Impact Of Trading Research Articles

Zero-carbon-oriented optimal power scheduling of electric vehicles considering V2G response

Abstract This paper presents an electric vehicle (EV) optimization scheduling method that incorporates vehicle-to-grid (V2G) responses within the framework of a carbon market. Initially, the method characterizes the grid-connected and off-grid operational states of EVs. These states are represented by three types of probability density functions derived from historical data. Subsequently, a V2G response model is formulated based on consumer psychology theory. The approach then integrates the impact of carbon trading on the charging and discharging schedules of EVs, aiming to minimize carbon trading costs. The resulting optimization scheduling model is solved using the CPLEX solver.

Tackling nonlinear price impact with linear strategies

AbstractEmpirical studies in various contexts find that the price impact of large trades approximately follows a power law with exponent between 0.4 and 0.7. Yet, tractable formulas for the portfolios that trade off predictive trading signals, risk, and trading costs in an optimal manner are only available for quadratic costs corresponding to linear price impact. In this paper, we show that the resulting linear strategies allow to achieve virtually optimal performance also for realistic nonlinear price impact, if the “effective” quadratic cost parameter is chosen appropriately. To wit, for a wide range of risk levels, this leads to performance losses below 2% compared to a numerical algorithm proposed by Kolm and Ritter, run at very high accuracy. The effective quadratic cost depends on the portfolio risk and concavity of the impact function, but can be computed without any sophisticated numerics by simply maximizing an explicit scalar function.

Effects of Child Street Trading on Educational Outcomes in Lagos Nigeria

This study examines the effects of child street trading on educational outcomes in Lagos, Nigeria. Using a qualitative research design, data were collected through semi-structured interviews with parents and teachers to explore how street trading impacts school attendance, academic performance, and the cognitive and emotional development of children. Data were analyzed using thematic analysis, which involved emergent open coding to identify recurring patterns and themes. The analysis revealed four major themes: (1) disruption of school attendance and engagement, (2) academic performance and learning challenges, (3) cognitive and emotional development, and (4) socioeconomic pressures and educational aspirations. The findings show that street trading significantly disrupts children’s school attendance, leading to tardiness, missed classes, and exhaustion, which hinder their ability to concentrate and engage in learning. As a result, academic performance suffers, with children experiencing gaps in knowledge and declining grades. Additionally, the emotional toll of street trading was evident, with many children struggling with low self-esteem and feelings of failure, further diminishing their motivation to succeed academically. The study concludes that child street trading poses substantial barriers to educational success, perpetuating poverty and limiting future opportunities. These findings highlight the urgent need for targeted policies and interventions to mitigate the negative impact of street trading on children’s education in Lagos, Nigeria.

How Does China’s Carbon Emissions Trading Policy Affect the Financing of High-Carbon Enterprises?

Evaluating the impact of carbon emissions trading (CET) policy on the operations and development of high-carbon enterprises is of great practical importance in a context where policy-makers aim to balance steady growth and reduce carbon emissions. Based on the panel data of A-share listed enterprises, this paper comprehensively employs the difference-in-differences (DID) and the difference-in-differences based propensity score matching (PSM-DID) methods to investigate the impact of China’s CET policy on the financing constraints and financing ability of high-carbon enterprises. The results indicate that: first, the level of financing constraints of high-carbon enterprises in China has significantly increased with the implementation of the CET policy from 2012 to 2019. Second, the impact shows significant heterogeneity in various industries, carbon markets, and the characteristics of enterprises. Third, the CET policy reduces the long-term debt financing ability of high-carbon enterprises by 22.26 percent during the sample period, but it has no significant impact on short-term debt financing ability. JEL Classification: C33, D92, G32, Q43, Q58

Global value chain participation, globalisation-Energy Nexus and sustainable development in ASEAN

Achieving net zero carbon emissions necessitates a systemic reorganization of global value chains, particularly in the ASEAN region, due to its growing role as a manufacturing hub. This study explores the interaction between global value chains (GVCs), globalization and sustainable development in ASEAN countries from 2014 to 2022. Using data from sources like the World Development Indicators, Human Development Index, Eora Global Value Chain Database, and others, the study employs a system-generalized method of moments to address endogeneity. The findings reveal that GVC participation significantly impacts sustainable development, with a 1 % increase in GVC involvement leading to a 0.11 % rise in sustainable development. Additionally, globalization metrics such as trade openness and merchandise trade, excluding foreign direct investment, also positively influence sustainable development. When combined with GVCs, these factors further enhance sustainable outcomes. The study also highlights the positive impact of trading in low-carbon goods on sustainable development. Based on these findings, the study recommends policies that promote sustainable production practices within GVCs, sustainable urban planning, good governance, and investment in green infrastructure. Additionally, increased investment in renewable energy technologies and infrastructure is essential to ensure equitable access to clean energy. Governments should prioritize transitioning to low-carbon energy sources to mitigate the negative effects of greenhouse gas emissions.

Impact of arbitrage trading between an ETF and its underlying assets on market liquidity of their markets using an agent-based simulation

Impact of arbitrage trading between an ETF and its underlying assets on market liquidity of their markets using an agent-based simulation

Impact of carbon emission trading on urban green innovation: empirical evidence from China’s carbon emission trading pilot policy

In the face of global climate change challenges, China’s implementation of the carbon emission trading (CET) pilot policy has provided new empirical research opportunities. Based on a dataset covering 281 Chinese cities from 2005 to 2021, this paper employs econometric models to conduct an in-depth analysis of the policy’s impact on urban green innovation (UGI). The findings indicate that the CET pilot policy has significantly promoted green innovation activities in affected cities, with positive effects observed both directly in pilot cities and indirectly in non-pilot cities through spatial spillover effects. In addition, the policy has been found to encourage technological investment and enhance public environmental awareness (PEA), further advancing green innovation. The paper also unveils comprehensive policy effects, indicating that the Big Data Comprehensive Test Zone policy and the New Energy Demonstration City policy work synergistically with the CET pilot policy in advancing green innovation. These findings provide valuable experiences and insights for designing environmental policy tools at the national level, promoting green development, and constructing climate change response strategies.

How does carbon trading price matter for bank loans? Evidence from Chinese banking sector

This paper investigates the impact of carbon trading prices on Chinese commercial banks. We propose a stress test model to calculate the decline of firms’ liabilities and the climate-driven loss of commercial banks to different industries. The results indicate that State-Owned Banks suffer the highest climate-driven loss among all types of banks. City commercial banks suffer the highest climate-driven loss ratio since they maintain a relatively low level of Tier 1 core capital. Beijing, Shanghai, Jiangsu, and Zhejiang maintain the highest levels of climate-driven loss ratio. Furthermore, the allocation of loans portfolio across different industries also influences climate-driven loss of banks. The climate-driven loss to the electric power, heat, gas, and water production and supply sector is the largest in all industries. It is necessary for banks to incorporate climate factors into the risk assessment framework.

Potential and challenges of Peer-To-Peer (P2P) electrical energy trading: investigation and case study

This paper explores the potential and challenges associated with Peer-to-Peer (P2P) electrical energy trading, focusing on both theoretical investigation and practical application through a comprehensive case study. By examining the interactions between prosumers (those who both produce and consume energy) and consumers, we employ utility functions to model these interactions. Optimization is achieved using a non-cooperative game theory approach coupled with real-time pricing mechanisms to reflect market dynamics accurately. Our analysis ensures feasibility and reliability by considering crucial factors such as energy balance and grid capacity constraints, which are essential for maintaining system stability. The simulation results demonstrate the effectiveness of our proposed method. These results highlight the significant potential of P2P trading to enhance overall energy efficiency, promote decentralized energy management, and reduce reliance on traditional energy sources. Furthermore, this study provides detailed insights into maximizing total utility by determining optimal prices and energy trades, ultimately showcasing the transformative impact of P2P trading on real-time energy market operations.

ANALYSIS OF THE IMPACT OF CRYPTO TRADING ON CARBON EMISSIONS USING PATH ANALYSIS

In parallel with the growing interest in cryptocurrencies, the relationship between crypto trading and CO2 is critical to drive financial markets and environmental sustainability efforts. The aim of this study is to analyse the impact of crypto trading on carbon emissions (CO2) through the mediating roles of international trade and energy use. Within the scope of the study, path analysis was carried out using the 2007-2021 period data of the top 20 countries with high crypto trade volume. A model proposal was presented to examine the relationships between the variables used in the study and the necessary analyses were carried out. The results of the analysis show that crypto trade volume has a positive and significant effect on carbon emissions. It is also concluded that international trade and energy use mediate the relationship between crypto trade and carbon emissions. It is seen that crypto mining activities and cryptocurrencies lead to an increase in energy use and environmental impacts. At this point, it is important for countries to switch to renewable energy sources and to regularly report and monitor the impact of cryptocurrency mining activities on carbon emissions.

The impact of carbon emission trading on the financing constraints of high-emission enterprises: Evidence from China

Using Difference-in-Differences (DID) and Propensity Score Matching combined with Difference-in-Differences-in-Differences (PSM-DDD) methodologies, this paper examines the impact of China's carbon trading pilot policy on enterprise financing. We find that the high-emission enterprises in pilot regions are less financially constrained, especially for state-owned enterprises. The carbon trading policy may motivate high-emission enterprises to reduce carbon emissions through green technology innovation, thereby ameliorating their financing environment. Our findings suggest the economic significance of carbon emission trading in enterprise financing.

Data-driven evaluation for quantifying energy resilience in distribution systems with microgrids and P2P energy trading

Electrical distribution systems (EDS) face the major issue of complete interruption of power when the supply end of the electrical grid encounters extreme events. The integration of distributed energy resources (DERs) at the residential level has opened the path to building energy resilience within these systems, enabling them to withstand such incidents at the load end. To further enhance energy resilience, peer-to-peer (P2P) energy trading networks could be established at the community level. While several researchers have developed models to implement energy trading in the P2P network with DERs, enabling prosumers to benefit from cost savings, the impact of both DERs and P2P energy trading on the system’s resilience has not been evaluated with a quantifiable measure. In this work, we propose a methodology introducing a quantifiable measure for evaluating energy resilience in electrical distribution systems with DERs and P2P energy trading by calculating the percolation threshold (PT) using complex networks for both univariate and multivariate data. We employ cooperative game theory to model P2P energy trading, ensuring that all prosumers participate rationally. We consider the formation of microgrids in a standard IEEE-123 node test feeder system integrated with renewable energy sources. The improvement in energy resilience with trading of energy in the P2P network is analyzed for the most resilient microgrid in the distribution system. The results demonstrate a 67.91% total cost benefit and a 25.07% improvement in the resilience of the microgrid due to the integration of DERs and P2P energy trading for a period of one year.

Carbon pricing policies and renewable energy development: Analysis based on cross-country panel data

While studies have theoretically discussed the impact of carbon pricing on renewable energy, the practical implementation and effectiveness of these policies remain uncertain. This study empirically examines the role of carbon emissions trading and carbon tax in global renewable energy development using panel data from 196 countries and regions and employing the staggered difference-in-differences (DID) model and Bacon decomposition method. The results suggest that: (1) From the perspective of policy shocks, carbon trading has increased non-hydro renewable electricity generation by 73.32%, while carbon tax has increased it by 31.79%. This indicates that the overall impact of carbon trading on renewable energy is greater than that of carbon tax. However, the elasticity coefficients of renewable energy to carbon trading prices and carbon tax rates are 0.1801 and 0.1845, respectively, suggesting a slightly greater marginal effect of carbon tax on renewable energy compared to carbon trading. (2) Both carbon tax and carbon trading have mitigated the growth of fossil electricity and encouraged public investment in renewable energy, thereby fostering its development. (3) The influence of carbon pricing on renewable energy varies by income level; notably, the implementation of these policies in high-income countries has diminished their promotional effect on renewable energy. (4) The contribution of technological innovation to renewable energy development is smaller than that of policies including carbon trading and carbon tax, indicating that renewable energy development during the sample period was predominantly driven by policy measures. The findings indicate that the application of carbon pricing policies should be further promoted to accelerate the energy mix transition.

Margin trading, short selling, and information asymmetry

We investigate the impact of margin trading and short selling (MTSS) on information asymmetry using data from a unique Chinese pilot program that permits MTSS for a specific list of stocks. We establish a theoretical framework indicating that MTSS enhances the pricing system’s informativeness, leading to reduced information asymmetry. Motivated by this theoretical framework, we design a quasi-experiment to analyze data from 2013 to 2016. We find that indeed MTSS weakens information asymmetry. Furthermore, the reduction of information asymmetry can be attributed to both margin trading and short selling.

Can carbon emissions trading policy promote product bargaining power increases for high-carbon enterprises? Evidence from China.

Carbon emissions trading policies play a crucial role in facilitating the transition to high-end products within high-carbon enterprises. Nevertheless, current empirical analyses of the carbon emissions trading market exhibit a lack of precision and are susceptible to bias in their findings. Limited research has been conducted on the influence of product quality as a potential constraint on the impact of carbon trading on product bargaining power. This study presents a double-difference model utilizing data on emission-control enterprises in China's carbon market to examine the influence of the carbon emissions trading mechanism on the bargaining power of high-carbon products. Empirical analysis is conducted using financial data from listed companies in China spanning the years 2010 to 2020. The findings indicate that the implementation of carbon emissions trading policies has a dampening impact on the product bargaining power of high-carbon enterprises. Moreover, carbon emissions trading policies have heterogeneous effects on the product bargaining power of high-carbon firms with different life cycles, with mature high-carbon firms receiving a boost and declining high-carbon firms receiving a dampening effect. Mechanism test finds that the incomplete transmission effect of cost shocks resulting from carbon emissions trading policies has negatively affect the product bargaining power of high-carbon enterprises. Further research finds that product quality is a key factor in determining the effect of the carbon emissions trading policy, and that the impact of the carbon emissions trading policy on the bargaining power of products of high-carbon firms takes on a "U" shape due to product quality. Once the product quality exceeds the bottleneck value of 0.5956, the policy significantly increases the bargaining power of products. The study confirms that the establishment of carbon markets can effectively increase the bargaining power of superior products. These results offer a comprehensive theoretical and practical foundation for nations to advance the development of carbon markets and facilitate the achievement of sustainable development by high-carbon enterprises.

A low-carbon route optimization method for cold chain logistics considering traffic status in China

In the paper of cold chain logistics, it is necessary to consider both traffic status and carbon reduction simultaneously. In this paper, an improved BPR (Bureau of Public Roads) road impedance function is designed, which reflects the traffic status in China under congested status more accurately. A low-carbon cold chain logistics route optimization model considering the traffic status in China is constructed, considering the multiple impacts of traffic status on total delivery cost, freshness of fresh products, and carbon emissions. To address the challenges posed by this multidimensional and discrete model, an improved discrete firefly algorithm (IDFA) is proposed. The numerical result demonstrates that IDFA has higher solving efficiency and better quality of the obtained solutions. Moreover, this paper also analyzes the impact of traffic status, vehicle types, and carbon trading prices on cold chain logistics delivery, as well as the comprehensive impact of traffic status and carbon trading prices. The proposed model is suitable for cold chain logistics enterprises with a single delivery center, active emission reduction willingness, and mostly delivering in congested road sections with high traffic volume. It offers valuable guidance for decision making and management in low-carbon cold chain logistics delivery.

Impact of Derivative Trading on Stock Market Volatility: Empirical Evidence from Emerging Markets

This study investigated the impact of derivative trading on stock market volatility in emerging markets. We analyzed data from 10 emerging markets over 15 years (2005-2020) using a panel data approach. The research employed GARCH(1,1) models to estimate volatility and conducted difference-in-differences (DiD) analysis to assess the effect of derivative introduction. Additionally, we used Granger causality tests to examine the directional relationship between derivative trading and volatility. Results indicated that introducing derivatives significantly reduced stock market volatility (β = -0.0023, p < 0.01). This effect was more pronounced in markets with higher liquidity (interaction β = -0.0012, p < 0.05) and better regulatory frameworks (interaction β = -0.0015, p < 0.05). Granger causality tests suggested a unidirectional relationship, with derivative trading Granger-causing reduced volatility (F = 7.234, p = 0.002). Furthermore, GARCH persistence analysis revealed decreased volatility persistence post-derivative introduction across all sample markets. These findings contribute to the ongoing debate on the role of derivatives in financial markets and have important implications for policymakers and market regulators in emerging economies.

Impact of carbon emission trading system on green technology innovation of energy enterprises in China

China proposed establishing a carbon emission trading market in its 12th Five-Year Plan to reduce carbon dioxide emissions through market mechanisms, promote the development of science and technology and help China become an environment-friendly country. To examine the impact of carbon emission trading on green technology innovation in Chinese energy enterprises, data from 1993 to 2020 were collected from 494 A-share-listed energy enterprises. Enterprises located in the pilot area of carbon emissions trading were assigned to the treatment group, while those in the non-pilot area were assigned to the control group. The propensity-score-matching method was utilized to match the treatment group with the control group, and the resulting samples were used as the actual sample data. The difference-in-differences method was then employed to assess the net impact of carbon emission trading and investigate its effect on green technology innovation in energy enterprises. This empirical study suggested that carbon emission trading has a positive impact on green technology innovation in energy enterprises, particularly state-owned ones. Larger enterprises are more willing to engage in green technological innovation than small enterprises. Furthermore, when faced with a carbon emission trading system, ‘mature’ companies tend to pay more attention to green technology innovation than younger enterprises do. This study puts forward policy measures for establishing a national-level carbon emission market in China in the future.

Exchange market share, market makers, and murky behavior: The impact of no-fee trading on cryptocurrency market quality

This study examines the impact of zero fees on market quality. This issue is examined using a natural experiment in Bitcoin provided by the Binance exchange, which eliminated maker–taker trading fees for market participants in July 2022. I find that although zero fees increase investors’ willingness to trade, thereby prima facie increasing liquidity, their elimination encourages market makers to widen the bid–ask spread and provide a shallower market depth, which in turn reduces liquidity. Liquidity providers realize gains at the expense of liquidity takers, suggesting the emergence of new potential forms of unethical financial market conduct. Notably, despite the removal of trading fees, total transaction costs increased for customers. These outcomes, coupled with the boost in exchange market share, raise concerns about price integrity and investors’ protection in the highly unregulated crypto environment, in turn implying that the elimination of maker–taker fees is harmful to the market.

Optimization model of monthly continuous bidding transaction in electricity market considering risk hedging

In order to further alleviate the problems of large assessment deviations, low efficiency of trading organisation and difficulties in system optimisation in medium- and long-term market trading, the article proposes an optimisation model for continuous intra-month bidding trading in the electricity market that takes into account risk hedging. Firstly, the current situation of market players’ participation in medium and long-term trading is analysed; secondly, the impact of contract trading on reducing operational risks is analysed based on the application of hedging theory in the primary and secondary markets; finally, the continuous bidding trading mechanism is designed and its optimisation effect is verified. The proposed model helps to improve the efficiency of contract trading in the secondary market, maintain the stability of market players’ returns and accelerate the formation of a unified, open, competitive and well-governed electricity market system.