Position In Trade Research Articles

The position of China in trade in services within the European Union

Research background: In recent decades, services in international trade have been growing steadily in importance, and there has been strong growth in China?s trade in services as a result of the ?opening up? policy. China has become the European Union?s second biggest trading partner in services with the European Union (EU), being China?s largest trading partner. The EU is one of the addressees of the Chinese Belt and Road Initiative, which creates opportunities and threads to the European Internal Market in services. Purpose of the article: The aim of this paper is to contribute to the literature and fulfil the research gap on the position of China in intra-EU trade in services. Methods: We identified the most important types of services offered by China to purchasers from the EU countries. By using the Revealed Symmetric Comparative Advantage (RSCA) and trade balance (LFI) indices, we classified the Chinese exports to the EU Internal Market by types of services and by their trade position. Findings & value added: We found out that China might be perceived as a strong competitor for intra-EU trade in selected services, especially those concerning low-end service tasks, that use relatively low-skilled labour and are less knowledge- and capital-intensive. However, China?s attitude is changing towards more sophisticated services for example R&D. It creates a need for a new approach to the EU economic policies (in terms of both protectionism and interventionism) in trade relations in services with China.

DETERMINANTS OF CAPITAL STRUCTURE: AN EMPIRICAL STUDY OF LISTED TEXTILE COMPANIES IN INDIA

Purpose --This paper aims to empirically investigate the capital structure determinants of Textile Industries of India listed on NSE (National Stock Exchange) during the Year of 2014-18 with a particular focus on short-term debt Ratio and long-term debt Ratio. Design/methodology/approach –Fixed affect panel data regression were used to analyze a sample of 18 Indian Textile Companies listed on NSE (National Stock Exchange) for which complete financial information was available for a Five year period, i.e. the 2014-2018. Findings – The results indicate that there is a significant and negative relationship between profitability, Short-Term, and Long-Term Debt Ratio. Moreover, The Short-Term Debt ratio is significant with Tangibility of the firm and Net Commercial Trade Position, Where Tangibility of the firm is negatively related and Net Commercial Trade Position is positively related. Short-Term Debt Ratio is not significant with Current ratio, Net Commercial Trade Position, Number of Non-Executive Members, Number of Executive Members Number of Audit Meetings, Number of Board Meetings and Quick Ratio, These all variable are having positively related except Quick Ratio. Whether Quick Ratio is negatively related. Practical implications – As debt policy influences Current Ratio, Net commercial Trade Position, Non-debt Tax Shield, Number of Non-Executive Members, Number of Executive Members, Number of Audit Meetings, Number of Board Meeting, Quick Ratio, Return on Assets, Tangibility of Firm financial institutions and managers may benefit from studies considering a relatively large number of capital structure determinants, several of which are linked to short- and long-term debt in various ways.

Trading Behavior in Agricultural Commodity Futures around the 52-Week High

Utilizing the Commodity Futures Trading Commission’s Commitment of Traders report, we examine the behavior of traders in three large agricultural futures markets (corn, soybean, and wheat) when prices are at a key technical trading level—the 52-week high (the highest price during the past year). Our empirical results confirm that, consistent with hedging behavior, commercial traders tend to be negative feedback traders, while non-commercial traders tend to be momentum traders. In both cases, there is a moderating effect when the market is at the 52-week high. For non-commercial traders, this effect is concentrated in short positions. Although we find no evidence of a broad market timing ability from any trader type, trader positions appear to be more informative when the market is at the 52-week high. Our results have implications for traders attempting to time market entry.

Chekists Penetrate the Transition Economy: The KGB’s Self-Reforms during Perestroika

ABSTRACT This article explores the KGB’s penetration of the transition economy by examining its self-reforms and collective practices during perestroika. A formerly classified KGB in-house journal demonstrates how Chekists adapted their work to economic liberalization. The KGB strengthened counterintelligence measures for Soviet–Western joint ventures by infiltrating active reserve officers and establishing intimate relationships with new Soviet businesses by supplying them with commercial secrets stolen from Western partners. Business and foreign trade positions became new covers for Lubyanka. These institutional arrangements, rather than the individual entrepreneurship of Chekists, paved the way for their prominence in the post-Soviet Russian economy.

Do the carry trades respond to geopolitical risks? Evidence from BRICS countries

This paper aims to analyze the implications of geopolitical risks on the return and volatility of carry trade transactions in the context of BRICS countries for the period 2006–2020. Fixed effects regressions considering the sample countries as a single portfolio document that geopolitical risks are correlated with volatility, while the results are inconclusive for returns. The non-parametric time-varying coefficients panel data estimations further indicate that the effect of geopolitical risks on carry trade volatility is amplified during the Global Financial Crisis and the post-2016 episode. Moving to the disaggregated data, the time-varying robust Granger causality test of Rossi and Wang (2019) show that geopolitical risks have a significant in-sample predictive power for both carry trade return and volatility during a myriad of sub-periods, which can not be captured by standard constant parameter techniques in the presence of instabilities. Overall, our empirical results suggest that the exposure to geopolitical risks should be taken into account by global investors for risk diversification purposes when entering carry trade positions in BRICS countries.

Implications of clean energy, oil and emissions pricing for the GCC energy sector stock

In this study, we analyse the implications of clean energy, oil and emission prices for the energy sector stock in the GCC region. In so doing, we estimate one-day-ahead value at risk (VaR) and the expected shortfall (ES) for Saudi, Abu Dhabi and Kuwaiti energy stock prices over short and long trading positions using three different long memory Autoregressive conditional heteroskedasticity (ARCH)/ Generalized(G)- ARCH models: fractionally integrated asymmetric power ARCH (FIAPARCH), fractionally integrated generalized autoregressive conditional heteroscedastic (FIGARCH) and fractionally integrated hyperbolic generalized autoregressive conditional heteroskedasticity (HYGARCH). In the GARCH model, we employ the three global energy indexes: clean energy production, crude oil and CO2 emission prices as exogenous regressors to consider their impacts on the GCC energy volatilities. Our findings indicate the presence of asymmetry, fat-tails and long memory in the GCC energy price volatilities, and that the three exogenous regressors do not play a significant role in the GCC daily returns volatility. The FIAPARCH produces the most accurate VaR and the expected shortfall for Saudi and Kuwait energy sectors, while HYGARCH performs better for the Abu Dhabi energy index. Our study has profound implications for the clean energy policy, emission pricing and investment strategies entailing energy stock.

Investor behavior and cryptocurrency market bubbles during the COVID-19 pandemic

PurposeCryptocurrencies lack fundamental values and are often subject to behavioral bias leading to market bubbles. This study aims to investigate the contribution of the coronavirus pandemic to the creation of market bubbles.Design/methodology/approachThis study identifies four major cryptocurrency market bubbles by using the Phillips et al. (2016) (hereafter PSY) test. Subsequently, the co-movements of the coronavirus proxies with PSY measurement using the wavelet approach were studied.FindingsShort-lived bubbles are detected at the beginning of the studied period, and more extended bubble periods are identified at the end. Besides, the empirical results show evidence of significant negative co-movement between each pandemic proxy and each cryptocurrency bubble measurement.Research limitations/implicationsGiven the complex financial dynamics of the cryptocurrency markets due to some behavioral biases in some circumstances, investors can benefit from the date stamping of the bubbles bursting to make the best trading positions. In the same way, governments could support the healthy development of cryptocurrencies by preventing bubbles during such pandemics.Originality/valueThe financial bubble is commonly attributed to a change in investor behavior. Because traders and investors think they can resell the asset at a higher price in the future. This study explored the contribution of the COVID-19 pandemic in the creation of these bubbles by date stamping their occurrence and explosive periods. To the best of the authors’ knowledge, this study is the first attempt that explores the contribution of the COVID-19 pandemic to the creation of bubbles caused by a change in the investors’ behavior.

Global Trade Pattern of Traditional Chinese Medicines and China's Trade Position.

To depict the evolution of the global trade of traditional Chinese medicine (TCM) products, this article analyzes the 2001–2020 trade data of TCM products in the World Bank and United Nations Commodity Trade Statistics Database to discern the spatial-temporal evolution characteristics of global and China's trade patterns of TCM products from 2001 to 2020 and thereby assess the changes in the global trade of TCM products and in the positions of various countries or regions in the global trade of TCM products. Research findings are as follows: First, on the whole, the total trade volume of TCM products and the number of participating economies and trade connections are on the rise. Second, in terms of topological structure, with higher network density and rising transmission efficiency, the global trade network of TCM products has typical small-world and scale-free network characteristics and has begun to be controlled by a few countries. Judging from the co-opetition between major trading countries, there are more diversified sources of imports for major trading countries, and there is competition between supplying countries. Third, For China, the trade volume of TCM products between China and various countries worldwide has grown rapidly and exhibits a trend of continuous increase followed by decline. China has established extensive trade partnerships and its position in the global trade network of TCM products has been continuously improved. China's participation has contributed to a closer connection among trading entities, but its network heterogeneity remains to be further improved. From the perspective of trade interdependence, the number of countries or regions maintaining high interdependence with China has been gradually increasing, and most of them are European and American countries, Japan, and Southeast Asian countries. The number of countries or regions maintaining low interdependence with China has gradually decreased, and countries or regions that are completely one-way dependent on China are nonexistent.

Leveraging the momentum effect in machine learning-based cryptocurrency trading

Cryptocurrency trading has become more and more popular among private investors. According to recent studies, the momentum effect influences the underlying market. Quantitative trading systems can leverage momentum indicators to open and close trading positions. However, existing approaches that exploit the momentum effect in cryptocurrency trading do not rely on machine learning. Since these systems are based on human generated rules they are not suited to highly volatile market conditions, which are quite common in cryptocurrency markets. This paper proposes to leverage machine learning approaches to automatically detect the momentum effect in cryptocurrency market data. For each cryptocurrency it estimates the likelihood of being affected by the momentum effect on the next trading day as well as the momentum direction. A backtesting session, performed on three very popular cryptocurrencies, shows that the machine learning models are able to predict, to a good approximation, short-term price volatility thus reducing the number of false trading signals and increasing the return on investments compared to state-of-the-art approaches.

Corruption, institutional quality, and offshoring: How do they affect comparative advantage, inter‐country wage inequality, and economic growth?

AbstractWe analyze whether, due to the effects on corruption, institutional quality, and offshoring affect comparative advantage, income inequality between countries and economic growth. We start by developing a theoretical model of endogenous R&D growth for an integrated area with two representative countries that differ in the economic development level. Then, we estimate an econometric model with panel data, considering combinations of 14 different countries, between 2000 and 2017. We show that an improvement in offshoring increases the comparative advantage of developing‐South countries and decreases the wage gap between developed‐North and South countries. In turn, an improvement in institutional quality increases the comparative advantage of the North and widens the wage gap between countries. Whatever the improvement, there is always an increase in the world economic growth rate. Thus, all countries can improve their position in international trade, labor market, and economic growth through the conduction of policies that reduce corruption and, respectively, increase the quality of institutions and the attractiveness for the offshoring.

What drives risk in China’s soybean futures market? Evidence from a flexible GARCH-MIDAS model

ABSTRACT Modeling futures market risk simultaneously influenced by macro low-frequency information and daily risk factors is a valuable challenge. We propose a new general framework for it based on the flexible GARCH-MIDAS model. It uses a skewed t distribution to describe the asymmetry of long and short trading positions, allows for a different number of trading days per month, and can identify the optimal combination of risky factors. We also derive its impact response function on how low-frequency factors directly influence the high-frequency futures market risk. Through an exhaustive empirical analysis of the Chinese soybean futures market, we not only find its excellent out-of-sample market risk forecasting performance but also offer systematic recommendations for improving risk management.

Carbon inequality in global trade: Evidence from the mismatch between embodied carbon emissions and value added

Global trade not only brings about the exchange of goods and services, but also stimulates the transfer of carbon emissions. Given different economic development stages and industrial structures, global carbon inequality occurs due to the mismatch between trade-related carbon emissions and value added. Combining the multi-regional input-output model and regional environmental index (REI), this paper constructs an integrated research framework to trace the embodied carbon emissions and value-added among six regions from 2010 to 2015 to shed light on global carbon inequality from a multi-regional perspective. The results indicate that major carbon exporters are placed in inferior positions in global trade, rendering them victims of carbon inequality. The EU, Japan and the USA have been favored by global trade from both economic and environmental perspectives, and the advantaged position of the EU has improved whereas the positions of Japan and the USA have slightly decreased. For disadvantage regions, China and ASEAN10 has improved their situations, yet the inequality suffered by the RoW148 has deteriorated. Adjusting the export structure from primary to advanced products is an effective measure to mitigate global carbon inequality. Our major implications help strike thinking on the rationality of global trade and offer integral solutions towards sustainable development.

The Situation of Regional Concentration of Tomato Foreign Trade in Turkey

World trade in agricultural products, tends to increase. Turkey is among the countries in foreign trade advantages with its agricultural potential. As one of the most important tomato producer countries, monitoring of developments in the world tomatoes trade is extremely important for Turkey. The aim of this study was to evaluate Turkey’s position in world tomato trade. The developments of tomato foreign trade between Turkey and importer countries were analysed using Trade Intensity Analysis Method. Turkey supplied %75 of total tomato exports to Russia. Ukraine, Saudi Arabia, Iraq, Syria and Israel are important markets for tomato export. The epidemic (Covid-19 virus) has also been reflected in the international trade balances in tomato production. Giving importance to Turkey’s political relations and to boost its exports by providing market diversity, it is important for the sustainability of tomato exports. In this context, market researches should be conducted specially to find and entrance into new markets. Besides the fresh tomato, the activities for the export of tomato paste and canned tomato should be implemented.

Globalization and the oil market: An overview on considering petroleum as a trade commodity

Today, the process of globalization and globalization of the economy is one of the most important issues in the world. In this process, the manner and rules of trade of some goods with a strategic international trade position are more important. Energy carriers, especially crude oil, are among these commodities that are considered strategic commodities in foreign trade. The inclusion of crude oil among the World Trade Organization commodities has raised various issues. Since the oil price in the market is affected by factors such as psychological factors and supply and demand, the inclusion of oil in the World Trade Organization will, directly and indirectly, affect these factors. Principles such as national behavior can directly affect crude oil demand. Also, the principle of quantitative restriction can directly affect the supply of crude oil. Besides, agreements such as the General Tariff and Trade Agreement, the Service Trade Agreement, and the Technical Barriers to Trade Agreement can influence engineering service providers' roles at various stages and move them toward competition.

A study of Economic complexity of Indian Exports Vis-à-vis China: A Review Paper based on Atlas of Economic Complexity theory

As the world tries to grapple with the aftermath of the COVID-19 pandemic, there are concerns about the revivals of economies across the globe. The world is also trying to make sense of global restructuring trade, which is expected in the post-COVID-19 world. This paper attempts to analyze the emerging trade scenario between India and China. Atlas of Economic Complexity theory (ACE) by Ricardo Hausmann, Cesar A. Hidalgo has been taken as a base for this research. This study propagates that the countries with products that require more know-how have more potential to grow. Taking the Atlas map giving details of Indian exports as a base, the researchers have compared the data from the last two years. The purpose is to identify whether the complexity of Indian exports is increasing or not. A particular case study has been done on Indian exports to China. There has been little progress in this field as India is exporting more complex products slightly to China. There is an urgent need to formulate a strategy to enhance the complexity of Indian exports. The policymakers need to give impetus to the industries which have a cross-cultural demand in China and leverage this opportunity. This will open the path for consolidating India's position in the global trade as well as improving its strategic position vis-a-vis China.

Impacts of the belt and road initiative on China’s bilateral trade

This study contributes to the existing literature by empirically analyzing the impacts of the Belt and Road Initiative (BRI) on China’s bilateral trade. Applying an augmented gravity model to trade flows between China and its 190 trading partners, of which 140 countries have signed the BRI agreements sequentially, during the period 2012–2020, we find that: (1) The BRI can significantly increase the extensive and intensive margins of China’s exports and imports, while reducing China’s trade surplus. (2) The BRI stimulates trade quantities, while lowering unit values of traded products. (3) These effects vary by income level and product category. In short, the BRI has been quite effective in strengthening China’s global trade position and it is also beneficial to both trading parities. Policy implications are proposed accordingly.

Czech Comparative Advantage in Agricultural Trade with Regard to EU-27: Main Developmental Trends and Peculiarities

The paper, based on RCA, LFI and GL indices, and logistic regression analysis, allowed us to track the dynamics of the comparative advantage/disadvantage of the Czech Republic in individual commodity aggregates in relation to individual EU partners, and to comprehend the role of the main production factors. The only production factor with a statistically significant effect is capital. Trade with countries richly endowed with agricultural land and capital, in most cases, appeared not favorable for the Czech Republic in terms of having a comparative advantage over them, if measured with LFI index. The values of the GL index disclosed that trade with these countries is mostly of an inter-industry character. The analysis revealed the following top-3 mostly competitive Czech aggregates: S3-08 (animal feed stuff), S3-06 (sugar and sugar preparations), along with S3-04 (cereals and cereal preparations). Some aggregates appeared to not have any comparative advantage: S3-01 (meat, meat preparations), S3-05 (vegetables and fruits), and S3-41 (animal oils and fats). Speaking of developmental trends, from 2000 to 2019 the Czech Republic has managed to improve its position in agri-food trade within the EU-27 by 43.81% if measured with LFI, and by 51.63% if measured with RCA. These positive changes also appeared to be statistically significant.

Does previous carry trade position affect following investors' decision-making and carry returns?

This paper builds a two-country model to investigate the relationship between carry trade activity and carry trade return. The two-country model finds that previous carry trade position could positively affect current carry return and current carry trade scale. This positive relationship fosters the asset bubble of high-yielding currency, and the potential for huge losses could also make the carry trader unwind the carry trade position. Based on carry trade panel data from 22 countries and regions, this paper studies the relationship empirically through a panel vector autoregression model. The empirical results find that carry trade position has a significant positive relationship with carry return and carry trade position in following periods. Also, the empirical results suggest that foreign exchange risk could negatively affect carry return and carry trade position. Once the foreign exchange risk increases, carry traders choose smaller carry trade positions.

Predicting Security Returns in the Presence of Upper Price Limits

The objective of this paper is to develop a Bayesian forecasting model of security returns in a security market in which daily trading is subject to price limits. Traders and investors are assumed to be Bayesian decision makers under uncertainty, in the sense that they combine their a-priori information about the security returns with realized stock returns, to form the posterior and predictive distributions, on which trading decisions would be made. It allows traders and investors to adjust their long/short trading positions while considering the presence of upper price limits. In our model, security returns are assumed normally distributed, with an unknown mean and a known variance. Our traders and investors apply Bayes’ rule to update their prior information to derive the security returns’ predictive distribution. Our major contribution is the derivation of the stock returns’ predictive distribution, which is analytically quite complex. To illustrate the usefulness of our forecasting model, we provide five numerical examples of the predictive distributions, in which we alter one of the parameters, ceteris paribus, and demonstrate its impact on the predictions. This would allow traders and investors to upgrade their trading positions in the presence of an upper price limits.

Monetary liberalization in Chile, Mexico and Brazil

The article presents an analysis of the development and current state of monetary and financial regulation in the context of the economic policies of Chile, Mexico and Brazil. The article is focused at the processes of liberalization of foreign exchange regulation in order to create more favorable conditions for the development of foreign trade, support for exporters and building a reliable prudential system. It is concluded that in the reviewed countries, the policy regarding the lifting of restrictions in order to support and develop export potential had been carried out consistently. The successful experience of these countries in the field of monetary and financial regulation deserves attention, as it shows their ability to maintain financial and economic stability, withstand external shocks and strengthen their positions in world trade.