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1 – 10 of over 3000Mohamed Shaker Ahmed, Adel Alsamman and Kaouther Chebbi
This paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market.
Abstract
Purpose
This paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market.
Design/methodology/approach
It uses the GJR-GARCH model to investigate feedback trading in the cryptocurrency market.
Findings
The findings show a negative relationship between trading volume and autocorrelation in the cryptocurrency market. The GJR-GARCH model shows that only the USD Coin and Binance USD show an asymmetric effect or leverage effect. Interestingly, other cryptocurrencies such as Ethereum, Binance Coin, Ripple, Solana, Cardano and Bitcoin Cash show the opposite behavior of the leverage effect. The findings of the GJR-GARCH model also show positive feedback trading for USD Coin, Binance USD, Ripple, Solana and Bitcoin Cash and negative feedback trading for Ethereum and Cardano only.
Originality/value
This paper contributes to the literature by extending Sentana and Wadhwani (1992) to explore the presence of feedback trading in the cryptocurrency market using a sample of the most active cryptocurrencies other than Bitcoin, namely, Ethereum, USD coin, Binance Coin, Binance USD, Ripple, Cardano, Solana and Bitcoin Cash.
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Edirimuni Nadeesh Rangana de Silva
South Asia is a region urgently seeking development, although it has failed in regional integration. It is the second least integrated region regarding the number of Free Trade…
Abstract
Purpose
South Asia is a region urgently seeking development, although it has failed in regional integration. It is the second least integrated region regarding the number of Free Trade Agreements (FTAs) and can thus be recognised as a missing bloc in the global multilateral system. This study aims to focus on South Asian FTAs and explores the problems of the inter-relations and compatibility between the systemic and regional trade systems.
Design/methodology/approach
The study proposes a framework to benchmark the compatibility of South Asian FTAs with WTO rules. Primary data from 2000 to 2020, including descriptive analyses of reports, legal text of the FTAs, official documents and factual presentations, have been collected and analysed through thematic analysis using the proposed framework.
Findings
The study finds that, although South Asian FTAs meet most of the WTO requirements, they are not progressing toward facilitating and promoting trade. Data from 2000 to 2020 show us that South Asian FTAs have not significantly impacted trade between themselves. The study argues that, although South Asian FTAs fulfil some benchmarks, they show only a lukewarm interest in contributing to the international trading system as building blocs. It is therefore recommended that the case of South Asian trade liberalisation must be understood contextually and be given careful and exclusive attention by the WTO.
Originality/value
As such, this study is the first to claim that South Asian FTAs are not fully compatible with the WTO rules. They remain a missing regional bloc in the multilateral system, rather than a building bloc or a stumbling bloc, delaying the region’s opportunity to develop as a region and within the larger system.
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Tiago Ferreira Barcelos and Kaio Glauber Vital Costa
This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000…
Abstract
Purpose
This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.
Design/methodology/approach
The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.
Findings
The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.
Research limitations/implications
The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.
Originality/value
Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.
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Harold Delfín Angulo Bustinza, Bruno de Souza and Roberto De la Cruz Rojas
Xiaojie Xu and Yun Zhang
For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction…
Abstract
Purpose
For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction problem based on the CSI300 nearby futures by using high-frequency data recorded each minute from the launch date of the futures to roughly two years after constituent stocks of the futures all becoming shortable, a time period witnessing significantly increased trading activities.
Design/methodology/approach
In order to answer questions as follows, this study adopts the neural network for modeling the irregular trading volume series of the CSI300 nearby futures: are the research able to utilize the lags of the trading volume series to make predictions; if this is the case, how far can the predictions go and how accurate can the predictions be; can this research use predictive information from trading volumes of the CSI300 spot and first distant futures for improving prediction accuracy and what is the corresponding magnitude; how sophisticated is the model; and how robust are its predictions?
Findings
The results of this study show that a simple neural network model could be constructed with 10 hidden neurons to robustly predict the trading volume of the CSI300 nearby futures using 1–20 min ahead trading volume data. The model leads to the root mean square error of about 955 contracts. Utilizing additional predictive information from trading volumes of the CSI300 spot and first distant futures could further benefit prediction accuracy and the magnitude of improvements is about 1–2%. This benefit is particularly significant when the trading volume of the CSI300 nearby futures is close to be zero. Another benefit, at the cost of the model becoming slightly more sophisticated with more hidden neurons, is that predictions could be generated through 1–30 min ahead trading volume data.
Originality/value
The results of this study could be used for multiple purposes, including designing financial index trading systems and platforms, monitoring systematic financial risks and building financial index price forecasting.
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Nida Rahman and Krishan Sharma
Regional comprehensive economic partnership (RCEP) is understood as the world's largest trading bloc given its contribution to the world output (30%). The mega trade bloc brings…
Abstract
Purpose
Regional comprehensive economic partnership (RCEP) is understood as the world's largest trading bloc given its contribution to the world output (30%). The mega trade bloc brings together 15 countries of East Asia, Southeast Asia and Oceania to eliminate tariff and non-tariff barriers in goods and services trade. The study suggests the importance of sector specific reforms for Malaysia to strengthen domestic capability.
Design/methodology/approach
The analytical framework constructs upon the partial equilibrium analysis and uses WITS SMART simulations.
Findings
The study finds that Malaysia's elimination of tariffs under the RCEP will cause a surge in imports from developed member countries of RCEP like Australia, South Korea and Japan. The study also finds a trade diversion in countries such as India. The empirical results establishes that RCEP would further strengthen intra-ASEAN trade.
Research limitations/implications
The study explores select sectors of the manufacturing industry in Malaysia.
Practical implications
The implementation of RCEP would impact the manufacturing sector immensely, especially in sectors like electrical machinery and equipment and inorganic chemicals, which are two of the major trading commodities of the Malaysian economy.
Social implications
Any trade agreement has a larger impact on the society. It may raise income, boost the consumer preferences and create or erode consumer welfare. The study reports the consumer welfare effect of the implementation of RCEP in Malaysia.
Originality/value
The study is the first attempt to do a partial equilibrium analysis for the electrical machinery and equipment sector and inorganic chemicals sector of Malaysia using both aggregated and disaggregated data at HS two-digit and HS six-digit level.
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Manuel Lobato, Mario Jordi Maura, Javier Rodriguez and Herminio Romero-Perez
This study aims to examine investor attention by exploring the trading behavior of investors in US-based exchange traded funds (ETFs) of countries active in the Federation…
Abstract
Purpose
This study aims to examine investor attention by exploring the trading behavior of investors in US-based exchange traded funds (ETFs) of countries active in the Federation Internationale de Football Association (FIFA) World Cups.
Design/methodology/approach
The present study employs event study methodology to measure abnormal returns and excess trading volume of country-specific ETFs during six FIFA World Cups. The sample of ETFs includes 19 participating countries.
Findings
Consistent with investor behavior that might be explained by attention effect, the study finds that country-specific ETFs from participating countries do indeed behave differently during FIFA World Cups events. The authors find significant evidence of abnormal trading volume and, albeit weaker, abnormal returns during cups.
Originality/value
This study contributes to the literature on investor behavior, linking investor attention with salient sports events.
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John Kwaku Amoh, Abdallah Abdul-Mumuni, Emmanuel Kofi Penney, Paul Muda and Leticia Ayarna-Gagakuma
Debt sustainability and the growing level of external debt in sub-Saharan African (SSA) continue to be significant research priorities. This study aims to examine the…
Abstract
Purpose
Debt sustainability and the growing level of external debt in sub-Saharan African (SSA) continue to be significant research priorities. This study aims to examine the corruption-external debt nexus in SSA economies and whether different levels of corruption better explain this relationship.
Design/methodology/approach
The panel quantile regression approach was applied to account for the heterogeneous effect of the exogenous variables on external debts. The research covers 30 years of panel data from 30 selected SSA economies for the period spanning from 2000 to 2021.
Findings
The empirical findings of the regression analysis demonstrate the heterogeneous influences of the exogenous variables on external debt. While there was a positive impact of foreign direct investment (FDI) inflows on external debts, corruption established a negative relationship with external debt from the 10th to the 80th quantile. The findings showed a positive link between trade openness and external debt, while they also showed a negative relationship between gross fixed capital formation and external debt.
Research limitations/implications
It is implied that corruption “sands the wheels” of external debts in the selected SSA countries. Therefore, the amount of external debt that flows into SSA is inversely correlated with corruption activity.
Originality/value
To the best of the authors’ knowledge, this study is one of the first to use panel quantile regression to analyze how corruption affects debt dynamics across different levels of debt, allowing for a more nuanced understanding of how corruption affects debt dynamics. Based on the findings of this study, SSA countries should create enabling environments to attract FDI inflows and to continue to drive domestic revenue mobilization and capital so as to be less dependent on external debts.
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Nikesh Nayak, Pushpesh Pant, Sarada Prasad Sarmah and Raj Tulshan
Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of…
Abstract
Purpose
Logistics sector is recognized as one of the core enablers of the economic development of a nation. However, inefficiency in logistics operations impedes the achievement of intended targets by increasing the cost of doing business. Also, it is difficult to improve the efficiency of a country’s logistics operations without a metric for evaluating and understanding logistics capabilities and efficiency. Therefore, the present study has developed In-country Logistics Performance Index (ILP Index) to propose a benchmarking tool to measure the in-country logistics competitiveness, particularly in the setting of emerging economies, i.e. India.
Design/methodology/approach
This study has developed a unified index using principal component analysis and quintile approach. In addition, the proposed index relies on several dimensions that are developed and illustrated using quantitative secondary panel data.
Findings
The findings of this study reveal that the quality of infrastructure, economy, and telecommunications are the three most important dimensions that may significantly support the growth of the transportation and logistics sector. The results reveal that Gujarat, Tamil Nadu, and Maharashtra are the top performers whereas, Bihar, Jharkhand, and Jammu and Kashmir scores the least due to the insufficient logistics infrastructure as compared to other Indian states.
Originality/value
Given the extensive focus on international-level logistics index (like World Bank’s LPI) in the existing literature, this study intends to develop in-country logistics index to evaluate the logistics capabilities at the regional and state level. In addition, unlike prior studies, this study utilizes quantitative secondary data to eliminate cognitive and opinion bias. Moreover, this benchmarking tool would assist decision-makers in idealizing standard practices toward sustainable logistics operations. Additionally, the ILP index could serve the international investors in crucial decision-making, as it provides valuable insights into a country’s logistics readiness, influencing their investment choices and trade preferences. Finally, the proposed approach is adaptable to measuring the overall performance of any other industry/economy.
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