Regulatory Issues and Countermeasures in International Financial Markets

With the deepening of globalization,the development speed of capital markets is constantly accelerating,presenting a trend of globalization.At the same time,the emergence of multiple forms of trading platforms and diversified financial products further highlights the competitive relationship between security exchanges and other trading platforms.While promoting the transformation of security exchange forms in various countries,it also prompts governments to re-examine the financial regulatory system of securities markets.In this situation,it is very important to research the international financial market and financial regulatory system.This article explores the regulatory issues and countermeasures in the international financial market,intending to promote the stability and healthy development of the international financial market.

Prevalence of Noise-Induced Hearing Loss Related to the Mills in the Markets of the Municipality of Parakou in 2021

Introduction: Noise is the second leading cause of hearing loss in adults after presbycusis. The objective of this work was to study hearing loss induced by the noise of mills in the markets of Parakou. Methods: This was a descriptive and analytical cross-sectional study, conducted from February 3 to June 3, 2021 in the markets of Parakou. It concerned millers and sellers located within a 5 meter radius around the mills and among whom pure-tone audiometry was performed to detect a hearing loss. Subjects with no particular medical health history, under 55 years of age and having been working in these markets since more than 12 months, were included. Results: In this study, 103 subjects were selected, including 43 millers and 61 sellers. Their average age was 29 ± 13 years. The sex ratio was 0.49. The average length of service in the profession was 8 years with the extremes of 3 months and 47 years. They were exposed to noise on average 10 hours per day and 6 days a week. The average duration of weekly noise exposure was 23 h 28 min ± 13 h 32 min with the extremes of 5 h 00 min and 52 h 30 min. The average level of noise exposure was 90 dB with the extremes of 72 and 110 dB. 24 subjects reported symptoms related to noise such as headache, tinnitus, and hearing loss, with respective proportions of 22.33%, 20.39% and 06.80%. The prevalence of noise-related hearing loss was 26.21% (n = 27/103). Subjects with a notch at 4000 Hz and normal Average Hearing Loss (AHL) (20.39%) had a seven-time greater risk of developing noise-induced hearing loss (OR = 6.58;95% CI [2.54 - 18.8], p Conclusion: Hearing loss related to the noise of mills affected both millers and sellers near the mills in markets, hence the importance of regulating mills.

Analysis and construction of evaluation index system of inter-provincial electricity spot markets

Because of the contradiction between the scale of new energy installations and the continuous load growth in the central and eastern regions of China,the balance problems of the electricity market are becoming increasingly prominent,and it is urgent to solve such problems through inter-provincial electricity spot markets.First,the development history and construction status of the inter-provincial electricity spot market are summarized;second,the mechanism design of the inter-provincial electricity spot market is sorted out in terms of the market operation framework,transaction declaration,and clearing methods;subsequently,the evaluation index system of the inter-provincial electricity spot market is constructed,including four themes of electricity mutual aid and support,new energy consumption,economic benefits of market-based allocation,and social benefits of market-based allocation;finally,the operation of the inter-provincial electricity spot market is comprehensively analyzed by the algorithm based on the market operation data of 2022,which proves the feasibility and practicality of the proposed index system.

Fuzzy multi-criteria decision-making method-based operational assessment of Chinese electricity markets

The evaluation of the electricity market is crucial for fostering market construction and development.An accurate assessment of the electricity market reveals developmental trends,identifies operational issues,and contributes to stable and healthy market growth.This study investigated the characteristics of electricity markets in different provinces and synthesized a comprehensive set of evaluation indicators to assess market effectiveness.The evaluation framework,comprising nine indicators organized into two tiers,was constructed based on three aspects:market design,market efficiency,and developmental coordination.Furthermore,a novel fuzzy multi-criteria decision-making evaluation model for electricity market performance was developed based on the Fuzzy-BWM and fuzzy COPRAS methodologies.This model aimed to ensure both accuracy and comprehensiveness in market operation assessment.Subsequently,empirical analyses were conducted on four typical provincial-level electricity markets in China.The results indicate that Guangdong’s electricity market performed best because of its effective balance of stakeholder interests and adherence to contractual integrity principles.Zhejiang and Shandong ranked second and third,respectively,whereas Sichuan exhibited the poorest market performance.Sichuan’s electricity market must be improved in terms of market design,such that market players can obtain a fairly competitive environment.The sensitivity analysis of the constructed indicators verified the effectiveness of the evaluation model proposed in this study.Finally,policy recommendations were proposed to facilitate the sustainable development of China’s electricity markets with the objective of transforming them into efficient and secure markets adaptable to the evolution of novel power systems.

Trading in Fast-ChangingMarkets withMeta-Reinforcement Learning

How to find an effective trading policy is still an open question mainly due to the nonlinear and non-stationary dynamics in a financial market.Deep reinforcement learning,which has recently been used to develop trading strategies by automatically extracting complex features from a large amount of data,is struggling to deal with fastchanging markets due to sample inefficiency.This paper applies the meta-reinforcement learning method to tackle the trading challenges faced by conventional reinforcement learning(RL)approaches in non-stationary markets for the first time.In our work,the history trading data is divided into multiple task data and for each of these data themarket condition is relatively stationary.Then amodel agnosticmeta-learning(MAML)-based tradingmethod involving a meta-learner and a normal learner is proposed.A trading policy is learned by the meta-learner across multiple task data,which is then fine-tuned by the normal learner through a small amount of data from a new market task before trading in it.To improve the adaptability of the MAML-based method,an ordered multiplestep updating mechanism is also proposed to explore the changing dynamic within a task market.The simulation results demonstrate that the proposed MAML-based trading methods can increase the annualized return rate by approximately 180%,200%,and 160%,increase the Sharpe ratio by 180%,90%,and 170%,and decrease the maximum drawdown by 30%,20%,and 40%,compared to the traditional RL approach in three stock index future markets,respectively.

Research on the Dynamic Volatility Relationship between Chinese and U.S. Stock Markets Based on the DCC-GARCH Model under the Background of the COVID-19 Pandemic

This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid the COVID-19 pandemic. Initially, a univariate GARCH model is developed to derive residual sequences, which are then used to estimate the DCC model parameters. The research reveals a significant rise in the interconnection between the Chinese and U.S. stock markets during the pandemic. The S&P 500 index displayed higher sensitivity and greater volatility in response to the pandemic, whereas the CSI 300 index showed superior resilience and stability. Analysis and model estimation suggest that the market’s dependence on historical data has intensified and its sensitivity to recent shocks has heightened. Predictions from the model indicate increased market volatility during the pandemic. While the model is proficient in capturing market trends, there remains potential for enhancing the accuracy of specific volatility predictions. The study proposes recommendations for policymakers and investors, highlighting the importance of improved cooperation in international financial market regulation and investor education.

Identification of Antioxidant Additives in Food Products Sold in Dakar Markets

The use of food additives in industrial production has the advantage of improving sensory properties, technological quality and extending the shelf life of foods. Among the most widely used additives are antioxidants, which prevent oxidation, browning and rancidity reactions in foods. However, the strong presence of these additives on the market is not without risks for human health, and should be controlled to guarantee food safety. Analysis of the risks associated with consumption of foods containing these additives requires, among other things, information on the frequency of use of these additives in various consumer products. The aim of this study is therefore to identify the antioxidants present in industrial food products distributed in Dakar. The methodology adopted consists of a qualitative analysis based on the identification of additives from food labels. Investigations were carried out in 9 stores, 4 superettes and 2 supermarkets located in different districts of Dakar. The results revealed the presence of 12 antioxidant additives, dominated by citric acid (53%) and ascorbic acid (29%). These studies have also highlighted the simultaneous use of several antioxidants in the same food product. Moreover, for some artificial antioxidants identified antioxydant such as BHA and BHT, health risks are associated with their consumption. The results of this study open up prospects for the development of information databases on food additives.

China’s Monetary Policy Impacts on Money and Stock Markets

This study investigated the impact of China’s monetary policy on both the money market and stock markets,assuming that non-policy variables would not respond contemporaneously to changes in policy variables.Monetary policy adjustments are swiftly observed in money markets and gradually extend to the stock market.The study examined the effects of monetary policy shocks using three primary instruments:interest rate policy,reserve requirement ratio,and open market operations.Monthly data from 2007 to 2013 were analyzed using vector error correction(VEC)models.The findings suggest a likely presence of long-lasting and stable relationships among monetary policy,the money market,and stock markets.This research holds practical implications for Chinese policymakers,particularly in managing the challenges associated with fluctuation risks linked to high foreign exchange reserves,aiming to achieve autonomy in monetary policy and formulate effective monetary strategies to stimulate economic growth.

Will high-frequency trading practices transform the financial markets in the Asia Pacific Region?

High-frequency trading(HFT)practices in the global financial markets involve the use of information and communication technologies(ICT),especially the capabilities of high-speed networks,rapid computation,and algorithmic detection of changing information and prices that create opportunities for computers to effect low-latency trades that can be accomplished in milliseconds.HFT practices exist because a variety of new technologies have made them possible,and because financial market infrastructure capabilities have also been changing so rapidly.The U.S.markets,such as the National Association for Securities Dealers Automated Quote(NASDAQ)market and the New York Stock Exchange(NYSE),have maintained relevance and centrality in financial intermediation in financial markets settings that have changed so much in the past 20 years that they are hardly recognizable.In this article,we explore the technological,institutional and market developments in leading financial markets around the world that have embraced HFT trading.From these examples,we will distill a number of common characteristics that seem to be in operation,and then assess the extent to which HFT practices have begun to be observed in Asian regional financial markets,and what will be their likely impacts.We also discuss a number of theoretical and empirical research directions of interest.

Price linkage between Chinese and international nonferrous metals commodity markets based on VAR-DCC-GARCH models

Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.

Multi-Blockchain Based Data Trading Markets With Novel Pricing Mechanisms

In the era of big data,there is an urgent need to establish data trading markets for effectively releasing the tremendous value of the drastically explosive data.Data security and data pricing,however,are still widely regarded as major challenges in this respect,which motivate this research on the novel multi-blockchain based framework for data trading markets and their associated pricing mechanisms.In this context,data recording and trading are conducted separately within two separate blockchains:the data blockchain(DChain) and the value blockchain(VChain).This enables the establishment of two-layer data trading markets to manage initial data trading in the primary market and subsequent data resales in the secondary market.Moreover,pricing mechanisms are then proposed to protect these markets against strategic trading behaviors and balance the payoffs of both suppliers and users.Specifically,in regular data trading on VChain-S2D,two auction models are employed according to the demand scale,for dealing with users’ strategic bidding.The incentive-compatible Vickrey-Clarke-Groves(VCG)model is deployed to the low-demand trading scenario,while the nearly incentive-compatible monopolistic price(MP) model is utilized for the high-demand trading scenario.With temporary data trading on VChain-D2S,a reverse auction mechanism namely two-stage obscure selection(TSOS) is designed to regulate both suppliers’ quoting and users’ valuation strategies.Furthermore,experiments are carried out to demonstrate the strength of this research in enhancing data security and trading efficiency.

Food safety inspection and the adoption of traceability in aquatic wholesale markets: A game-theoretic model and empirical evidence

Supply chain traceability is key to reduce food safety risks,since it allows problems to be traced to their sources. Moreover,it allows regulatory agencies to understand where risk is introduced into the supply chain,and offers a major disincentive for upstream agricultural businesses engaging in economically motivated adulteration. This paper focuses on the aquatic supply chain in China,and seeks to understand the adoption of traceability both through an analytical model,and empirical analysis based on data collected through an extensive (largest ever) field survey of Chinese aquatic wholesale markets. The field survey includes 76 managers and 753 vendors,covering all aquatic wholesale markets in Zhejiang and Hunan provinces. The analytical and empirical results suggest that the adoption of traceability among wholesale market vendors is significantly associated with inspection intensity,their individual history of food safety problems,and their risk awareness. The effect of inspection intensity on traceability adoption is stronger in markets which are privately owned than in markets with state/collective ownership. The analysis offers insights into the current state of traceability in China. More importantly,it suggests several hypothesized factors that might affect the adoption of traceability and could be leveraged by regulatory organizations to improve it.

Ethnobotanical study on medicinal plants from the Dragon Boat Festival herbal markets of Qianxinan, southwestern Guizhou, China

Dragon Boat Festival herbal markets in the Qianxinan Buyi and Miao Autonomous Prefecture of southwestern Guizhou have a long well-conserved history.These markets,which are a feature of Buyi and Miao traditional medicines,contain a rich diversity of medicinal plants and traditional medical knowledge.Today,people in southwestern Guizhou still believe that using herbs during the Dragon Boat Festival prevents and can treat disease.In this study,we identified the fresh herbal plants sold at the herbal markets of Xingren City and Zhenfeng County in Qianxinan Buyi and Miao Autonomous Prefecture and quantified their importance.We identified 141 plant species(belonging to 114 genera and 61 families).The plant family with the most species was Asteraceae(14 species).Informants reported that most medicinal plants are herbaceous,with 95.7%of plants used for decoction and 30.5%used for medicinal baths.Medicinal plants are most commonly used to treat rheumatism,injury,and abdominal diseases.The utilization frequency index and relative importance values indicated that Artemisia argyi and Acorus calamus are the most important plants sold at herbal markets during the Dragon Boat Festival.The price of medicinal materials sold in the market may serve as an indicator of the conservation status of species in the region.These findings indicate that the Dragon Boat Festival herbal markets in the Qianxinan Buyi and Miao Autonomous Prefecture fully embodies the characteristics of indigenous ethnomedicine and culture,and also exhibits the diversity of plant resources.We recommend that rare and endangered plants in this region be domesticated and protected.

Dynamic connectedness between stock markets in the presence of the COVID‑19 pandemic:does economic policy uncertainty matter?

This study investigates the dynamic connectedness between stock indices and the effect of economic policy uncertainty(EPU)in eight countries where COVID-19 was most widespread(China,Italy,France,Germany,Spain,Russia,the US,and the UK)by implementing the time-varying VAR(TVP-VAR)model for daily data over the period spanning from 01/01/2015 to 05/18/2020.Results showed that stock markets were highly connected during the entire period,but the dynamic spillovers reached unprecedented heights during the COVID-19 pandemic in the first quarter of 2020.Moreover,we found that the European stock markets(except Italy)transmitted more spillovers to all other stock markets than they received,primarily during the COVID-19 outbreak.Further analysis using a nonlinear framework showed that the dynamic connectedness was more pronounced for negative than for positive returns.Also,findings showed that the direction of the EPU effect on net connectedness changed during the pandemic onset,indicating that information spillovers from a given market may signal either good or bad news for other markets,depending on the prevailing economic situation.These results have important implications for individual investors,portfolio managers,policymakers,investment banks,and central banks.

Internet big data and capital markets:a literature review

Background:Research in various academic disciplines has undergone tremendous changes in the era of big data.Everyone is talking about big data nowadays,but how exactly is it being applied in research on financial studies?Results:This study summarizes the sources of Internet big data for research related to capital markets and the analytical methods that have been used in the literature.In addition,it presents a review of the research findings based on Internet big data in the field of capital markets and proposes suggestions for future studies in which big data can be applied to examine issues related to capital markets.Conclusion:(1)Internet big data sources related to present capital market research can be categorized into forum-type data,microblog-type data and search class data.(2)As for research about investors’sentiments on the basis of Internet big data,the main methods of sentiment analysis include building an inventory of lexical categories,using dictionaries for analysis of lexical categories,and machine learning.(3)Many studies address whether Internet big data can predict capital markets.However,they reach no consistent conclusions,which could be due to limitations of sample and analysis method used.(4)Data collection technique and analysis methods require further improvements.

International carbon markets under the Paris Agreement:Basic form and development prospects

Article 6 of the Paris Agreement introduces two international carbon markets that receive extensive attention and are expected to play an important role in the post-2020 climate regime.Three key elements of the two international carbon markets,including the scope,the types of tradable units and the governance,are identified,as the basis to clarify their basic forms.Based on the key issues and their different designs identified in negotiations,this study analyzes the contributions and challenges for China to participate in international carbon markets.Considering the inherent needs of climate change mitigation,climate finance,the development of a green"Belt and Road"and the China South-South cooperation in climate change,along with the existing domestic capacities on market mechanisms,this study puts forward the short-,medium-and long-term development prospects of the two international carbon markets.

Volatility spillover effect between financial markets:evidence since the reform of the RMB exchange rate mechanism

The volatility spillover effect between the foreign exchange and stock markets has been a major issue in economic and financial studies.In this paper,GC-MSV model was used to study the spillover effect between the foreign exchange market and the stock market after the reform of the RMB exchange rate mechanism.The empirical results show that there is a negative correlation of dynamic price spillovers between the foreign exchange and stock markets.There are asymmetric volatility spillover effects between these two markets for both RMB stages—continued RMB appreciation or constant RMB shock(a significant reduction in appreciation).However,this has been reduced over time.In conclusion,The RMB exchange rate is a key variable that can affect the internal and external equilibrium of the national economy in an open economic environment,and the stock market is capable of quickly reflecting subtle changes in the real economy.In order to keep the stability of the financial markets and the healthy and rapid development of national economy,some suggestions were proposed.

China-Japan Cooperation in Third-Party Markets: Japan's Strategic Thinking and Its Obstacles

Japan’s decision to cooperate with China in third-party markets along the Belt and Road routes reflects the Abe government’s strategic reorientation and comprehensive reassessment of domestic and external situation. Such cooperation is a brand-new path for the two sides to achieve win-win outcomes as well as steady and sustainable bilateral relations.

An Extension of One-Period Nash Equilibrium Model in Non-Life Insurance Markets

This paper deals with an extension of the one-period model in non-life insurance markets (cf. [1]) by using a transition probability matrix depending on some economic factors. We introduce a multi-period model and in each period the solvency constraints will be updated. Moreover, the model has the inactive state including some uninsured population. Similar results on the existence of premium equilibrium and sensitivity analysis for this model are presented and illustrated by numerical results.

Relationship of Margin Rule and Volatility in Chinese Copper Futures Markets

Different from western markets, the margin rates in Chinese futures markets are raised when contract approaches maturity. This paper concentrates on the effect of this time dependent margin rule on volatility. Open interest, another candidate in the margin rule, is also included in our model to investigate its necessity as one of the factors of the rise of margin rates. With the popular copper contract in Shanghai Futures Exchange （ SHFE）, our test results suggest that margin levels have a significant positive effect on volatility, yet open interest has little to do with volatility. The implication is that the rise of margin rate approaching maturity virtually deteriorates the degree of market risks, and open interest is not a necessary factor for the margin rule. It indicates that the policy tool, represented by margin rates, has significantly greater influence on volatility than the market element, represented by open interest.