• International Area Studies Review
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• v.15 no.3
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• pp.215-237
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• 2011

The paper is basically designed to reveal substitutability or complementary nature of export and import among Korea, China, and Japan by employing unit root test, cointegration technique, and vector error correction model(VECM). Empirical evidences are shown that the trading among these countries has been dominated by a complementary nature in the short run which enables it to promote trading in those countries. In the long run, however, the substitutability nature effects strongly to the trading among Korea, China, and Japan. To this end, it could be tentatively concluded that market-oriented trading policies are more effective to stimulate the export and import in those countries in the short run, while a trading policy has to be selectively implemented by the substitutability nature in the long run basis. For instance, a stability policy for exchange rates and various commercial policies could be set for a short term target. Whereas, the substitutability nature should be counted in building up a new industrial structure or in implementing FTA agreement among Korea, China, and Japan.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.293-306
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• 2003

In recent years, distributed computing environments have been radically changing to a structure of global, heterogeneous, federative and wide-area systems. This structure's environments consist of a let of objects which are implemented on telecommunication network to provide a wide range of services. Furthermore, all of objects existing on the earth have the duplicated characteristics according to how to categorize their own names or properties. But, the existing naming or trading mechanism has not supported the binding services of duplicated objects, because of deficiency of independent location service. Also, if the duplicated objects which is existing on different nodes provide the same service, it is possible to distribute the client requests considering each system's load. For this reason, we designed and implemented a new model that can not only support the location management of replication objects, but also provide the dynamic binding service of objects located in a system with minimum overload for maintaining load balancing among nodes in wide-area object computing environments. Our model is functionally divided into two parts; one part is to obtain an unique object handle of replicated objects with same property as a naming and trading service, and the other is to search one or more contact addresses by a location service using a given object handle. From a given model mentioned above, we present the procedures for the integrated binding mechanism in design phase, that is, Naming/Trading Service and Location Service. And then, we described in details the architecture of components for Integrated Binding Service implemented. Finally, we showed our implement environment and executing result of our model.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.939-959
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• 2006

This paper studies the introduction of flood quota system for efficient flood prevention. In the present system where local governments decide its flood prevention independently, the optimal flood prevention in a river basin can not be achieved. Thus, the flood quota system is necessary. In deciding the flood quota for each local government in a river basin, its social and economic characteristics as well as geographical feature of the area should be considered. In order to promote the cooperation among local governments in a river basin, the flood quota is necessary to be accompanied with the trading system of the quota.

• The Korea Journal of Herbology
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• v.26 no.4
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• pp.163-168
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• 2011

Objective : The purpose of this study is to determine the origin of Aquilariae Lignum. Method : Firstly identify the production areas of Aquilariae Lignum and its trading status with China in Chinese history through Chinese historical books such as Twenty-Five Histories(二十五史) and the records of the Chosun Dynasty and then, compare the distribution of the genus Aquilaria in the concerned areas. Result : Since the records in the NanfangCaomuZhuang(南方草木狀) written in 304 saying that Aquilariae Lignum was produced in Vietnam and had white flowers, Vietnam had led production and trading of Aquilariae Lignum until Qing Dynasty(淸代). Even though Thailand traded Aquilariae Lignum during Qing Dynasty, however, the volume was at a low level. Aquilariae Lignum from southern Thailand, Malaysia and Indonesia was rated as low quality and low-priced because of its fishy smell and strong flavor. Conclusion : These results show that the origin of Aquilariae Lignum comes from Vietnam and this species is distinguished from the ones of Indodesia or Malaysia.

• The Research Journal of the Costume Culture
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• v.9 no.6
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• pp.855-871
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• 2001

The purposes of this study were to compare the marketing compose elements of Apgujung and Shinchon branch of Hyundai Department Store and to suggest desirable fashion marketing strategies for other Department Stores and retailing stores. The results were as follows: Two kinds of factor were classified form this study; one was Hardware elements such as Trading Area Site, Store Composition, Scale, and Subsidiary facilities etc., another was Software elements like Store Concept, Image, and Merchandising and so on. The followings were suggested from Hardware elements; 1) Trading Area could be classified'local type'and 'spread type'. 2) Each branch was differentiated from store formation of conventional department store which had food department in basement. There were the most powerful women's fashion brand to lead costumers in second basement. 3) In accordance with the position of subsidiary facilities of Hyundai Department Store,'Water Jet Effect'strategy and'Show Effect'strategy could be usefully applied for other Department Stores and retailing stores. 4) The strategy of approaching easily to the target floor which was located in lower floor, could be applied to various retailing stores. The followings were suggested from Software elements; 1) Stores management coping with poles-apart in costumer could be needed to other Department Store and retailing stores. 2) It also could be needed to find and maintain effective ratio between common brand and differentiated brands in the other Department Stores.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.179-206
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• 2011

Masan Port, which is a main entrance to Korea, has undergone the tough time these days. Many problems are mainly due to the deterioration of harbor facilities, the shortage of waterfront area and the decrease of the trading volumes. Especially the trading volumes are seriously affected by the Busan New Port, which was not only very close to the Masan Port but constructed in a large scale. For the Masan Port to develop continuously, therefore, it is vital to modernize harbor facilities, redevelop the old harbor, expand its waterfront, construct green port and develop harbor for sightseeing. At the same time, Masan port should be ready to develop a higher value added port. To vitalize Masan port's economy, we have to push forward a differentiation strategy that makes Masan port specialized harbor for distributing goods like hard and heavy cargo.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• International Commerce and Information Review
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• v.8 no.2
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• pp.119-139
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• 2006

The purpose of this research is to analyze four models of global e-trade implementation which was suggested at the advance research of implementation global e-Trade with major trading countries. The main outcomes of this empirical study are as follows. For realizing global e-trade of G-Networking model country we have to implement e-trade in the field of "import & logistics". And for realizing global e-trade of P-Networking model country, it need to try in "settlement & clearance". Furthermore, for realizing global e-Trade of G-Penetration model country, we have known that the field of "import & logistics" would be implemented. Finally for realizing global e-Trade of P-Penetration model country, "settlement & clearance" could be implemented. Also, this study suggests that we have to do negotiation with China and Japan at first, and to try the area of settlement & clearance to implement the global e-Trade with Korea's 10 major trading countries.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.183-193
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• 2006

The purpose of this study is to examine differences in college students' spatial behavior and time for purchasing (weekdays or weekends) according to trading areas they use to purchase casual wears and formal wears. An empirical research developed a questionnaire as a measuring tool to conduct a main survey. McNemar test were carried out by using the SPSS to test statistical differences in spatial buying behaviors between weekdays and weekends. ArcGIS 9.1 and ArcView GIS 3.2a program were applied to visualize the results adopting a spider display technique to understand students clothing buying behaviors. This study obtained the result of that there were differences in college students' selecting a trading area according to the time for purchasing(weekdays or weekends) clothing wears. This study implies that understanding individual clothing spatial behaviors help to set up the strategy of trade area as well as store for marketers related to the fashion industry.