• Korea Trade Review
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• v.42 no.6
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• pp.111-129
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• 2017

According to the World Bank statistics, China's contribution to global economic growth during the year of 2013-2016 was estimated at 31.6 percent. This figure is even larger than 29.0 percent, the contribution by summing each contribution of the United States, EU and Japan. The Chinese commodity trade accounts for up to 11.5 percent of world trade volume. Thus, we can consider that the Chinese economy has a strong influence on the global economy. The primary purpose of this study is to analyze the contribution level of Chinese seaborne trade volume on world economy. First, this study conducted a time-lag analysis using Moran test, so we can find that China's level of contribution to global economic growth varies from time to time. The contribution of the first phase (1999-2007) was nearly three times higher than the contributions from the second phase (2008-2016), suggesting that the overall contraction of the global trade volume starting from the subprime mortgage crisis in 2008 has continued until recently and recovery has not even occurred. Second, using the econometrics model, this study conducted an regression analysis of the impact of Chinese imports and exports in chemicals, grain, steel, crude oil, and container on global economic growth. Fixed effects model with time series data has been applied to examine the effect of Chinese seaborne trade volume on global economic growth. According to the empirical analysis of this study, China's exports of steel products, exports of container, imports of containers, imports of crude oil and imports of grain have significant contributions to global economic growth. Estimates of China's exports of steel products, exports of container, imports of containers, imports of crude oil and imports of grain are 1.023, 1.020, 1.019, 1.007 and 1.006, respectively. For example, the estimated value 1.023 of China's exports of steel products means that the growth rate can be 1.023 times higher than the current world GDP growth rate if Chinese seaborne trade volume of exports of steel products increased by one unit (one million tons). This study concludes that the expansion of China's imports and exports should be realized first to increase the global GDP growth rate. The expansion of Chinese trade can lead to a simultaneous stimulus of production and consumption in China, which can even lead to global economic growth ultimately. Thus, depending on how much China's trade will be broaden in the future, the width of global economic growth can be determined.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.21-38
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• 2023

An attempt has been made in this article to discuss the fundamentals of technical analysis of the stock market. A retail investor or trader may not have the wherewithal to source that kind of information. Technical analysis requires a candlestick chart only. Most of the brokers in India provide charting solutions as well. Studying the price action of a security or commodity or Forex generally indicates a price pattern. Prices react at certain levels and widely known as support and resistance levels. Since whatever is happening with the price of the security is considered to be a part of a pattern or cycle which has already played out sometime in the past, these studies help a keen technical analyst to identify with certain probability, the future movement of the price. Study of the candlestick patterns, price action, volumes and indicators offer the opportunities to identify a high probability trade with probable target and a stop loss. A trader or investor can take high probability trade or position and control only her losses.

• Korea Trade Review
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• v.48 no.2
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• pp.27-43
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• 2023

The maritime industry is playing an increasingly vital part in global economic expansion. Specifically, the Baltic Dry Index is highly correlated with global commodity prices. Hence, the importance of BDI prediction research increases. But, since the global situation has become more volatile, it has become methodologically more difficult to predict the BDI accurately. This paper proposes an integrated machine-learning strategy for accurately forecasting BDI trends. This study combines the benefits of a convolutional neural network (CNN) and long short-term memory neural network (LSTM) for research on prediction. We collected daily BDI data for over 27 years for model fitting. The research findings indicate that CNN successfully extracts BDI data features. On this basis, LSTM predicts BDI accurately. Model R2 attains 94.7 percent. Our research offers a novel, machine-learning-integrated approach to the field of shipping economic indicators research. In addition, this study provides a foundation for risk management decision-making in the fields of shipping institutions and financial investment.

• Journal of Korean Port Research
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• v.6 no.1
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• pp.93-110
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• 1992

The most change in this century is supposed to be declination of ideology, and block of world economy. Addition to down full of cold war atmosphere around Northeast Asia, not only economic and social mood in this region is dramatically changed, but also it gave birth to the block of Northeast economy that accerlated new hub of world economy. According to dramatic change of economic surroundings the dynamic potential of growth in this region will be guided to enlarge inter-regional trade and increase volume of trade, thus suggests to grow steadily transportation. cargos in this region will have to arrange the system of delivery and inner transportation, accessary facilities, inter-regional harbors if North America and EC has connected easily. As have accerlated GATT and UR represented multilateralism and regionalism, it has regulated to increase trades of region due to relief of the trade barrier through specific areas has agreed with separately. The flow of regionalism of world economy has appeared to realize EC and NAFTA centered U.S.A, and also has presented to free trade region or one-size market agreement in Asia as APEC, EAEG in Malaysia, and etc. In defense to this block and internationalism of world economy, Pusan has to come forward to the hub of Northeast others has proposed a project to dominate the Northeast, Economy Association Agreement as Far East comprehensive development project in USSR, Hunchun development project in NK, and East Sea development project in PRC, Niigate regional development in Japan, Duman River development project in NK, and East Sea development project in Korea. As this exercise has proceed, Pusan also have arranged development strategy definitely and prepared provisions systematically. Engaging to participate center of delivery system is meant to be completed complex functions, namely the transfer storage processing & assembly function of international commodity. Pusan has ability to be terminal point of TSR. it had been connected to EC as the biggest economy block and TKR as complex transportation root to Far East, it would be the center of inground and seabase delivery terminal to Rotterdom as the biggest container pier and major piers to North-East and South East Asia. In order to provide a Role of 21 century's internationalization, Pusan has appealed to participate in management information research and development connected to Pohang-Ulsan-Changwon-Masan, and has utilized efficiently the resources such as man, material, money and information.

• The Journal of Fisheries Business Administration
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• v.41 no.2
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• pp.107-133
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• 2010

As policy makers are often concerned about dynamic effects of demand behavior and its welfare analysis by quantity changes, the paper shows how dynamic price formation systems can be built up to analyze the effect of policy options to the markets dynamically. The paper develops dynamic model of price formation for fish from the intertemporal optimization of the consumer choice problem. While the resulting model has a similar form of the error correction types of dynamic price formation system, it provides the rational demand behavior contrary to the myopic behavior of error correction demand models. The paper also develops appropriate tools of dynamic welfare analysis in quantity space using only short-run demand estimates both theoretically and empirically as a first attempt in the literature of price formation and fisheries. The empirical results of Korean fish markets show that the dynamic model and the welfare measures are reasonably plausible. The methodology and theory of this research can be applied and extended to the commodity aggregation, dynamic demand estimation, and dynamic welfare effects of regulation in the similar framework. Thus, it is hoped that this will enhance its applications to the demand-side economics.

• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.337-343
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• 2016

The core decisions of bulk shipping businesses can be summarized as the timing and the choice of period for which carrying capacity is traded. In particular, frequent decisions to trade freight either with repeated spot transactions or with a one-off long-term deal critically impact business performance. Even though a variety of freight trading strategies can be employed to facilitate the decisions, chartering practitioners have not been active in utilizing these strategies, and academic research has rarely proposed applicable solutions. The specific properties of freight as a tradable commodity are not properly reflected in existing studies, and limitations have been reported in their application to the real world. This research focused on the establishment of applicable freight trading strategies by taking into account two properties of freight: time perishability and term-dependant pricing. In addition to traditional trading strategies, artificial neural networks were applied for the first time to the test of freight trading strategies. The performances of the trading strategies were measured and compared to produce a remarkable outperformance of the ANN. This research is expected to make a significant contribution to chartering practices by enhancing the quality of chartering decisions and eventually enabling the effective management of freight rate risk. In addition to methodological expansion, the result will propose a way to approach the controversial issue of freight market efficiency.

• Korean Journal of Agricultural Science
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• v.33 no.1
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• pp.43-56
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• 2006

In this thesis we aim at analyzing international competitive power of Chinese ginseng in comparison with Korean ginseng and searching policy direction for Korea to compete Chinese ginseng industry. We summarized the research results as follows; First, we examine the structural change of ginseng industry of China. Second, we review the theories for international competitiveness and apply the method of analyzing competitiveness to ginseng industry. Third, we compared the international competitive power of the ginseng industry between China and Korea and found that Chinese ginseng, estimated by Revealed Comparative Advantage(RCA) at about 15, still remains high competitiveness in terms of cost and price but lowering price competitiveness recently. Based on the research results, we suggest export promotion strategies of the Korean ginseng as follows; 1) Korean government should enforce trade cooperation with China so as to register Korean root ginseng an importable medicine. 2) Korean ginseng producer should develop various products such as capsules, powders and etc. according to China's consumer purchasing power and taste. 3) Korean ginseng should be sold as an differentiated commodity so that it will contribute to building consumer loyalty to Korean ginseng, makes market share superior to other cheaper ginseng products in China. 4) In order to be effective brand marketing and product advertisement, there should be established reliable networks to process and distribute Korean ginseng products exclusively.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.175-186
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• 2009

Power consumed by modern computer systems, particularly servers in data centers has almost reached an unacceptable level. However, their energy consumption is often not justifiable when their utilization is considered; that is, they tend to consume more energy than needed for their computing related jobs. Task scheduling in distributed computing systems (DCSs) can play a crucial role in increasing utilization; this will lead to the reduction in energy consumption. In this paper, we address the problem of scheduling precedence-constrained parallel applications in DCSs, and present two energy- conscious scheduling algorithms. Our scheduling algorithms adopt dynamic voltage and frequency scaling (DVFS) to minimize energy consumption. DVFS, as an efficient power management technology, has been increasingly integrated into many recent commodity processors. DVFS enables these processors to operate with different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. Our algorithms effectively balance these two performance goals using a novel objective function and its variant, which take into account both goals; this claim is verified by the results obtained from our extensive comparative evaluation study.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.9-21
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• 2020

The aim of this paper is to predict the Borsa Istanbul (BIST) 30 index movements to determine the most accurate buy and sell decisions using the methods of Artificial Neural Networks (ANN) and Genetic Algorithm (GA). We combined these two methods to obtain a hybrid intelligence method, which we apply. In the financial markets, over 100 technical indicators can be used. However, several of them are preferred by analysts. In this study, we employed nine of these technical indicators. They are moving average convergence divergence (MACD), relative strength index (RSI), commodity channel index (CCI), momentum, directional movement index (DMI), stochastic oscillator, on-balance volume (OBV), average directional movement index (ADX), and simple moving averages (3-day moving average, 5-day moving average, 10-day moving average, 14-day moving average, 20-day moving average, 22-day moving average, 50-day moving average, 100-day moving average, 200-day moving average). In this regard, we combined these two techniques and obtained a hybrid intelligence method. By applying this hybrid model to each of these indicators, we forecast the movements of the Borsa Istanbul (BIST) 30 index. The experimental result indicates that our best proposed hybrid model has a successful forecast rate of 75%, which is higher than the single ANN or GA forecasting models.

• Asian Journal of Business Environment
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• v.10 no.3
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• pp.23-33
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• 2020

Purpose: The purpose of this study is for the leading sector, a pattern of shifting structure of the economic sector, and community export competitiveness on the economy Malinau Regency. Research design, data, and methodology: The type of data used is secondary data with a quantitative approach of 2009-2018. The study data used Location Quotient (LQ), Shift Share Analysis (SSA), and Revealed Comparative Advantage (RCA) analysis tools. Results: There are 6 leading sectors: agriculture; electricity, gas, and clean water; building and construction; trade, hotels, and restaurants. That has been classified has changed the economic structure of the Malinau Regency from the secondary sector to the tertiary and primary sectors in 10 years. While, community export competitiveness of the Malinau Regency through RCA Analysis, see if the export products of coal and excavation (types A, B, C) are shown to have a higher comparative advantage with comparative advantage. This shows that only a few commodities that can provide the good performance of export. Conclusions: Analysis of economic growth in the Malinau Regency after regional autonomy shows that there has been a shift in the economic structure of the economy which is dominated by the structure of the primary sector.