

The Role of Chinese Financial Industry in Promoting Reform and Opening up and Serving the Real Economy in the New Era

Finance plays an important role in the economic development of the new era. In the historical process of further deepening reform and opening up, the financial industry should upgrade the level of supervision and strengthen the ability of risk prevention so as to realize the strategic goal of serving the real economy. Based on background, it's necessary to analyze the limited openness and protectionist behavior of the financial industry in developed countries, and then review the important achievements of Chinese financial industry in opening up and reform. In the new historical period, China should attach great importance to the work of financial security from the basic national conditions, improve the level of supervision and risk prevention, strengthen abilities of technological innovation, especially gradually expand the two-way reciprocal opening in the financial field, and introduce social capital into the real economy through deepening reform and effective use of financial means, so that finance can return to serving the real economy. The aim is to promote the healthy development of the national economy in the new era, and constantly improve Chinese comprehensive competitiveness in the world economic system.

Model for evaluating the international competitiveness of financial system with fuzzy number intuitionistic fuzzy information

At present, China has been a member of WTO for five years, the protection period has been past. So it is pretty meaningful to discuss how to improve the competitiveness of Chinese financial system both in theories and reality. The premise of improving competitiveness of Chinese financial industry i s to correctly assess the present Chinese financial industry’s competitiveness level. It is under the above background that the author tries to analyze and evaluate the competitiveness level of Chinese financial industry. In this paper, we investigate the multiple attribute decision making problems with fuzzy number intuitionistic fuzzy information. Firstly, we analyze several operations on the fuzzy number intuitionistic fuzzy sets. We develop the induced fuzzy number intuitionistic fuzzy Hamacher correlated geometric (IFNIFHCG) operator. Then, we use the IFNIFHCG operator to solve multiple attribute decision making with the fuzzy number intuitionistic fuzzy information. Finally, an illustrative example for evaluating the international competitiveness of financial system is given to verify the developed approach.

Big data’s role in expanding access to financial services in China

General consumer and business finance companies have had limited success in serving the needs of economically active low-income families and micro-enterprises cost-effectively and sustainably in emerging economies such as China. Recent advances in computing and telecommunications technology are dramatically transforming this landscape by changing the way the financial industry operates. A key mechanism underlying this transformation concerns the use of big data in assessing, evaluating and refining the creditworthiness of potential borrowers and reducing the transaction costs. While China’s internet-only banking industry is currently small and some activities of players in this industry are akin to those in the shadow banking, this industry has potential to cause a major disruption in the Chinese financial market. A main objective of this paper is to examine the role of big data in facilitating the access to financial products for economically active low-income families and micro-enterprises in China. A second objective is to investigate how formal and informal institutions facilitate and constrain the use of big data in the Chinese financial industry and market. The paper also investigates how various inherent characteristics of big data – volume, velocity, variety, variability and complexity – are related to the assessment of the creditworthiness of low-income families and micro-enterprises. Case studies of big data deployment in the Chinese financial industry and market are discussed. The paper also looks at various categories of personal financial and non-financial information that are being used as proxy measures for a potential borrower’s identity, ability to repay and willingness to repay. Various business models involving the sources of data (internal vs. external to the big data organization) and providers of credits (big data organization vs. external partners or clients of the big data organization) are investigated. The analysis of the paper indicates that the main reason why low-income families and micro-enterprises in China and other emerging economies lack access to financial services is not because they lack creditworthiness but merely because banks and financial institutions lack data, information and capabilities to access the creditworthiness of and effectively provide financial services to this financial disadvantaged group.

Chinese Urban Households’ Security Market Participation: Does Investment Knowledge and Having a Long-Term Plan Help?

Investment in the securities markets is vital to households’ wealth accumulation and financial security. Using data from the 2008 Survey of Chinese Consumer Finance and Investor Education, we found that self-assessed investment knowledge and having a long-term financial plan were positively associated with Chinese households’ participation in the securities markets. The findings provide insight into the long-term financial security of Chinese households. Given the growing middle class and the rapid development of the financial markets in China, the Chinese financial planning industry is likely to grow substantially in the coming years.

Data-Oriented Method to Big Data Standard System Creation: A Case of Chinese Financial Industry

Even though Big Data is a hot technology in the ICT industry with a large effect on economy and society, Big Data is a relatively indefinite concept, like a “laundry list”,compared with cloud computing and Internet of things. Fortunately, there is a consensus that Big Data standardization can promote the exchange and scoping of data, guarantee the data completeness and timeliness, ensure the quality of further analysis, eliminate information islands and improve the industry efficiency. However, the existed methods to Big Data standard system are all technology-oriented. This paper proposes an integrated method, called data-oriented method, which combines bottom–up, top–down, method of expertise with investigation together, to build Big Data standard system based on the data essence in the special field. This approach makes the system get rid of pure technique thinking and adapt more to practical condition. Meanwhile, this research also gives a case study on Chinese financial industry in practice. According to that this data-oriented method sets a close and accurate links between special data and standard system, it can be applied on the construction of Big Data standard system in other fields with improving the system model and laying a good foundation for Big Data applications and creations.

Research on Application of Information Technology in Commercial Bank

During the progress of improvement on scientific technology and national economy level. Chinese financial industry is growing strongly and fast. Facing to large data in network technology and various of uncertain risk factors, firstly the development situation of information technology of commercial bank has been introduced, then the problem in information technology of commercial bank has been analysed. Also we have suggested improvement by using value engineering. Finally finally we have made the conclusion.

The impacts of the recent global financial crisis on Chinese financial system

The recent global financial and economic crisis has important impacts on the world economic and financial system. This paper discusses its impacts on Chinese financial system and the challenges faced by Chinese financial industry in the post-crisis era. The direct impacts of crisis on Chinese financial system are relatively smaller than on other countries. The main reasons are the Chinese banking sector reform, the large spin-off of non-performing assets, the injection of capital by the government and the Chinese banking sector remains highly regulated and localised without much room for innovative market pursuit. But China’s financial industry will face major challenges in the post-crisis era. The lessons learned from the financial crisis and the impacts on Chinese financial system development are also mentioned.

The Study on Financial Supervision for Chinese Financial Industry under Mixed Operation

Abstract Financial mixed operation refers to that financial institution can offer all financial services (banking, securities, insurance, and trust) and engage in industrial businesses by holding the share ownership. Because of self interests, risk diversification, the change of competition condition, and clients’ needs of the diversity of financial products and services, commercial banks make it possible for the mixed operation to be the optimal choice of the banking businesses under dynamic conditions in globalized competition, which results in the diversity and integration of banking businesses.