Market Supervision Research Articles

Collaboration and regulation: A dual regulatory game for the sustainable development of green housing

The promotion of green housing can significantly reduce energy consumption and greenhouse gas emissions in the construction industry, thereby contributing to the achievement of the dual-carbon goal. However, the frequent occurrence of greenwashing, loan defaults, green debt, and other risks has created an urgent need for stronger government supervision of the green housing market, improved bank capital supervision mechanisms, and greater collaboration between property developer and residents to promote the sustainable development of green housing, ensuring its sustainability and compliance. This study constructs a four-party evolutionary game model involving the core stakeholders of green housing—government, bank, property developer, and resident—to clarify the long-term stable choices of each stakeholder under the dual regulation mode of government and bank. The effectiveness of dual regulation is further confirmed through simulation and sensitivity analysis. The study results indicate that: (1) Under the collaboration strategy, increased government regulation raises the likelihood that bank will also regulate, facilitating the formation of a dual regulation mode. Property developer is more likely to engage in compliant green housing development under this mode, and residents will choose to buy green housing. (2) Under the regulatory strategy, both incentive subsidies and mandatory penalties are effective. The stronger these measures, the more likely property developer will choose compliant green housing development. Finally, based on the study's conclusions, recommendations are proposed to promote the sustainable development of green housing.

The Impact of the US Subprime Mortgage Crisis

The subprime mortgage crisis has a huge impact on American society, it makes a lot of countries get into financial crisis too. A lot of countries economy goes downturn. It is due to the lack of supervision of the U.S. financial industry, and with the need for rapid economic recovery, led to the financial crisis in the later years, and the U.S. economy fell into negative growth. Subsequently, the U.S. strengthened the supervision of the financial market in order to restore the U.S. economy. The significance of this article is to analyze the economic impact of subprime mortgages on the United States and to study some wrong policies behind the prosperous U.S. economy. The policy which commended by this article are that the national economic development should not focus on the short-term, but on longterm development. Loans should be given to small and medium-sized enterprises to promote the progress of social and economic development.

Research on Financial Regulation and Sustainable Development of Real Estate Markets

The sustainable development of real estate is related to the interests of all parties, and it is of great significance to strengthen the macro-control and supervision of the real estate market to promote the sustainable development of the property market. This paper, taking Hangzhou as an example, points out that changes have occurred in Hangzhou's current macro-control policy system and the latest regulatory policies through literature review and case analysis. These changes are based on land supply, developer credit management, presale fund supervision, and financing credit support for enterprises, etc. These policies have played a positive role in the current sustainable development and transaction of Hangzhou's real estate. However, in the long run, there are still shortcomings in the top-level design of regulatory policies, policy implementation, and regulatory systems. This paper believes that in order to promote the sustainable and healthy development of Hangzhou's real estate market, improvements need to be made in policy optimization, regulatory models, and regulatory systems, so as to better play the unique role and value of policy regulation and better serve the overall economic situation. The research of this paper will also play a positive reference role for the real estate regulatory policies of other cities.

Study on the Problems and Countermeasures of Tourism Market Supervision in Ethnic Areas

Ethnic regions are increasingly capturing the attention of tourists, thanks to their unique cultural heritage and natural resources, thus becoming indispensable growth points in the tourism market. However, the rapid expansion of the tourism sector has imposed heightened demands on regulatory mechanisms. Currently, the tourism market in these regions faces a myriad of challenges, including insufficient oversight, a lack of transparency in information, and varying quality among market participants. These issues not only diminish the visitor experience but also impede the advancement of sustainable tourism development. Consequently, there is an urgent need for a comprehensive and effective regulatory strategy to standardize market order and ensure tourism quality. This study analyzes the current state and challenges of the tourism market in ethnic areas and proposes a series of targeted recommendations, including the enhancement of the regulatory framework, increased enforcement efforts, improved information transparency, and the elevation of participant quality. These strategies aim to foster the robust development of the tourism market, enhance visitor satisfaction, and achieve sustainable growth in the tourism industry of ethnic regions.

Identification of Cervi cornu pantotrichum and its mixed varieties by UHPLC-QTOF-MS and UHPLC-TQS-MS/MS

Sika deer (Cervus nippon Temminck) and red deer (Cervus elaphus Linnaeus) are the two creatural sources of velvet antlers, which are recorded in the Chinese Pharmacopoeia (2020 edition). However, the counterfeits-moose (Alces alces Linnaeus) antlers are selling as genuine products in the market. In order to strengthen antler quality control and market supervision, a UHPLC-QTOF-MS coupled with chemometrics analysis and UHPLC-TQS-MS were developed and applied to distinguish the Velvet Antler of moose from that of sika deer and red deer. Firstly, the QTOF-MS quantized data obtained from samples treated with trypsin were subjected to principal component analysis (PCA) to classify these three kinds of antlers. Then, the potential differential marker peptides were found with orthogonal partial least-squares discriminant analysis (OPLS-DA). Finally, validation of these differential marker peptides was assessed using UHPLC-QTOF-MS, and the results showed that the specific ion pairs (m/z 724.8 → 518.1, m/z 724.8 → 938.3, m/z 732.8 → 526.3, m/z 732.8 → 784.3) were detected in moose deer antler, not in velvet antler of sika deer (Cervus nippon Temminck) and red deer (Cervus elaphus Linnaeus). The methods in the paper and specific ion pairs could be successfully applied to distinguish moose antlers from sika deer antlers and red deer antlers.

Should underwriters be trusted? Reducing agency costs through primary market supervision

We examine the mandated introduction of a supervised auction framework within China's primary bond market. This regulatory intervention resulted in a substantial reduction in debt costs for Chinese Bond issuers, primarily attributed to the alleviation of agency conflicts between underwriters and issuers. Leveraging unique bidder-level data obtained from a lead underwriter, our study provides replicable tools to discern collusive bidding behavior. This sheds light on instances of artificially inflated bond yields, highlighting economically burdensome practices. Our findings can assist regulators, issuers, and investors engaged in unsupervised auction mechanisms. Our insights offer potential enhancements to regulatory frameworks and operational efficiency across various sectors, including securities issuance, construction projects, and procurement.

Analysis of Art Incubation and Related benefit Mechanism: Ex-ploration of Transformation from Traditional Market to Digital Collection

This paper deeply analyzes the incubation and related interest mechanism of the transformation of the art market from the traditional model to the digital one. Firstly, the article summarizes the gradual attention paid by the state to the management of art market, including policy support and legislative guarantee, and points out that the value of art is multidimensional, involving aesthetics, philosophy, politics and finance. The article further discusses the stakeholders in the art market, including artists, middlemen and consumers, as well as their interaction and market operation logic. This paper discusses in detail the transformation of artworks from marketization to financialization, including different operation modes of art investment funds, such as portfolio investment, artist trust investment and art hedge investment. The article also emphasizes the rise of the digital collection market and how it can innovate the incu-bation and trading methods of works of art with the help of blockchain technology and NFT. Finally, the article puts forward some suggestions such as strengthening market supervision, perfecting laws and regulations, promoting the integration of market and finance, and supporting the development of digital collection market, to promote the healthy and sustainable development of the art market.

The government intervention effects on panic buying behavior based on online comment data mining: a case study of COVID-19 in Hubei Province, China

At the end of 2019, the world grappled with an unparalleled public health crisis due to the COVID-19 pandemic, which also precipitated a global economic downturn. Concurrently, material panic buying occurred frequently. To restore benign market order, the government instituted a series of interventions to stabilize the market. This scholarly exploration dives deep into evaluating the tangible impact of these governmental measures in Hubei, China, a region which found itself at the very epicenter of the epidemic in its onset phase. Existing papers often employ structured questionnaires and structural equation methods, with small samples and limited effective information. In contrast, we used a dataset of tens of thousands of entries and employed text analysis to maximize the extraction of valid information. Through a meticulous analysis of public feedback, our findings unveil several pivotal insights: (1) The news measures of materials have the best effect. Their effectiveness, in descending order, is ranked as: material sufficiency > authority effect > market supervision > appeal and guidance; (2) Government measures during the epidemic’s initial phase exhibited a delay. After the lockdown measures, the phenomenon of large-scale buying has been formed, and the relevant material news was released later; (3) A dual approach combining authority influence with material sufficiency yielded the most favorable results. In light of these findings, the paper concludes with tailored recommendations aimed at amplifying the efficacy of government-led public opinion interventions in future crises.

Research on Problems and Solutions of Quantitative Investment in the Chinese Market

Quantitative investment has gradually become increasingly important in the Chinese finance market in recent decades. It improves the efficiency of investment, reduces the risk of investment, enhances the liquidity of some market assets and provides new opportunities to accumulate wealth for investors. As a new investment method, it raises some problems which lead to the turmoil of the market when it keeps developing and gaining traction. This paper will review the current situation of quantitative investment in the Chinese market from its development history and the sizes of funds. This study shows that there are mainly four problems existing in the application of quantitative investment in China. Listed below are problems. The evident government intervention in the market has a negative impact on the fitting effectiveness of quantitative models. Some kinds of assets and commodities face poor liquidity and for them, quantitative investment strategies can hardly be conducted accurately. The accuracy of quantitative analysis can be unreliable for the financial data is sometimes incomplete and unreliable in the Chinese market. The high-frequency trading affects the stability of the whole market because of lack of market supervision. This paper also puts forward relevant countermeasures and suggestions according to these problems. This study has great significance to the healthy development of quantitative investment in the Chinese market.

Study on the Legal Risks of Social Entities' Participation in Non-Emergency Transfers

Non-emergency transfer multi-level protection system is an important livelihood project in China and an important diversified support for a sound Chinese-style modern social security system, as well as an ideal governance tool to effectively solve the problems of non-emergency demand crowding out the emergency capacity, unbalanced transfer resources and differences in the quality of service, imperfect management mechanism and laws and regulations, and low social acceptance. We use structural theory to analyse the main problems in the current practice of China's non-emergency transfer security system, accordingly construct the non-emergency transfer security system, and put forward suggestions to promote the development of the system in a benign cycle. Improve the internal resource allocation mechanism to enhance the efficiency of non-emergency transfer services; focus on the cultivation of the talent team to steadily improve the quality of services; optimise the management system and strengthen the articulation mechanism to boost patients' beliefs in recovery; and strengthen the all-round management of information technology for market supervision to deepen the emotional communication and connection.

Research on Credit Construction of Art Market Based on Collaborative Governance

The art market in China started late, but developed rapidly, showing a good momentum of vigorous development. However, as an emerging market, there are still some credit problems, such as forgery of art series, which seriously hinders the high-quality development of China art market. On the basis of analyzing the credit problem of China art market, this paper puts forward some countermeasures, such as perfecting the credit laws and regulations system of China, establishing the credit mechanism of art market, strengthening the supervision of art market and perfecting the appraisal and evaluation system of art.

Intensified law enforcement and firm innovation: Evidence from China's antitrust consolidation

This paper examines the significant transformation in China's antitrust regulatory framework following the consolidation of its three primary antitrust agencies the Ministry of Commerce (MOFCOM), the National Development and Reform Commission (NDRC), and the State Administration for Industry & Commerce (SAIC) into the State Administration for Market Supervision (SAMR). Utilizing data from publicly listed firms across various industries, we analyze how firms in highly concentrated industries have adapted to this consolidation, by increasing the R&D investment, patent filing, and total factor productivity (TFP). Our mechanism channel indicates that stricter enforcement actions and fines by SAMR have spurred competition and innovation, with effects that are comparably significant across both state-owned enterprises (SOEs) and private firms. The paper contributes to the literature by providing an empirical assessment of the effects of this major restructuring within China's Anti-Monopoly Law (AML) enforcement. Our findings shed light on the broader implications of regulatory consolidations on firm innovation, offering insights into the efficacy of such transformations in antitrust policy.

Low-carbon operation strategy of virtual power plant considering progressive demand response

Adapting virtual power plants (VPPs) to the development of new power systems has gradually become a trend. Meanwhile, the economical and effective use of demand-side resources in VPPs has become a research hotspot in the field of new energy. This paper proposes a low-carbon operation strategy with progressive demand response (DR). A DR model id established by evaluating the scheduling potential of low-carbon and flexible loads and the DR transfer of different users motivated by incentive mechanisms. Because the changing carbon price in carbon trading also affects the response transfer amount, it is beneficial to reduce the operating cost of the energy system by using consumers’ surplus value according to consumer psychology to guide energy users to participate in DR. Finally, wind, light, user load data and VPP internal unit output are optimized in rolling mode over multiple time scales, and the optimal adjustment results of the previous day are taken as the basis. At the same time, the output deviation penalty function is added to further reduce the system cost. The nonlinear model of DR cost is transformed into a mixed integer linear model, which is modeled on MATLAB software and solved by a CPLEX optimization solver. The case analysis shows that the progressive DR strategy may increase the total operating cost of the system, but reduce the cost of the carbon emission. The proposed model and method can not only improve the feasibility and effectiveness of market supervision strategy, but also provides a useful reference for operators and demand-side users in energy systems to choose strategies.

DNA metabarcoding unveils the hidden species composition in fish surimi: Implications for the management of unlabeled and mixed seafood products

Fish surimi products are traditional foods primarily made from fish meat and may contain a complex species composition. In Taiwan, the abundant fishery resources and diverse fish species lead to local catches being widely used as ingredients in fish surimi products. However, due to growing market demand and increasingly scarce resources, some surimi products contain sensitive species, such as sharks, posing potential threats to the ecological environment and biodiversity. In this study, by applying metabarcoding techniques, we analyzed 120 fish surimi product samples from different brands and types throughout the four seasons in Taiwan's market. The main fish species identified included milkfish (Chanos chanos), dolphinfish (Coryphaena hippurus), Pomfret (Taractes rubescens), swordfish (Istiophorus spp.) and cartilaginous. Moreover, at least 37 species of cartilaginous fish, including 26 endangered species, were found. Through comprehensive and accurate species identification of surimi product ingredients, we unveiled the usage of sensitive species in products on the market. This finding is important for the surimi industry's quality control and market supervision. Furthermore, it can promote the sustainable use of Taiwan's fishery resources and protect biodiversity.

UPLC-MS/MS-Based Target Screening of 90 Phosphodiesterase Type 5 Inhibitors in 5 Dietary Supplements.

The aim of individuals consuming health supplements is to attain a robust state through nutritional regulation. However, some unscrupulous manufacturers, motivated by profit, fraudulently incorporate drugs or unauthorized components with therapeutic effects into the product for instant product performance enhancement. The long-term use of these products may inadvertently inflict harm on human health and fail to promote nutritive healthcare. The illegal inclusion of these substances is prevalent in kidney-tonifying and sexuality-enhancing products. Developing effective analytical methods to identify these products and screen for illegal added ingredients can effectively prevent such products from reaching and remaining on the market. A target screening method for the detection and quantification of 90 phosphodiesterase type 5 inhibitors (PDE-5is) in 5 kinds of health products was developed and validated. The type of dietary supplements varied from tablets, capsules, and protein powder to wine and beverages. Sample preparation was completed with a one-step liquid phase extraction. The screening process of 90 PDE-5is was done efficiently within 25 min by ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) using the dynamic multiple reaction monitoring (dMRM) technique. The LODs of 90 PDE-5is were detected at levels ranging from 25 to 85 ng/g or ng/mL. This novel targeting methodology was effective and can be applied to routine market supervision. Among 286 batches of samples, 8 batches were found to be positive. Three kinds of PDE-5is were first detected in healthy products. The screening method demonstrated herein will be a promising and powerful tool for rapid screening of PDE-5is.

Government procurement and zombie firms' productivity: Evidence from China

AbstractThe growing number of zombie firms has severely hampered economic growth in most countries, especially after the COVID‐19 pandemic when zombie firms increased dramatically. Improving the productivity of zombie firms has become a major concern around the world. This paper, using Chinese government procurement contract data and listed firm data, empirically investigates the relationship between government procurement and zombie firms' productivity. The research findings indicate that government procurement can improve zombie firms' productivity and narrow the production efficiency gap with non‐zombie firms. This impact is more pronounced for local and low‐level government clients. Our research further investigates the channels through which government procurement improves zombie firms' productivity. The results demonstrate that government procurement promotes productivity by enhancing technological innovation, improving sales performance, and increasing market supervision. Additionally, this study identifies that government procurement exhibits a spillover effect, which enhances the productivity of non‐zombie firms within the same city. These findings contribute significantly to bridging the existing knowledge gap regarding the impact of government procurement on the productivity of zombie firms. Furthermore, the results offer innovative strategies for policy makers to address the challenges posed by zombie firms.

Identification of chrysanthemum variety via hyperspectral imaging and wavelength selection based on multitask particle swarm optimization

Chrysanthemum, a widely favored flower tea, contains numerous phytochemicals for health benefits. Due to the different geographical origins and processing technics, its variety has a direct influence on the phytochemical content and pharmacological effect. Accordingly, an accurate identification for chrysanthemum varieties is significant for quality detection and market supervision. In this study, the hyperspectral imaging (HSI) combined with chemometrics methods was exploited to identify the chrysanthemum varieties. First, to alleviate the problem of easily trapping into local optimum in traditional spectral variable selection methods, the multi-tasking particle swarm optimization (MTPSO) was developed to select the key wavelengths by dividing hundreds of variables into low-dimensional subtasks. Second, to enrich the feature information, the spatial texture and color features contained in hyperspectral images were extracted and applied to chrysanthemum identification for the first time. Finally, an ensemble learning model, extreme gradient boosting (XGBoost), was constructed to conduct the chrysanthemum variety classification due to its strong generalization ability. Experimental results showed that the proposed MTPSO achieved the identification accuracy of 96.89%, and increased by 1.11–5.91% than classical spectral feature selection methods. Furthermore, after the involvement of spatial image information, the classification accuracy using spatial–spectral features was improved further, and reached 98.39%. Overall, this study highlights that the feature fusion of key wavelengths and spatial information is more effective for chrysanthemum variety identification, and can also provide technical reference for other HSI-related applications.

GME's Short Squeez and Market Regulation

GME Century Forbidding War is an event in which American retail investors force to force hedge funds. Based on the analysis of GME Century Forbidding War, this case analyzes the market supervision issues reflected behind this century war, and then explores the roles that enterprises, governments and individuals should play in the current financial market, thus further improving the financial market. Finally, it summarizes the inspiration of GME century's forced air war.

Rapid and duplex detection of sweetpotato and maize components in starch products using Proofman-LMTIA method

To simultaneously detect sweetpotato and maize components in starch products, this study develops a rapid analysis method based on ladder-shape melting temperature isothermal amplification (LMTIA) coupled with proofreading enzyme-mediated probe cleavage (Proofman). Internal transcription spacer (ITS) gene sequences were targeted to design species-specific primers linked with Proofman probes. The detection of this duplex Proofman-LMTIA method could be completed in 20 min under the optimal temperature of 61 ℃. The specificities of sweetpotato and maize ITS primers were verified with seven other species. The sensitivities of sweetpotato and maize DNA extracts were 10 pg/μL and 1 pg/μL, respectively. The detection limits of sweetpotato and maize DNA samples extracted from artificially adulterated starch powders were both 1 %. To demonstrate the effectiveness of the established duplex Proofman-LMTIA method, a total of 19 commercial sweetpotato noodles and 14 starch products were collected and tested for sweetpotato and maize authentication. Taken together, the LMTIA method is suitable for rapid and accurate detection of sweetpotato and maize components in starch products. The popularization of this method will provide guidelines for ingredients authentication and market supervision of products.

Utilizing excitation-emission matrix fluorescence spectroscopy and convolutional neural networks for dark tea brand and aging period identification

This study utilized excitation-emission matrix (EEM) fluorescence spectroscopy in conjunction with convolutional neural networks (CNNs) to identify the dark tea brands and their aging periods, which were both key factors of market value. The adaptation of EEM data to the CNN model was examined, encompassing the configuration of the data structure and the implementation of data augmentation. Three typical CNN models including AlexNet, GoogLeNet, and ResNet were evaluated. ResNet was selected because it demonstrated the highest classification accuracy on the test set and superior clustering performance in the t-SNE visualization of extracted features. Analysis of feature contribution suggested that the CNN model exhibited enhanced sensitivity towards the boundaries of the fluorescence region. Furthermore, transfer learning was proved to be effective in facilitating adaptation of dark tea recognition models to databases with different sample sizes, which was meaningful for the application of this method in dark tea market supervision. Finally, the multi-task model was developed and achieved a 96.9 % accuracy in brand identification and 87.5 % in aging period determination, suggesting the advantages of multi-task learning in enhancing model generalization and training efficiency.