• International Commerce and Information Review
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• v.6 no.2
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• pp.65-84
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• 2004

Korean Government has provided special support to Korean export industry during past 40 years. However, due to the agreement on UR and appearance of WTO, the Government can't provide most of the subsidies which were allowed before WTO era. Hence, export insurance system became more useful tool since it's one of the few allowed subsidies under WTO. This study tries to find the impacts of export insurance systems on the exports in Korea, the United States, and Japan. Firstly, this study surveyed the export insurance systems of Korea, the United States, and Japan. Then, using a regression analysis it analysed the effects of export insurance systems upon the exports in Korea, the United States, and Japan respectively. The period of data is from 1980 to 1999. The results of the regression analysis for export insurance showed significant and positive effects of both Korean and Japanese but the United States showed insignificant and positive upon the exports.

• Management & Information Systems Review
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• v.34 no.1
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• pp.65-80
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• 2015

In previous studies concerning turnover, they argue individual stock's turnover must be identical to market portfolio's turnover under one condition where 2 funds separation theorem holds. In this kind of world, all market participants hold and trade the same portfolio and this should be only market portfolio. If one's trading portfolio's shape is different from market portfolio's, this would mean he or she has an advantage over others in information and this kind of information would be private. In accordance with this theory, we develop a metric which measures how far one's trading portfolio from market's and name it as Stock Selection by Investor(SSI). We apply this measurement to the various types of investor groups classified as individual, institutional and foreign who participate in Korea stock market. To test the validity of measure, we regress price ratio on this measurement using SUR method. As a result, individual investor group shows large number in SSI, but the coefficient in regression is not significant and economically meaningless. In case of institutional investor group, the coefficient proves to be significantly negative. We can infer from this fact that their trading is somehow far from informed trading. Stock selection activity by foreign investor groups proves to be informed trading by showing significantly positive coefficient and the magnitude of coefficient is economically meaningful, especially in sell activity.

• Management & Information Systems Review
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• v.38 no.4
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• pp.79-93
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• 2019

This study analyzed the information effect of KOSPI200 market and KOSPI200 futures market and volume synchronized probability of informed trading (VPIN). The data period is 760 days from July 8, 2015 to August 9, 2018, and the intraday trading data is used based on the trading period of the KOSPI 200 Index. The findings of the empirical analysis are as follows. First, as a result of regression analysis of the same parallax, when the level of VPIN is high, the return and volatility of KOSPI200 are high. Second, the KOSPI200 returns before and after the VPIN measurement and the return of the KOSPI200 future had a positive relationship with the VPIN. The cumulative returns of KOSPI200 futures were positive for about 15 minutes.Finally, we find that portfolios with high levels of VPIN showed high KOSPI200 and KOSPI200 futures return. These results confirmed the applicability of VPIN as a trading strategy index. The above results suggest that KOSPI200 and KOSPI200 futures markets will be able to explore volatility and price changes, and also be useful indicators of financial market risk.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.348-353
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• 2013

Recently, control theory including stochastic optimal control and various machine-learning-based artificial intelligence methods have become major tools in the field of financial engineering. In this paper, we briefly review some recent papers utilizing stochastic optimal control theory in the fields of the pair trading for mean-reverting markets and the trend-following strategy, and consider a couple of strategies utilizing both stochastic optimal control theory and machine learning methods to acquire more flexible and accessible tools. Illustrative simulations show that the considered strategies can yield encouraging results when applied to a set of real financial market data.

• Proceedings of the IEEK Conference
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• summer
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• pp.387-390
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• 2004

In this paper, we design and implement practical application service using VoiceXML. And we suggest new solutions of problems can be occurred when implementing a new systems using VoiceXML, based on the fact. Up to now, speech related services were developed using API (Application Program Interface) and programming languages, which methods depend on system architectures. It thus appears that reuse of contents and resource was very difficult. To solve these problems, nowadays, companies develop their applications using VoiceXML. Advantages of using VoiceXML when developing services are as follows. First, we can use web developing technologies and technologies for transmitting web contents. And, we can save labors for low level programming like C language or Assembler language. And we can save labors for managing resources, too. As the result of these advantages, we can reduce developing hours of applications services and we can solve problem of compatibility between systems. But, there's poor grip of actual problems can be occurred when implementing their own services using VoiceXML. To overcome these problems, we implemented interactive stock trading system using VoiceXML and concentrated our effort to find out problems when using VoiceXML. And then, we proposed solutions to these problems and analyzed strong points and weak points of suggested system.

• Journal of Environmental Policy
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• v.9 no.4
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• pp.77-102
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• 2010

The purpose of this paper is to analyze the Japanese emission trading system and climate change policy thereby contributing to the instituting of similar systems that will be viable for the Korean context. In applying such analyses, it is important to include a careful consideration of cost sharing between stakeholders and firms, an enhancement of the trust worthiness of data concerning greenhouse gases, and an examination of related infrastructure such as emissions authentication agencies and their development. Moreover, it is important to minimize the outflow of domestic resources such as offset credit, green electricity certification system, and ecopoint, making compatible economic growth and carbon reduction thereby encouraging the production and dissemination of 'Environmental Value' as well as connecting 'Environmental Value' to a emission trading system.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.209-215
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• 2018

The level of cultural enjoyment in Korea has improved every year, but the culture that the general public possesses artworks has not developed so much. Most artwork trading systems, from traditional ones to the latest blockchain-based ones, are designed for expensive artwork trading and are hardly accessible to the general public. In this paper, we propose a blockchain-based artwork trading system that can improve the culture of the general public's art collection and contribute to the popularization of fine art. The proposed system consists of three interacted blockchains for identification, artwork registration and smart contract. The proposed system utilizes the advantages of the blockchain system for users to provide trust to each other, and introduces the concept of art notebook for artists to build trust in their own artwork. Since the proposed system builds a trust system through participants rather than experts or external organizations, it can reduce the cost of trading and deal with artworks that can be owned by the general public.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.152-159
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• 2023

This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies - Bitcoin, Ethereum, Litecoin, and EOS - and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies - AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet - representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning-based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1610-1616
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• 2013

Recently, district heating and cooling (DHC) systems based on combined cycle generation (CCG) providers are increasing in Korea. Since characteristics of combined heat and power (CHP) generators and heat demands of providers, heat trading between DHC providers based on the economic viewpoint is required; the heat trading has been doing. In this paper, a mathematical model for optimal operation based on heat trading between DHC providers is proposed. Especially, start-up characteristic of CCG is included. The operation model is established by mixed integer linear programming (MILP).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.123-129
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• 2013

The aim of this study is to design an intelligent pattern-based real-time trading system (PRTS) using rough set analysis of technical indicators, dynamic time warping (DTW), and genetic algorithm in stock futures market. Rough set is well known as a data-mining tool for extracting trading rules from huge data sets such as real-time data sets, and a technical indicator is used for the construction of the data sets. To measure similarity of patterns, DTW is used over a given period. Through an empirical study, we identify the ideal performances that were profitable in various market conditions.