• 한국전자통신학회논문지
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• 제7권3호
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• pp.661-670
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• 2012

명료하면서도 수익이 나는 주식투자기법을 만들기 위해서는 투자수익 발생구조와 투자자의 상황, 그리고 주식시장의 장세가 통합적으로 고려되어야 한다. 그러나 통합적 이해 과정은 주식투자자들로 하여금 오랜 시간과 많은 비용을 요구하게 된다. 본 논문에서는 주식투자자가 자기 상황에 적합한 주식투자모델을 완성하는데 소요되는 시간과 비용을 절감할 수 있도록 주식투자 고려요소들을 분류하고, 그 요소들을 통합해 가는 과정을 로드맵화 하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• 수산경영론집
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• 제32권1호
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• pp.1-14
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• 2001

The research on the price-volume relation in the market is very important because it examines into regular phenomenon revealed by market participants including producers and middlemen. The purpose of this study is to investigate the relationship between price and trading volume in the oyster producing market. In order to accomplish the purpose of this study, the contents of empirical analysis include the time series properties of price and trading volume, the short-term and long-term relationships between price and trading volume, and the determinants of trading volume. The data used in this study correspond to daily price and trading volume covering the time period from January 1998 to April 2001. The empirical results can be summarized as follows : First, price and trading volume follow random walks and they are integrated of order 1. The first difference is necessary for satisfying the stationary conditions. Second, price and trading volume are cointegrated. This long-run relationship is stronger from trading volume to price. Third, error correction model suggests that feedback effect exists in the long-run and that price tends to lead trading volume by about five days in the short run, that is, to be required period by digging, conveying, and peeling oystershell for selling oyster. Fourth, price and price volatility is a determinant of trading volume. In particular, trading volume is a negative function of price. It is believed that the conclusion drawn from this study would provide a useful standard for the policy makers in charge of reducing the oyster price volatility risk caused by trading volume(selling quantities).

• 전기학회논문지
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• 제58권8호
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• pp.1496-1503
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• 2009

The United Nations Framework Convention on Climate Change (UNFCCC) is an international environmental treaty to stabilize greenhouse gas concentrations in the atmosphere. In order to fulfil the commitments of the countries in an economically efficient way, the UNFCCC adapted the emission trading scheme in the Kyoto Protocol. If the UNFCCC's scheme is enforced in the country, considerable changes in electric power industry are expected due to the imposed greenhouse gas emission reduction. This paper proposes a game theoretic model of the case when generation companies participate in both competitive electricity market and emission market simultaneously. The model is designed such that generation companies select strategically between power quantity and greenhouse gas reduction to maximize their profits in both markets. Demand function and Environmental Welfare of emission trading market is proposed in this model. From the simulation results using the proposed model the impact of the emission trading on generation companies seems very severe in case that the emission prices are significantly high.

• 전기학회논문지
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• 제61권7호
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• pp.957-965
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• 2012

Korean government has been preparing the introduction of Emission Trading as part of the framework convention on Climate Change as a relief of negative downstream effect over electricity industry. This paper develops a mathematical model amenable to analyzing the economic impact of introduced emission trading system on the national generation expansion planning. The developed model was also employed with a case study to verify its applicability.

• East Asian Economic Review
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• 제16권2호
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• pp.205-225
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• 2012

I use panel data of sales by the foreign subsidiaries of the U.S. MNCs to examine whether trading blocs create more or less FDI and the impacts on FDI of the extended market size created by forming blocs. By employing a region-fixed effects model, I find that countries forming trading blocs attract more FDI, particularly from non-member countries, but that FDI does not always increase with the market size of the blocs. As the market size increases, FDI increases only for large blocs. However, these findings are sensitive to model specifications. A policy implication is that a country considering forming or joining a trading bloc with a view to attract FDI may want to form a trading bloc with a country or countries with a large market size.

• Journal of applied mathematics & informatics
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• 제2권2호
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• pp.47-52
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• 1995

in this paper we reduce the trading strategy of discounted security model to trading strategy of original model

• 무역학회지
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• 제47권1호
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• pp.99-114
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• 2022

This paper analyzed the dynamic conditional correlation between the carbon emission trading prices of Korea, China, EU, New Zealand. This paper was analyzed using the daily data of carbon emission trading prices of each country from January 12, 2015 to January 13, 2021 using the DCC-GARCH model. Summarizing the research results, first, the dynamic conditional correlation between carbon emission trading prices in the EU, Korea, and China, excluding New Zealand, was strong, indicating that there was a co-movement phenomenon. Second, it was found that carbon emission trading prices in major countries have a stronger tendency to co-movement due to global shocks. Third, it appears that the dynamic conditional correlation between the carbon emission trading prices of Korea and China is gradually strengthening. This study confirmed that the co-movement between carbon emission trading prices in Korea and other countries gradually intensified as time passed. In particular, it is meaningful in suggesting the implication that the phenomenon of co-movement between carbon emission trading prices in Korea and China is gradually intensifying.

• 지능정보연구
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• 제17권3호
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• pp.187-201
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• 2011

방향성(Direction)과 변동성(Volatility)에 대한 분석은 증권투자를 위한 시장분석의 기초가 된다. 변동성분석이 옵션 투자에서 중요하다면 주식이나 주가지수선물투자는 방향성분석에 의하여 투자성과가 결정된다. 기존의 금융분석에서 기계학습을 이용한 방향성에 대한 연구는 주가나 투자위험의 예측을 중심으로 이루어졌으며, 최근에 와서야 실전투자를 위한 매매시스템(trading system) 개발에 대한 연구가 이루어지고 있다. 인공지능형 주가예측모형에서는 ANN(artificial neural networks), fuzzy system, SVM(Support Vector Machine) 등의 기법이 주로 활용되고 있다. 본 연구에서는 방향성매매를 위한 지능형 기계학습방법 중에서도 패턴인식에서 좋은 성과를 보이고 있는 은닉마코프 모형(Hidden Markov Model)을 이용한다. 실무적으로는 방향성 예측을 위해 주로 주가의 추세분석(Trend Analysis)을 활용한다. 다양한 기술적 지표를 이용한 추세분석에 기반한 시스템트레이딩(System Trading) 기법은 실전투자에서 점차 확대추세에 있다. 본 연구에서는 시스템트레이딩 기법 중 실무에서 많이 이용되는 이동평균교차전략(moving average cross)에 연속 은닉마코프모형을 적용한 지능형 매매시스템을 제안하고, 실제 주가자료를 이용한 시뮬레이션 결과를 제시한다. 세계적 선물시장으로 성장한 KOSPI200 선물시장에서 제안된 매매시스템의 장기간의 투자성과를 분석하기 위하여 지난 21년 동안의 KOSPI200 주가지수자료를 실증 분석하였다. 분석결과는 KOSPI200 주가지수선물의 방향성매매에서 제안된 CHMM기반 지능형 매매시스템이 실전에서 일반적으로 활용되는 시스템트레이딩 기법의 투자성과를 개선할 수 있음을 보여주었다.

• 대한전기학회논문지:전력기술부문A
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• 제52권10호
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• pp.616-623
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• 2003

Competition among electric generation companies is a major goal of restructuring in the electricity industry, The trading system in an electricity market has been one of the most important issues in deregulated electricity market. This paper deals with comparisons of the major two types of the trading system: compulsory pool market and bilateral contract market. The two trading systems are compared quantitatively from the viewpoint of consumer's surplus and social welfare, This paper, also, proposes a unified model of Cournot and Bertrand for analyzing the mixed trading system of pool market and bilateral contract market. Nash equilibrium of the unified model is derived by criteria for participating in bilateral contract market. Numerical results from a sample case show that a mixed trading system of pool market and price-competitive bilateral market is beneficial to consumer from the view points of consumer's surplus.