Trading Activity Research Articles

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.

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

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.

Multi-market trading and overnight price discovery: Evidence from American Depository Receipts

This article compares the overnight price discovery of American Depository Receipts (ADRs) and common stocks traded in the US stock market. It examines how trading activities of ADRs’ underlying shares in home markets affect price discovery. We find that the efficiency of the opening price and the price discovery during the close-to-open period is significantly higher than that of US common stocks. Further analyses show that the price discovery of ADRs shifts from the trading day to the overnight, and the opening prices of ADRs are more efficient if there are more trading activities of underlying shares in home markets. The results suggest that trading similar assets in multiple markets over non-overlapping hours improves price efficiency. JEL Classification: G12, G14, G15

J-Curve For Indonesia’s Trade Balance with Non-Linier ARDL

The performance of Indonesia’s Balance of Payments (BOP), especially for the trade balance/current account, which recorded a surplus and adequate foreign exchange reserves, controlled political conditions, and attractive yields, can impact the exchange rate. This improvement in the exchange rate further encouraged the entry of foreign investors, which caused the Indonesian economy to continue to grow when the world experienced a financial crisis. This study analyzes asymmetric models to prove the Marshall Lerner Condition of Indonesia with trading partners. Using NARDL methods, this study uses monthly data from 2005 to 2021 from the International Federal Reserve (IFS), a data source for foreign trade activities. The result of this study is a J curve in Indonesia’s trade pattern with its trading partners, formed in the United States, Singapore, Vietnam, and Japan. For the nonlinear ARDL method, the J curve is formed in trading partners Netherlands, Germany, Korea, Singapore, United Kingdom, Vietnam, and Japan. The implementation of Indonesia’s exchange rate policy should be followed by a policy that can suppress the exchange rate against inflation because if this policy is not followed, it will not significantly impact Indonesia’s trade performance in the long run.

ASSESSING FOOD SAFETY AWARENESS AND PRACTICES AMONG STREET FOOD VENDORS IN KATSINA STATE, NORTH WESTERN NIGERIA

Food safety is a critical global issue, with contaminated food posing serious health risks, particularly to vulnerable populations such as children under five, the elderly, and the sick. This study examined food safety practices among street food vendors in major towns of Katsina State. Using structured questionnaires and a multi-stage sampling technique, data were collected from a total of 316 street food vendors to assess vendors' awareness and adoption of food safety measures. Descriptive statistics and traffic light model were used to analyse the data. While vendors demonstrated high awareness of basic hygiene practices like washing utensils and avoiding work when ill, the adoption of other crucial practices, such as using hand gloves and maintaining clean selling locations, was found to be low. This gap between awareness and practice highlights the need for targeted interventions, including training programs and public awareness campaigns, to bridge the knowledge-behaviour gap. The traffic light model categorized food safety risk to levels, revealing that many vendors operate at high to moderate risk levels. These findings underscore the importance of continuous monitoring, feedback, and enforcement of food safety regulations. Recommendations include enhancing access to resources, providing incentives for good practices, and implementing regular health and safety audits. This can significantly reduce foodborne illnesses, ensuring safer food consumption, and supporting national health and economic development through safer trade and tourism activities. This study contributes to the on-going discourse on food safety in developing regions and highlights critical areas for policy and practical interventions to safeguard public health.

Управление логистическими процессами в трансграничной электронной коммерции

In the context of the globalization of the economy and the development of cross-border e-commerce, the importance of cross-border logistics is increasing, allowing for an effective process of product distribution. The issues of organizing transport and logistics processes during the delivery of goods within the framework of the functioning of cross-border e-commerce are discussed. The main aspects of the development of e-commerce logistics and its impact on the trading business have been studied. An analysis of the cross-border e-commerce market in Russia is carried out. It is noted that currently the global logistics industry is in an unstable environment. The main directions and trends in the development of logistics services in modern conditions are considered and the specifics of adapting the process of goods distribution within the framework of cross-border e-commerce to changes in the external environment are investigated. The distinctive features of e-commerce logistics have been studied in the context of its impact on the trading business, which allows for increased efficiency of logistics processes such as procurement, transportation, order processing, inventory and warehouse management, packaging and labeling. It has been proven that with the development of information technology and telecommunication networks, as well as increasing demand in the field of online trading, the need for effective logistics support is significantly increasing, and delivery speed is becoming increasingly important to provide quality service to consumers. The advantages of e-commerce are substantiated from the perspective of subjects of trade and logistics activities, which include the global nature of customer coverage and the convenience of inter-subject interaction, reduction of operating costs of trade and logistics activities, expanded opportunities for marketing and advertising support, increased level of automation of e-commerce logistics management processes.

COREDAO.VIP: Crypto-Based Liquidity Pool Creation for Profit Maximization

The emergence of decentralized finance (DeFi) has revolutionized traditional financial markets, offering greater financial inclusion, transparency, and user autonomy. This paper investigates the creation of a coredao.vip crypto-based liquidity pool, allowing liquidity providers to profit similarly to traditional brokers. By leveraging blockchain-based liquidity pools, coredao.vip enables participants to contribute assets to decentralized platforms and earn rewards based on the trading activity within the pool. This research outlines the mechanism of liquidity pool creation, explores its profitability for liquidity providers, and analyzes the associated risks and benefits. The study further examines how decentralized liquidity protocols can democratize access to financial services while addressing liquidity challenges.

Visualising trade-related virtual urban land transfers in China

ABSTRACT As a type of environmental footprint, the concept of virtual land captures the indirect land use embedded in our consumption and trade activities. Utilising the environmentally-extended multi-regional input–output model (EEMRIO) and Kaleidoscope diagram, we visualise for the first time the interprovincial flow of virtual urban land in China. It unveils the intricate urban network connections and the telecoupled interactions between human activities and land use amidst China's rapid urbanisation phase. The results indicate that the eastern region of China emerges as the primary net beneficiary of virtual urban land, whereas the western region stands as the principal net contributor. The local urban land in 65% of the provinces suffices for their own consumption demands. However, provinces like Zhejiang, Henan, and Jiangsu rely heavily on inter-provincial urban land to fulfil their consumption requirements. Inter-regional trade plays a pivotal role in facilitating the flow of land resources, significantly easing the strain between human demands and land availability in the developed coastal provinces of eastern China. Yet, it imposes additional ecological pressure on the more ecologically vulnerable areas in the west. The insights from this research are poised to offer valuable guidance for the Chinese government in harmonising urban development strategies, industrial distribution and the allocation of construction land on a national scale.

Sustainable energy transition, knowledge co-creation and trade: the case of EU residential energy efficiency

ABSTRACT The European Union (EU) sustainable energy transition requires radical changes of economic, technological, societal and political systems. This paper empirically investigates the relationships among environmental policy, innovation and technological capabilities, and economic performances, in terms of country export competitiveness, focusing on residential energy efficiency goods, a core pillar of the EU energy and climate strategy. We combine network analysis with a gravity model to investigate the evolution of the EU bilateral trade and co-patenting activities from 1990 to 2015, based on a panel of 19 European countries. Our results show that the technological skills of the exporting country, related to the production of the households’ energy-consuming appliances, strongly enhance its export performances, and this effect is stronger when countries are EU members. Cooperation in knowledge creation and institutional proximities between trade partners are further key determinants of export performances of analysed countries.

PREDICTION OF UNIT VALUE INDEX OF EXPORTS OF SITC 897 JEWELRY AND PRECIOUS GOODS GROUP IN INDONESIA

Export is an international trade activity that plays an important role in the economic progress in Indonesia. One of Indonesia's leading commodities that dominate the export market is jewelry. In export activities, the export unit value index is an important component that serves to describe the development of export commodity prices. This unit value index always changes every time and fluctuates. This research conducts a comparative analysis of the performance of parametric method, non-parametric method, and machine learning, specifically, ARIMA, Fourier series estimator, and Support Vector Regression (SVR). This study aims to evaluate the effectiveness of various methods in improving prediction accuracy for the unit value index of the SITC code 897 in Indonesia. The research data used is secondary data including monthly export unit value index data with SITC code 897 in Indonesia obtained from the Central Bureau of Statistics. The data divided into 90% training data and 10% testing data. The methods used in this analysis are ARIMA, Fourier series estimator, and SVR. The best model obtained from each method is ARIMA (1,1,1) with MAPE of 10.92%, Fourier series estimator with MAPE of 8.47%, and an SVR RBF kernel function with MAPE of 3.73%. The results of this study obtained the best method for predicting the unit value index of SITC code 897 is SVR with an RMSE value of 8.288 and very good prediction accuracy.

Can Bitcoin trigger speculative pressures on the US Dollar? A novel ARIMA-EGARCH-Wavelet Neural Networks

In recent years, Bitcoin has garnered attention as a digital currency, prompting increasing debate regarding its effects on traditional financial markets, particularly the US dollar. This study investigates the relationship between Bitcoin and the US dollar, especially in the contexts of speculative attacks, where investors attempt to devalue a currency, and short squeezes, where rapid price rises force short sellers to quickly buy back assets to avoid further losses. The study employs a novel hybrid model combining an autoregressive moving average, Generalized Autoregressive Conditional Heteroskedasticity, and Wavelet Neural Networks techniques with neural networks approaches. The results suggest that significant trading activity in Bitcoin/US dollar, particularly during speculative attacks and short squeezes, can substantially impact the US dollar/EUR market, increasing price volatility as traders adjust their strategies. These adjustments, along with risk management strategies, drive higher trading volumes and further volatility. Our findings demonstrate that our novel hybrid model combined with Quantum Recurrent Neural Networks provides the most accurate predictions, offering valuable insights to inform trading strategies in both Bitcoin/US dollar and US dollar/EUR markets. This study has important implications for policymakers and market participants, emphasising the need to understand the relationship between Bitcoin and the US dollar for financial stability and effective policy formulation. It also highlights the necessity of advanced modeling techniques to accurately predict cryptocurrency market behavior.

Firm Heterogeneity and India’s Manufacturing Exports: Lessons on Protection and Trade Theory

ABSTRACT Empirical examinations of heterogeneity among Indian manufacturing firms provide helpful lessons for trade theories and policies. Using descriptive statistics of cross-section data for 2011, 2015, and 2019, the asymptotic Wilcoxon-Mann-Whitney test, and regression analysis, the study reveals that firms are heterogeneous within each 4-digit National Industrial Classification (NIC) category, exporting firms are more productive than non-exporters, and exporter premia decline with trading activities. The study concludes that recent protectionist policies reduced extensive trade margins, firm heterogeneity, and productivity in the Indian manufacturing sector.

Do Foreign Investors Underperform or Outperform Domestic Investors in Trading Activities? Evidence from Indonesia

The performance of foreign investors relative to domestic investors has been a subject of mixed evidence. While foreign investors are often perceived to underperform due to an information disadvantage, they are also known for their aggressive trading and superior performance in initiated orders. We provide further clarity on this issue. Specifically, by analyzing over five million transactions on the Jakarta Stock Exchange, our findings reveal that foreign investors consistently outperform domestic investors in terms of both annualized returns and profit amounts. Further investigation attributes this outperformance to the higher sophistication of foreign investors, who demonstrate superior stock-picking abilities and effective growth investing strategies.

Engagement in New Gambling Practices and its Association with Gambling Disorder, Impulsivity, and Cognitive Distortions: Findings from a Nationally Representative Sample of Spanish Gamblers.

Most epidemiological surveys focus on adult gambling behaviors related to traditional gambling forms, while studies on novel forms often focus on loot boxes and cryptocurrency trading individually. This study examines the co-ocurrence of emergent gambling and gambling-like practices, analyzing the demographic and psychological characteristics of involved gamblers. A cross-sectional study surveyed 1429 Spanish individuals aged 18-65, using a web-based questionnaire. The survey assessed participation in 19 gambling (e.g., lotteries, sports betting) and gambling-like activities (e.g., trading of cryptocurrencies and other assets, buying loot-boxes), along with sociodemographic and substance use. Problem gambling (PGSI), Impulsivity (UPPS-P), and cognitive distortions (Labrador's cognitive distortions scale) were also assessed. Participants who gambled over the past year (n = 921) were classified into four groups: traditional gambling (TG) only (64.5%, n = 594), TG with trading activities (27.5%, n = 253), TG with gambling withing video games or streaming platforms (2.5%, n = 23), and TG with both trading and video gambling (5.5%, n = 51). Most gamblers engaged exclusively in traditional formats, but 35.5% also participated in novel gambling forms. Those involved in both trading and video gambling were generally younger, male, with higher levels of impulsivity and gambling-related cognitive distortions compared to TG-only gamblers (p < 0.001). This group also exhibited higher rates of problem gambling and substance use (p < 0.001). This study emphasize the importance of including emerging gambling activities, which are particularly prevalent among high-risk gamblers, in epidemiological surveys. Identifying new gambling patterns and associated risk factors could help optimize public policies and develop more effective regulatory and prevention strategies.