Trading Activity Research Articles

Stakeholder-led proactive risk assessment of medication safety in the pharmaceutical supply chain

Abstract Introduction In 2022/23, 1.08 billion medications were dispensed to patients using NHS England, at a cost of £19.04 billion1 . However, Elliot et al (2019)2 estimate every year there are 237 million medication errors at some point of the medication process, with a high associated cost. Increasingly, media is reporting medication shortages of critical medicines3 that can contribute to errors of omission. Medication errors suggests system, tasks and processes should be explored to understand if they have been poorly designed. This paper is a pre-Brexit study that examines the pharmaceutical supply chain with stakeholders. Aim To explore risk to medication safety in the pharmaceutical supply chain using qualitative interviews of stakeholders across the supply chain and proactive risk assessment method SHERPA (Systematic Human Error Reduction and Prediction Approach). Method 1. Qualitative interviews with process models System process models were developed (by literature, field observations and interviewees) and employed to elicit stakeholder perceptions about risk to medication safety in 31 qualitative interviews. Participants included pharmacists, wholesalers, pharmaceutical industry representatives, regulators and policymakers. Ethical approval was granted by Cambridge LREC to include healthcare professionals and 6 patients. Interviews were audio-recorded, transcribed and thematically analysed using N-Vivo. 2. Focus group for SHERPA Six stakeholders participated in the SHERPA focus group4 , including pharmacists and representatives from pharmaceutical manufacturing and wholesale industries. Interview participants were invited and those that agreed, attended. The SHERPA template was completed by the group. The session was audio-recorded, transcribed and thematically analysed using N-Vivo. Results The system models led to a greater understanding of the current system ‘as-is’ and created an overview of the supply chain. SHERPA is a validated method and provided the rigour to risk assess the supply chain process and identify sources of risk. However, the error mode terminology required adjustment to healthcare. Across all supply routes, the main source of risk was failure to supply medicines that caused errors of omission and the risk of counterfeit medicines. Failure to supply resulted from shortages that take place from trading activities that result in stockpiling or exporting of medicines. A lack of robust regulation and parallel imports increased the risk of counterfeit medicines. Stakeholders highlighted deficiencies in the supply chain and poor performance of stakeholders, as medication safety concerns. In order of frequency, the deficiencies include fragmented supply chain; complacency by stakeholders; poor communication and integration across supply chain; and end-user often regarded as the pharmacist, rather than the patient. Discussion and conclusion From the findings, strategies emerged as possible solutions. These included communication of shortages in each component of supply chain; robust counterfeit strategies; use of technology (automation/digital tools); and re-design tasks and processes in dispensaries and wards. Staff training, education, and revalidation of stakeholders is vital. Key limitations in this study include biases that can occur from recruitment strategy and small sample size. The SHERPA method posed terminology problems. In conclusion, this multi-method approach reveals risk and possible solutions to improve safety and reduce cost in the NHS. It is clear this study needs to be repeated to understand the impact of Brexit and current reconfiguration of NHS.

The impact of corporate digital transformation on stock market activity: evidence from the Chinese listed manufacturing companies

Purpose This research aims to investigate the impact of corporate digital transformation (CDT) on stock market activity. Design/methodology/approach A data set of Chinese listed manufacturing enterprises from 2012–2021 is used as a research sample. Findings This research finds that CDT can promote stock market activity. This study validates two potential mechanisms: increasing financial performance and mitigating information asymmetry. This study further suggests that internal control and analyst coverage can strengthen the impact of CDT on stock market activity. Research limitations/implications The research exhibits certain limitations that should be considered in future research. Because the findings are based on the Chinese context, the applicability and generalizability of the findings to other environments may be limited. This research enriches the literature on the determinants of stock market activity from a technological perspective and incrementally contributes to understanding the impact of CDT on stock markets. After analyzing two opposing perspectives on the economic consequences of CDT, the favorable effect of CDT on stock market activity is proven based on the resource-based view and agency theory. This research extends the literature on the relationship between CDT and investor behavior, demonstrating that investors perceive CDT as beneficial. The results provide evidence that CDT can increase financial performance and improve the information environment, leading to increased investor attention and enhanced trading activity. Practical implications This research has incremental practical implications for enterprises and regulatory authorities to comprehend the economic consequences of CDT in developing countries. First, enterprises should increase their digital investments to improve their performance and decrease information asymmetry. Furthermore, enterprise managers should strengthen information systems to adapt to the process of CDT and train employees on digital skills. Second, regulatory authorities should provide comprehensive digital policies and programs supported by tax incentives, subsidies and digital infrastructure projects (Wang et al., 2023). Originality/value This research strengthens the debate on the market impact of CDT. Unlike prior literature, this study explores the influence of CDT on stock market activity for the first time, enriching the literature on CDT and stock market activity. Furthermore, the outcomes guide regulatory authorities to actively support CDT and expedite the digital upgrading of manufacturing industries to promote stock market activity.

Does CEO social capital affect corporate ESG performance?

This paper empirically examines the relationship between CEO (Chief Executive Officer) social capital and corporate ESG (Environment, Social and Governance) performance. Using a sample of A-share listed companies in Shanghai and Shenzhen from 2010 to 2020, the paper finds a negative correlation between CEO social capital and corporate ESG performance. In addition, we also consider how the firm's market trading activity and CEO duality moderates the impact of CEO social capital on firms' ESG, and both are concluded to be positively moderated. Upon further research, we also find that (1) the positive contribution of CEO's social capital to firms' ESG performance is more significant in state-owned enterprises. (2) The negative facilitating effect of CEO's social capital on corporate ESG performance is more significant in large-scale enterprises. (3) ESG practices lead to the loss of shareholder wealth, resulting in the reduction of corporate value. The results of the study deepen the knowledge of academics and practitioners about the value-creating function of CEO social capital, and provide empirical evidence for listed companies to pay attention to and make use of CEO social capital to enhance their corporate social responsibility commitment.

Is the Taiwan Stock Market (Swarm) Intelligent?

It is well-believed that most trading activities tend to herd. Herding is an important topic in finance. It implies a violation of efficient markets and hence, suggests possibly predictable trading profits. However, it is hard to test such a hypothesis using aggregated data (as in the literature). In this paper, we obtain a proprietary data set that contains detailed trading information, and as a result, for the first time it allows us to validate this hypothesis. The data set contains all trades transacted in 2019 by all the brokers/dealers across all locations in Taiwan of all the equities (stocks, warrants, and ETFs). Given such data, in this paper, we use swarm intelligence to identify such herding behavior. In particular, we use two versions of swarm intelligence—Boids and PSO (particle swarm optimization)—to study the herding behavior. Our results indicate weak swarm among brokers/dealers.

Digitalization and country distance in international trade: An empirical analysis of European countries

This study examines the influence of digitalization to reduce the detrimental impact of country differences on exports and imports. It employs the Euro Commission's Digital Economy and Society Index (DESI) starting in 2015 to measure the European countries' digitalization level and its positive impact on declining international trade suffering from country distances. Digitalization's moderating influence on the connection between country distance and trade activity is evaluated using the System GMM technique. Empirical evidence has proven that digitalization can positively moderate the unfavorable reaction of religion and geographic distance on international trade. Besides, digitalization also helps countries overcome language, administration, and economic gaps to promote export activities. These results offer encouragement to implement digitalization in countries to stimulate international trade.

Gender difference in equity portfolio diversification

This study provides compelling evidence that individual investors consistently maintain under-diversified portfolios, with female investors exhibiting significantly lower levels of diversification than their male counterparts. Analyzing a comprehensive dataset of retail investor trades, this study provides the first detailed examination of gender differences in trading activity, performance, and portfolio diversification. Performance, and diversification are systematically related to investor characteristics such as portfolio size, income, education, language, age, and investment experience. The result that increasing diversification improves performance for all investors corresponds with the fact that female investors are found to diversify less at the same time as they show a slightly lower aggregated performance than male investors.

An ETF-based measure of stock price fragility

Equity mutual fund flows are commonly employed to measure stock price fragility - a stock’s exposure to non-fundamental demand risk. However, this approach may be biased by confounding fundamental information, potentially underestimating risk exposure. We propose an alternative method that uses the primary market data of exchange-traded funds (ETFs). This approach overcomes many limitations of mutual fund data, incorporates the influence of a broader set of investor demand, and strongly predicts stock return volatility and return comovement. Our study highlights the significant role that the arbitrage trading activity of ETFs play in signaling non-fundamental demand shocks.

Systematics Literature Review: Exploration of Ethnomathematics in Community Activities in Buying and Selling and Distribution of Goods

Ethnomathematics examines the relationship between mathematics and culture groups in community activities, it is an approach that can reveal important and unique phenomena about how various cultures implement mathematical principles. This study aims to identify, review, evaluate, and interpret according to the established keywords by analyzing articles within the period of 2020- 2024 related to cultures that use mathematical concepts in community activities, particularly in distribution and trade. Through Systematic Literature Review (SLR), there are 17 article data in the form of journal articles, proceedings, theses, and dissertations which were obtained from the Semantic Scholar and Google Scholar databases. The result of this research is the presence of a different ethnomathematics approach in community activities, particularly in distribution and trade activities based on their culture.

A 3D index for measuring economic resilience with application to modern financial crises

AbstractThis paper proposes a vector index R composed of monotonous functions capturing three theoretical aspects (3D) of economic resilience (engineering, ecological, evolutionary) and performs an analysis of GDP data of 200 countries worldwide for the period 1960–2020 and 15 economic crises (shocks). The empirical analysis, first, reveals that economic resilience appears positively related to gross value added (GVA), employment, education, sectorial structure and diversification, agricultural production, tax revenue and natural resources, whereas it is negatively associated with urbanization degree, primary sector specialization and trade activity. Also, it shows that the global economy shifted to a less resilient performance through time, and it reveals the pros and cons of the continents' performance in economic resilience, highlighting a relative sensitivity of European countries against the available shocks and relatively higher resilience of Asian and African countries. Finally, the analysis of transition probabilities reveals the 2008 economic crisis as the only shock with significant transitions among different states of resilience, providing insights into the insignificant geographical scale of previous shocks in the global economy. Overall, in the complex conceptualization and measurement framework of economic resilience, the proposed 3D index contributes to a multilevel consideration of diverse theoretical aspects of this concept, provides empirical insights into the global economy's resilience and facilitates better management of economic resilience‘s computational complexity.

Leveraging data mining and cybersecurity techniques to enhance algorithmic trading performance and forensic investigations in financial markets

In the evolving landscape of financial markets, the convergence of data mining, cybersecurity, and algorithmic trading plays a pivotal role in enhancing trading performance and forensic investigations. This study investigates how data mining techniques are leveraged to extract meaningful patterns and trends from vast financial datasets, improving the accuracy and profitability of algorithmic trading strategies. By identifying historical trends, price movements, and trade margins, data mining enables traders to optimize decision-making processes and manage risks more effectively. Cybersecurity emerges as a critical factor in safeguarding both trading algorithms and sensitive financial data from cyber threats. The integration of advanced cybersecurity measures ensures the integrity, confidentiality, and availability of trading systems, reducing vulnerabilities that could be exploited by malicious actors. Additionally, forensic investigation techniques are employed to detect fraudulent trading activities, such as insider trading and market manipulation, thereby protecting market participants and maintaining regulatory compliance. This research highlights the importance of combining secure data mining practices with robust cybersecurity measures to enhance the overall performance of algorithmic trading systems. Furthermore, it explores how forensic methodologies can help detect anomalies and ensure the transparency and fairness of financial markets. Through an integrated approach, this study emphasizes the potential of data mining and cybersecurity in transforming trading operations while mitigating risks associated with cyber threats and financial fraud.

Allocation or Skill? What is Driving Corporate Trading Performance in the EU ETS?

This study empirically analyzes factors related to companies’ profits from trading emission allowances in the European Union Emissions Trading System (EU ETS) for the period from 2005 to 2017 by combining information on trading activities with company characteristics of more than 6,000 companies. The factors considered include net position (i.e., free allocation of allowances minus emissions), strategic skills (i.e., banking of allowances, timing of trading, transaction frequency, use of intermediaries), skill-related structural factors (i.e., number of installations, sector affiliation), market pressure, year, and region effects. The results from estimating a Panel Heckman Selection Model suggest that companies’ profits from buying and selling emission allowances are related to a company’s net position, banking of allowances, timing of trading, and the number of installations. The findings further indicate that companies choose the number of banked allowances efficiently, that is, they take into account the opportunity costs of selling these allowances on the market. JEL Classification: Q48, Q54, Q58

Independent operation or coordinated integration? Enhancing the system resilience of ports in dealing with congestion based on a bilateral bargaining game

Fierce competition between ports may trigger substantial issues including port congestion, further wreaking havoc on the system resilience of ports. The coordinated integration of ports becomes a feasible and indispensable strategy for mitigating competitive pressure and enhancing the system resilience. In a two-tier supply chain within trade activities between two adjacent ports, we discuss the competitive and cooperative strategy selections between ports by a bilateral bargaining game to investigate how to improve the system resilience of ports in coping with congestion. The results reveal that port cooperation has the advantage of improving throughput and the system resilience of ports by alleviating port congestion, but becomes more challenging as the advantageous port's bargaining power and competitive intensity increase. Although under the pressure of high freight rates, shipping companies are still willing to actively participate in and promote the coordinated integration of ports for a premium service provided by ports. From the overall shipping supply chain, port cooperation optimizes the entire operation of port system and promotes profits from the high system resilience, demonstrating a better environmental performance by dealing with congestion. In light of the conclusions, it is essential to vigorously establish a port-port alliance through coordinated contracts to tackle congestion and enhance resilience, thereby boosting competitiveness and ensuring profitability in the whole system of ports.

Automated Machine Learning for Optimized Load Forecasting and Economic Impact in the Greek Wholesale Energy Market

This study investigates the use of automated machine learning to forecast the demand of electrical loads. A stochastic optimization algorithm minimizes the cost and risk of the traded asset across different markets using a generic framework for trading activities of load portfolios. Assuming an always overbought condition in the Day-Ahead as well as in the Futures Market, the excess energy returns without revenue to the market, and the results are compared with a standard contract in Greece, which stands as the lowest as far as the billing price is concerned. The analysis achieved a mean absolute percentage error (MAPE) of 12.89% as the best fitted model and without using any kind of pre-processing methods.

Research on International Trade Development Path of Small and Medium-sized Enterprises in the Context of E-commerce Trade

With the rapid development of Internet technology and the advancement of globalization, e-commerce has become an important part of international trade activities. In this context, how to expand the international market and enhance the competitiveness of small and medium-sized enterprises with the help of e-commerce trading platform has become a hot issue in current research. This paper first summarizes the development of e-commerce trade and its impact on the international trade of small and medium-sized enterprises (SMEs), and then analyzes the current situation and main problems of the international trade of small and medium-sized enterprises. On this basis, it puts forward the development path and strategy of SMEs' international trade under the background of e-commerce trade, including establishing e-commerce trade platform, strengthening supply chain management, utilizing cross-border e-commerce, strengthening brand building, and innovating service mode. This paper aims to provide theoretical support and practical guidance for SMEs to carry out international trade under the background of e-commerce trade.

Effect of road infrastructure on food sovereignty in Akwa Ibom State, Nigeria

The study was designed to assess the effect of road infrastructure on food Sovereignty in Akwa lbom State, Nigeria. The specific objectives of the study were to: ascertain the socioeconomic characteristics of the respondents; identify the food sovereignty in the study area and ascertain the effect of road infrastructure on food sovereignty in the study area. The survey research design was adopted for the study. The population of the study comprised all rural farming households in Akwa Ibom State. The study adopted multi-stage and simple random sampling techniques. Three blocks were selected from each of the three Agricultural Zones in the state. Three cells were randomly selected from each of the blocks sampled, which gave a total of twenty-seven (27) cells. A total of 450 respondents were selected using simple random sampling technique. Data were collected with the aid of a semi structured questionnaire. Data obtained were analyzed using percentages, means and standard deviation as well as ranking. The results of the socio-economic characteristics of the respondents showed that 58.90% of the respondents were males (265), while 41.10% of them were females (185). A good number of the respondents, 53.60%, were married (241), while 24.20%were single (109). Also, the results showed that 19.60% of the respondents had no formal education (88), while 30.70% attained secondary level of education (134), and about 33.70% of the respondents had tertiary level of education (152). The socio-economic characteristics of the respondents also indicated that 40.0% of the respondents had farm size ranging from 1-2 hectares, while 5.80% had farm size of 5 hectares and above. A good number of the respondents had access to credit (59.60%), while a small proportion (40.40%) had no credit facilities. The study revealed that 21.30% of the respondents had income ranging from N351,000 to N450,000, less than one US$ while a small proportion of the famers (8.90%) had income of about N251,000 to N350,000 only from farming activities. The main sources of food sovereignty of the people were crop farming and livestock production, though some were involved in trading and artisanal activities. The study noted that road projects have reduced accident (x ̅=2.75), increased farmers’ income (x ̅=3.20), increased trading and shopping activities (x ̅ =2.62), and reduced floods (x ̅ =2.64) among others. It was also concluded that road projects have positive effects of food sovereignty although some of the abandoned projects have caused some hardship and environmental challenges. The study recommended the completion of all abandoned road projects carried out in rural Akwa Ibom State in particular, and Nigeria in general. The study, however, concluded that in Akwa Ibom State, rural road projects have brought the much needed relief from accidents, wastage, spoilage, and food sovereignty to many hitherto isolated rural communities. Key words: Akwa Ibom State, Effect, Farmers, Food, Sovereignty, Road infrastructure

Retail Trading Around Earnings Announcements: Evidence from Robinhood Traders

Retail investors from the discount broker Robinhood swarm into stocks with pending earnings announcements and stay away from them immediately after the announcements. We study four competing explanations for this phenomenon: liquidity provision, informed trading, lottery preference, and attention-induced herding by noise traders. We find strong evidence that, immediately around earnings announcements, Robinhood investors’ behavior is primarily driven by attention-induced noise trading. Our results offer new insights into retail traders’ motivation for trading when they face heightened uncertainty from earnings announcements. We also find corroborative evidence from a proprietary data that tracks retail trading activities from NASDAQ.

Identifikasi Modal Sosial dan Kekuasaan dalam Underground Economy Pasar Maling, Kota Malang

Purpose: This study aims to reveal the role of social capital and power structures in the underground economy of Pasar Maling, Malang City. Methodology: This study used a phenomenological qualitative method. To obtain data, unstructured interviews and observations were conducted with triangulation of sources and Nvivo14 was used to process the data. Results: The research reveals the role of social capital in strengthening the existence of the underground economy through four main aspects: trust, networks, information, and norms. The power structure that can provide rules or contracts at Pasar Maling Malang City is in the form of informal contracts and is dominated by the non-government community, namely the Madurese ethnic community. This market is similar to a perfect competition market, but in the ongoing economy market, Pasar Maling Malang City has restrictions on entering the market or barriers to entry. Only people of the same ethnicity can participate in and conduct trading activities in Pasar Maling Malang City. Limitations: This research only focuses on the market's internal perspective, including sellers and the surrounding community in Pasar Maling. Contribution: This research may provide additional knowledge for readers and serve as a reference for further research on underground economy.

Energy factors affecting environmental pollution for sustainable development goals: The case of India

This study investigates the nexus between electricity consumption, fossil fuel dependency, renewable energy adoption, population growth, trade activities, economic growth, and environmental pollution in India. The primary objective is to understand how these factors interrelate and influence each other, focusing on their implications for sustainable development. The study used data from the World Bank from 2000 to 2023; the methodology adopted includes vector autoregression modeling, Granger causality tests, cointegration analysis, impulse response functions, and variance decomposition. These econometric techniques were selected due to their ability to capture dynamic relationships, determine causality, and identify long-term equilibrium among the variables. The findings reveal that economic growth significantly increases electricity consumption and fossil fuel usage, leading to higher carbon dioxide emissions. On the other hand, renewable energy adoption reduces environmental pollution. The study also highlights the complex interplay between population growth, urbanization, and trade activities in shaping India's energy demand and environmental outcomes. The implications of these findings are critical for India's sustainable development. The results suggest that while economic growth is essential, it must be balanced with sustainable energy practices to mitigate environmental pollution. The findings emphasize the need for policy interventions that promote renewable energy, enhance energy efficiency, and enforce environmental regulations. Recommendations include accelerating renewable energy adoption, implementing stringent energy efficiency standards, and developing integrated policies that simultaneously address the economic, energy, and environmental dimensions. These actions will help India achieve a sustainable balance between economic growth and environmental protection, ensuring a healthier future for its population.

Assessment of Prospects for Sustainable Cross‐Border Cooperation of the Russian Post‐Virgin Regions of the Urals and Siberia with the Republic of Kazakhstan

Aim. Comprehensive assessment of the stability of cross‐border cooperation between the Russian steppe regions of the Urals and Siberia and the Republic of Kazakhstan in the fields of foreign trade and migration. To achieve the goal, a model has been developed to assess the prospects for sustainable cross‐border interaction of the Russian steppe regions of the Urals and Siberia with the Republic of Kazakhstan.The research conducted using the methodology developed made it possible to identify the problems of cross‐border interaction of Russian steppe regions with the Republic of Kazakhstan. Against the background of a decrease in general mobility of the population of the Russian steppe regions, the share of those who left for the Republic of Kazakhstan among the total number of those who left abroad had a positive trend during the period analysed in the vast majority of steppe regions of the Russian Federation. In five of the eight regions considered, the interaction is characterized as "stable" and "steady", "unstable" interaction in the field of migration only in the Altai Territory.The Tyumen Region was the leader in terms of the share in the country's export‐import operations among the steppe regions of the Russian Federation for 2015–2021. In the period under review, foreign trade turnover had a stimulating effect on the economy of the Chelyabinsk region, the Republic of Bashkortostan and the Novosibirsk region. At the same time, the most active foreign trade activity with the Republic of Kazakhstan was observed in the Altai Territory and Omsk and Kurgan regions. Stable cross‐border cooperation in the field of foreign trade with the Republic of Kazakhstan is only in place in the Kurgan region.

Designated market makers and agricultural futures market quality: Evidence from China's Dalian commodity exchange

AbstractMany financial markets use designated market makers (DMMs), but the impacts of DMMs on agricultural futures markets – and in particular, how to arrange DMMs among contracts expiring in different months – are largely neglected. In 2017, Chinese exchanges started recruiting DMMs for inactive contracts when they become nearby contracts to address the discontinuous trading activity of nearest‐to‐maturity contracts, which enables us to study the benefit and cost of recruiting DMMs for inactive contracts using a quasi‐experimental framework. Leveraging tick‐by‐tick data on corn and soybean meal futures, we find that DMMs improve the market quality of inactive contracts without disrupting the market quality of dominant contracts. Heterogeneity analysis in policy settings suggests that more DMMs are conducive to improving market quality for corn and soybean meal futures. We demonstrate that DMM policy is a feasible measure to facilitate continuous activeness in Chinese agricultural futures markets. Our results are important for exchanges and regulators seeking to better design and implement designated market‐making programs in agricultural futures markets.