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.

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.

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.

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.

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.

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.

The linkage between Bitcoin and foreign exchanges in developed and emerging markets

This study investigates the connectedness between Bitcoin and fiat currencies in two groups of countries:the developed G7 and the emerging BRICS.The methodology adopts the regular(R)-vine copula and compares it with two benchmark models:the multivariate t copula and the dynamic conditional correlation(DCC)GARCH model.Moreover,this study examines whether the Bitcoin meltdown of 2013,selloff of 2018,COVID-19 pandemic,2021 crash,and the Russia-Ukraine conflict impact the linkage with conventional currencies.The results indicate that for both currency baskets,R-vine beats the benchmark models.Hence,the dependence is better modeled by providing sufficient information on the shock transmission path.Furthermore,the cross-market linkage slightly increases during the Bitcoin crashes,and reaches significant levels during the 2021 and 2022 crises,which may indicate the end of market isolation of the virtual currency.

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE preference matrix is transformed into the normalized HFE preference matrix.On this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated.Then,the normalized HFEs are transformed into agent satisfactions.Considering the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed.Based on the agent satisfaction matrix,the matching intention matrix of two-sided agents is built.According to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set up.Furthermore,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions.Using the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is obtained.Finally,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

Editorial to special issue“Hidden market linkages between Bitcoin,cryptocurrencies and financial markets:Evidence from high‑frequency data and higher‑order moments”in financial innovation

The cryptomarket has evolved into a complex system of different types of cryptoassets,each playing an important role within the system.With specific features,opportunities,and risks.Studying their apparent and hidden linkages and general connectedness not only inside the system but also the linkages to the outer markets,being it either the traditional financial markets or the macroeconomic and monetary indicators and variables,plays a crucial role in understanding the market,managing risks,and aiming for profitable opportunities.The cryptomarkets are far from being simply Bitcoin or even just the most popular and capitalised cryptocurrencies and tokens which might have been the case just a few years back.

Extreme dependencies and spillovers between gold and stock markets:evidence from MENA countries

This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets in the Middle East and North Africa(MENA)region and(ii)using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios(i.e.,bear,normal,bull).The results provide strong evidence of quantile dependence between gold and stock returns.Positive correlations are found between MENA gold and stock markets when both are bullish.Conversely,when stock returns are bearish,gold markets show negative correlations with MENA stock markets.The risk spillover from gold to stock markets intensified during the global financial and European crises.Given the risk spillover between gold and stock markets,investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets.Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions.Overall,such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.

Evaluation method for assessing the auxiliary service transaction mechanism in regional power markets

Accurate and seamless auxiliary services in the power market can guarantee smooth and continuous power system operation. China’s new round of power system reform has entered a critical period, and reform implementation requires comprehensive improvements in the maturity of the supporting auxiliary service market. This study reviews the development status and evolution path of the European unified power market and the US regional power market, provides experience for the development of China’s regional power market, then identifies the key influencing factors of auxiliary service trading mechanism design in regional power markets. To analyze the rationality of the auxiliary service trading evaluation index, this paper established an evaluation model for assessing regional power markets. Using combined weight optimization, the gray correlation TOPSIS method was applied to comprehensively evaluate auxiliary service trading in the regional power market. Finally, the application of the proposed evaluation method was briefly analyzed to examine four regional power markets in China and evaluate the effectiveness of current market construction in different regions and provide suggestions for future market construction.

Two-Sided Matching Decision Making with Multi-Attribute Probabilistic Hesitant Fuzzy Sets

In previous research on two-sided matching(TSM)decision,agents’preferences were often given in the form of exact values of ordinal numbers and linguistic phrase term sets.Nowdays,the matching agent cannot perform the exact evaluation in the TSM situations due to the great fuzziness of human thought and the complexity of reality.Probability hesitant fuzzy sets,however,have grown in popularity due to their advantages in communicating complex information.Therefore,this paper develops a TSM decision-making approach with multi-attribute probability hesitant fuzzy sets and unknown attribute weight information.The agent attribute weight vector should be obtained by using the maximum deviation method and Hamming distance.The probabilistic hesitancy fuzzy information matrix of each agent is then arranged to determine the comprehensive evaluation of two matching agent sets.The agent satisfaction degree is calculated using the technique for order preference by similarity to ideal solution(TOPSIS).Additionally,the multi-object programming technique is used to establish a TSM method with the objective of maximizing the agent satisfaction of two-sided agents,and the matching schemes are then established by solving the built model.The study concludes by providing a real-world supply-demand scenario to illustrate the effectiveness of the proposed method.The proposed method is more flexible than prior research since it expresses evaluation information using probability hesitating fuzzy sets and can be used in scenarios when attribute weight information is unclear.

Social interactions in periodic urban markets and their contributions to sustainable livelihoods:Evidence from Ghana

Periodic markets are an important aspect of local economies,providing a platform for farmers(producers),wholesalers,retailers,and consumers to interact face-to-face and exchange goods and services.These markets have been increasing in urban areas in Africa,Asia,and South America because of urbanization.The increase of periodic urban markets(PUMs)in urban areas is observed as an index of modernization,reflecting a response to transition process.However,there are limited studies on how social interactions in PUMs contribute to sustainable livelihoods.This study investigated the types of social interactions occurring in PUMs in Ghana,the benefits of social interactions for participants of PUMs,and how social interactions contribute to sustainable livelihoods.This research interviewed 162 participants,comprising 27 farmers(farmers were regarded as producers in this study),61 retailers,47 wholesalers from 9 selected PUMs across Ghana,and 27 officers from government institutions and non-governmental market associations to obtain their opinions.We analyzed the interview data using the NVivo software.The results showed that there are seven kinds of social interactions in PUMs,including(i)producer-wholesaler relationship,(ii)producer-consumer relationship,(iii)wholesaler-retailer relationship,(iv)retailer-consumer relationship,(v)trader-driver relationship,(vi)trader-institution relationship,and(vii)trader-international buyer relationship.We found that these social interactions in PUMs enhance sustainable livelihoods by supporting human,social,financial,natural,and physical assets of traders(traders refer to producers,wholesalers,and retailers in this study).Therefore,we concluded that the development of policies to improve PUMs could strengthen social interactions,enabling the achievement of sustainable livelihoods in developing countries.

Innovations Not Enough—Yet—to Make Headset Market an Actual Reality

In January 2024,after decades of intermittent improvements in virtual reality(VR)and augmented reality(AR)devices failing to help the technology catch on with the public,tech behemoth Apple(Cupertino,CA,USA)launched its marketing of a headset with by far the highest resolution and sharpest contrast of any commercially available device to date[1].Yet sales of the Vision Pro(Fig.1),Apple’s much anticipated first entry in the VR/AR marketplace,have fallen far short of the company’s already low expectations[2].

Impact of Sharing Marketing on Marketing Willingness of Employees in Internet Decoration Industry

With the development of information technology,sharing marketing,as an innovative marketing method,plays an important role in promoting the marketing willingness and enthusiasm of employees in the Internet decoration industry.Based on the data obtained from the ques-tionnaire survey,this paper makes an empirical analysis of the impact of the economic value,social value,perceived ease of use,perceived convenience,enabling conditions and subjective norms of sharing marketing on the marketing willingness of employees in the Internet decoration industry.The results showed that the questionnaire had good internal consistency and construct validity.Through empirical analysis,it can be found that the economic value,social value,perceived ease of use,perceived convenience,enabling conditions and subjective norms of sharing marketing have a significant positive impact on employees'marketing willingness.

Renewable Polymers in Biomedical Applications:From the Bench to the Market

Polymers from renewable resources have been used for a long time in biomedical applications and found an irreplaceable role in some of them.Their uses have been increasing because of their attractive properties,contributing to the improvement of life quality,mainly in drug release systems and in regenerative medicine.Formulations using natural polymer,nano and microscale particles preparation,composites,blends and chemical modification strategies have been used to improve their properties for clinical application.Although many studies have been carried out with these natural polymers,the way to reach the market is long and only very few of them become commercially available.Vegetable cellulose,bacterial cellulose,chitosan,poly(lactic acid)and starch can be found among the most studied polymers for biological applications,some with several derivatives already established in the market,and others with potential for such.In this scenario this work aims to describe the properties and potential of these renewable polymers for biomedical applications,the routes from the bench to the market,and the perspectives for future developments.

Exploring the impacts of major events on the systemic risk of the international energy market

This study examines the systemic risk caused by major events in the international energy market(IEM)and proposes a management strategy to mitigate it. Using the tail-event driven network(TENET)method, this study constructed a tail-risk spillover network(TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets(SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

Activity Data and Emission Factor for Forestry and Other Land Use Change Subsector to Enhance Carbon Market Policy and Action in Malawi

Activity data and emission factors are critical for estimating greenhouse gas emissions and devising effective climate change mitigation strategies. This study developed the activity data and emission factor in the Forestry and Other Land Use Change (FOLU) subsector in Malawi. The results indicate that “forestland to cropland,” and “wetland to cropland,” were the major land use changes from the year 2000 to the year 2022. The forestland steadily declined at a rate of 13,591 ha (0.5%) per annum. Similarly, grassland declined at the rate of 1651 ha (0.5%) per annum. On the other hand, cropland, wetland, and settlements steadily increased at the rate of 8228 ha (0.14%);5257 ha (0.17%);and 1941 ha (8.1%) per annum, respectively. Furthermore, the results indicate that the “grassland to forestland” changes were higher than the “forestland to grassland” changes, suggesting that forest regrowth was occurring. On the emission factor, the results interestingly indicate that there was a significant increase in carbon sequestration in the FOLU subsector from the year 2011 to 2022. Carbon sequestration increased annually by 13.66 ± 0.17 tCO2 e/ha/yr (4.6%), with an uncertainty of 2.44%. Therefore, it can be concluded that there is potential for a Carbon market in Malawi.

Analyzing the Wind-Dominant Electricity Market under Coexistence of Regulated and Deregulated Power Trading

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity market.In this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated systematically.In detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is established.Firstly,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are provided.Next,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.