• Environmental and Resource Economics Review
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• v.25 no.3
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• pp.377-401
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• 2016

This study analyzes how much cost the power generation and energy sector in South Korea have to bear due to the introduction of emissions trading scheme during 2016 - 2017. To this end, the data on the seventh basic plan for long-term electricity supply and demand is applied to the electricity market simulation model called M-Core, and then the model forecasts carbon dioxide emissions to compare with the free emission allowances in the first national emissions permit allocation plan. The main results are as follows. Carbon dioxide emissions are estimated to be less in 2016 but more than the free emission allowances in 2017. When the price of the allowances is changed from \10,000/ton to \20,000/ton, the cost of purchasing the allowances is ranged from \70 billion to \140 billion. Under the assumption that CO2 cost is incorporated into the variable cost, a reversal of merit order between coal and LNG generation takes place when the price of the allowances exceeds \80,000/ton.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.171-181
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• 2022

The real estate price index plays key roles as quantitative data in real estate market analysis. International organizations including OECD publish the real estate price indexes by country, and the Korea Real Estate Board announces metropolitan-level and municipal-level indexes. However, when the index is set on the smaller spatial unit level than metropolitan and municipal-level, problems occur: missing values. As the spatial scope is narrowed down, there are cases where there are few or no transactions depending on the unit period, which lead index calculation difficult or even impossible. This study suggests a supervised learning-based machine learning model to compensate for missing values that may occur due to no transaction in a specific range and period. The models proposed in our research verify the accuracy of predicting the existing values and missing values.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.140-148
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• 2002

컴퓨터를 통해 편리한 생활을 추구해온 인간들은 전자상거래 분야에서도 이러한 욕구를 충족시키기 위해 자동협상이라는 기능을 요구하게 되었다. 지능형 에이전트를 이용한 자동협상은 인간의 거래협상 업무의 부담을 많은 부분을 덜어주고 있어 자동협상 에이전트에 관한 연구들이 활성화되고 있다 소비자간 전자상거래에서는 다수의 자동협상 에이전트 연구들이 경매시장에서의 자동협상에 초점을 맞추고 있는데 반해, 가격 이외의 여러 거래속성을 갖는 상품에 대한 제안기반 협상시장에서의 자동협상 에이전트에 관한 연구들이 최근에 활발히 이루어지고 있다. 본 연구에서는 소비자간 전자상거래에서 거래속성의 변화에 따라 개인의 효용가치의 차이를 이용한 다속성 상품의 제안기반 협상시장이 가져야할 특성에 대해 연구하고, 이를 기반으로 자동 거래협상을 수행에 필요한 거래속성 변화에 따른 소비자 개인의 선호체계를 표현하기 위한 방법을 개발하였다. 그리고 이러한 자동 거래협상을 공정하게 수행하기 위해 협상시장이 가져야할 특징과 프로토콜을 제안하고 시장운영 에이전트 시스템의 구조를 설계하였다. 마지막으로 이러한 분산형 시장구조를 갖는 제안기반의 협상시장에 참여하는 사용자 에이전트 시스템이 최적의 거래상대와 최적의 거래안을 찾기 위한 탐색방법을 구체적으로 개발하였다. 본 연구의 결과를 통하여 소비자간 전자상거래에서 구매자 뿐만 아니라 판매자도 협상결과에 따른 거래로 얻어지는 자신의 효용을 극대화할 수 있는 공정한 협상시장을 운영할 수 있을 뿐만 아니라 사용자들도 손쉽게 자신의 협상 선호체계를 쉽게 표현하고, 표현된 선호체계를 반영한 자동 거래협상을 수행할 수 있을 것 이다. 기존의 UN/EDIFACT표준을 사용하고 있는 EDI환경과 기존 VAN 방식의 EDI 중계 시스템과 연동되며, 향후 관세청의 XML/EDI 표준 시행을 미리 대비하는 선도연구로서 자리매김이 된다. 본 연구에서는 개발된 XML/EDI 통관시스템은 향후, 서비스의 최대 걸림돌이 되어왔던 값비싼 EDI 사용료의 부담에서 벗어날 수 있게 할 것이며, 저렴한 EDI구축/운영 비용으로 전자문서교환의 활성화와 XML이 인터넷 기반의 문서유통 표준으로 자리매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without

• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.569-593
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• 2005

This study tests for the law of one price and Grander Causality between the EU ETS and Nord Pool $CO_2$ allowance prices. The Johansen cointegration test shows that there exists a long run equilibrium between EU ETS and Nord Pool prices and support the law of one price. The Granger casuality test suggests that the EU ETS leads Nord Pool for all vintages traded. The test results imply that the EU ETS can be regarded as the representative carbon market in the EU where many exchanges just started competing for the newly rising market for carbon.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.68-70
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• 2021

인터넷 가상화폐 거래소에 게시되는 공시를 분석하여 향후 게시된 공시가 가상화폐 가격에 줄 영향을 예측해보고자 한다. 과거 게시된 공시 데이터를 바탕으로 딥러닝을 이용해 영향치를 도출해낸다. 프로그램은 Python 언어로 작성하였으며, django 웹 프레임워크를 이용하여 결과치를 보여줄 수 있는 웹 사이트를 구현하였다. 또한 공시를 통합한 데이터를 이용하여 새로 게시되는 공시가 해당 가상화폐의 가격에 줄 예측치를 분석하였으며 해당 공시가 가상화폐의 가격에 어떻게 영향을 줄지 쉽게 판단할 수 없는 사용자들에게 도움을 줄 수 있을 것이다.

• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.57-70
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• 1997

주식 시장을 예측하는 문제는 금융 분야에서 중요한 관심이 되어왔다. 주식 시세는 시장 환경의 변화에 따라 급격한 변화를 갖는다. 따라서 주식 투자로부터 이윤을 창출하기 위해서 주식을 사고 파는 시점을 결정하는 문제는 중요하다. 본 연구에서는 주시 매매 타이밍을 예측하기 위해서 캔들스틱 차트(Candlesticks chart)분석을 이용한 전문가 시스템(Expert System)으로서 '차트 해석기 (Chart Interpreter)'를 설계, 개발하였다. 주식 가격의 변동을 예고하는 패턴들을 정의하고 그 패턴들의 의미에 따라 매미결정을 첨가한 규칙을 생성하였다. 정의된 패턴들은 의미에 따라 크게 하락형, 상승형, 중립형, 추세지속형, 추세 전환형으로 분류된다. 정의된 패턴과 지식베이스의 유용성을 검증하기 위해서 수행된 1992년부터 1997년에 걸친 과거 한국 주식 시장 실거래 투자 데이터에 대한 실험결과는 평균 투자 성공률이 약 72%로서 주식시장에서 투자자들의 투자를 돕는데 우수한 지표로서 사용될 수 있음을 보였다. 또한, 개발된 지식베이스는 특정 연도나 특정 분야에 따라 예측력이 크게 변하지 않은 시간 독립적이고 분야 독립적인 특성을 가짐으로 분야나 시간에 구애받지 않고 사용할 수 있다는 장점을 갖는다.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.155-174
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• 2021

This study noted the emergence of the Resell investment within the fashion market, among emerging investment techniques. Worldwide, the market size is growing rapidly, and currently, there is a craze taking place throughout Korea. Therefore, we would like to use shoe data from StockX, the representative site of Resell, to present basic guidelines to consumers and to break down barriers to entry into the Resell market. Moreover, it showed the current status of the Resell craze, which was based on information from various media outlets, and then presented the current status and research model of the Resell market through prior research. Raw data was collected and analyzed using the XGBoost algorithm and the Prophet model. Analysis showed that the factors that affect the Resell market were identified, and the shoes suitable for the Resell market were also identified. Furthermore, historical data on shoes allowed us to predict future prices, thereby predicting future profitability. Through this study, the market will allow unfamiliar consumers to actively participate in the market with the given information. It also provides a variety of vital information regarding Resell investments, thus. forming a fundamental guideline for the market and further contributing to addressing entry barriers.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.1-22
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• 2008

This study is to evaluate, to the extent to, which advanced currency futures and emerging currency futures markets can predict accurately the future spot rate. To this end, Johansen's the maximum-likelihood cointegration method(1988, 1991) is adopted to test the unbiasedness and efficiency hypothesis. Also, this study is to estimate and compare a quantitative measure of relative efficiency as a ratio of the forecast error variance from the best-fitting quasi-error correction model to the forecast error variance of the futures price as predictor of the spot price in advanced currency futures with in emerging currency futures market. Advanced currency futures is British pound and Japan yen. Emerging currency futures includes Korea won, Mexico peso, and Brazil real. The empirical results are summarized as follows : First, the unbiasedness hypothesis is not rejected for Korea won and Japan yen futures exchange rates. This indicates that the emerging currency Korea won and the advanced currency Japan yen futures exchange rates are likely to predict accurately realized spot exchange rate at a maturity date without the trader having to pay a risk premium for the privilege of trading the contract. Second, in emerging currency futures markets, the unbiasedness hypothesis is not rejected for Korea won futures market apart from Mexico peso and Brazil real futures markets. This indicates that in emerging currency futures markets, Korea won futures market is more efficient than Mexico peso and Brazil real futures markets and is likely to predict accurately realized spot exchange rate at a maturity date without risk premium. Third, this findings show that the results of unbiasedness hypothesis tests can provide conflicting finding. according to currency futures class and forecasts horizon period, Fourth, from the best-fitting quasi-error correction model with forecast horizons of 14 days, the findings suggest the Japan yen futures market is 27.06% efficient, the British pound futures market is 26.87% efficient, the Korea won futures market is 20.77% efficient, the Mexico peso futures market is 11.55%, and the Brazil real futures market is 4.45% efficient in the usual order. This indicates that the Korea won-dollar futures market is more efficient than Mexico peso, and Brazil real futures market. It is therefore possible to concludes that the Korea won-dollar currency futures market has relatively high efficiency comparing with Mexico peso and Brazil real futures markets of emerging currency futures markets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.170-177
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• 2017

The price of land in Jeju is reaching a new high every day and this phenomenon not only causes real difficulties for the purchase of real estate by local residents, but also results in psychological deprivation. Therefore, this study analyzes the factors causing the increase of the land price in Jeju, in order to examine the measures required to stabilize the land price which is continuously rising. As a result of this study, we developed a land price prediction model including seven variables, including the 'inflation rate', 'interest rate', and 'population'. According to the model, land prices in Jeju are expected to rise steadily, and it is predicted that in 2020 the price will increase to 170% of that in 2015 and will triple by 2025. Based on the results of this study, this study suggested policy alternatives, such as 'Establishing a tourism policy for managing the number of tourists' and 'increasing the approval standards for development activities'. The two policies proposed in this study can be implemented as a regional initiative, which may be less effective than the changes in the national system, but it is meaningful that the efforts to stabilize the land price will continue at the regional level.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.49-57
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• 2021

With the advent of the era of the fourth industry, more and more scientific techniques are being used to solve decision-making problems. In particular, big data analysis technology is developing as it becomes easier to collect numerical data. Therefore, in this study, in order to overcome the limitations of qualitatively analyzing investment trends, the association of various products was analyzed using associated analysis techniques. For the experiment, two experimental periods were divided based on the COVID-19 economic crisis, and sales information from individuals, institutions, and foreign investors was collected, and related analysis algorithms were implemented through r software. As a result of the experiment, institutions and foreigners recently invested in the KOSPI and KOSDAQ markets and bought futures and products such as ETF. Individuals purchased ETN and ETF products together, which is presumed to be the result of the recent great interest in sector investment. In addition, after COVID-19, all investors tended to be passive in investing in high-risk products of futures and options. This paper is thought to be a useful reference for product sales and product design in the financial field.