• Journal of the Korean Geographical Society
• /
• v.39 no.6 s.105
• /
• pp.907-921
• /
• 2004

Lots of characteristics such as dwelling, neighborhood, and accessibility characteristics affect to the housevalue. Many researches have been done to identify values of each characteristic using hedonic technique. However, there is a limit to identify interaction of each characteristic and variation of each characteristic among the accessibility context. This paper has implemented the Expansion Method research paradigm to model the housevalue determination process in the city of Seoul. The findings of this paper have revealed the presence of contextual variations in the housevalue determination process. The initial model for housevalue reveals that as $F_1$ increases (i.e., larger the number of rooms/bathrooms, larger parking space) and/or $F_2$ increases (i.e., higher owner occupied housing units, higher apartment housing units) and/or $F_3$ increases, (i.e., higher the ratio of higher than college graduated households, 8 school zone, older housing units) the estimated housevalue increases. However, the above relationships drift across their respective contexts. The houses which have negative $F_1$ value, the housevalue does not fluctuate according to the distance to the city center or subcenters. However, the houses which have positive $F_1$ value, the closer to the subcenters or shorter to the river, the higher the estimated housevalues. On the other hand, in areas far from the subcenters, the estimated housevalues does not fluctuate much according to the corresponding $F_2$ level. In areas close to the subcenters, the estimated housevalues vary tremendously according to the $F_2$ value. In the residual analysis, it is revealed that large apartment which are located in Kangnam, IchongDong, MokDong are underestimated. This paper has contributed to our understanding of the housevalue determination process by providing an alternative conceptualization to the traditional approach.

• Environmental and Resource Economics Review
• /
• v.22 no.4
• /
• pp.581-612
• /
• 2013

Opinet is the system that has announced the daily domestic petroleum price data from April 2008. This study's goal is to examine if the domestic petroleum(gasoline and diesel) prices adjust their prices asymmetrically comparing before-Opinet with after-Opinet. The results of this study found the evidence of asymmetric domestic petroleum prices before the Opinet and the evidence of symmetric domestic petroleum prices after the Opinet. Also the domestic petroleum prices after the Opinet adjust upward/downward nearly twice as fast when its actual value is below/above its equilibrium. According to this study, the domestic petroleum market works more efficiently than before.

• Journal of the Korea Society for Simulation
• /
• v.23 no.4
• /
• pp.1-8
• /
• 2014

Cloud computing helps big data processing to make various information using IT resources. The government has to start the RPS(Renewable Portfolio Standard) and induce the production of electricity using renewable energy equipment. And the government manages system to gather big data that is distributed geographically. The companies can purchase the REC(Renewable Energy Certificate) to other electricity generation companies to fill shortage among their duty from the system. Because of the RPS use voluntary competitive market in REC trade and the prices have the large variation, RPS is necessary to predict the equitable REC price using RPS big data. This paper proposed REC price prediction method base on fuzzy logic using the price trend and trading condition infra in REC market, that is modeled in cloud computing environment. Cloud computing helps to analyze correlation and variables that act on REC price within RPS big data and the analysis can be predict REC price by simulation. Fuzzy logic presents balanced REC average trading prices using the trading quantity and price. The model presents REC average trading price using the trading quantity and price and the method helps induce well-converged price in the long run in cloud computing environment.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.05a
• /
• pp.309-309
• /
• 2004

쾌속조형 공정의 파트 성형 방향 결정 문제는 파트 표면의 품질, 제작시간, 파트 가격 등에 영향을 미치므로 대단히 중요하다. 실제적으로 이들 중요 변수들끼리는 모델제작과정에서 trade-off가 존재한다. 실제 파트 성형 방향 결정은 작업자의 경험이나 시행착오에 의해서 파트의 방향이 결정하고 있어 조금 복잡한 파트에 대해서는 최적의 성형을 결정하기 매우 힘들다. 일반적으로 쾌속조형 공정은 작업동안 공정변수가 변하지 않는 일정한 층두께를 가지고 작업을 수행한다.(중략)

• Environmental and Resource Economics Review
• /
• v.20 no.3
• /
• pp.459-487
• /
• 2011

A/R CDM project has properties such as irreversibility and uncertainty that Real Option Analysis can be applied to its modelling. This study tries to model A/R CDM using Real Option under CER price uncertainty, and conducts empirical test with the Posco A/R CDM Project case. For precise comparison and decision-making, l-CER's expected present value is calculated from the Spot CER price. As a result, the critical value of the project is lower than the expected l-CER price, which means that the decision to invest made by the project owner is profitable. We can also find out that the level and the range of the discount rate, where is applied to, affect the result; the critical value of the project and the decision-making.

• Journal of Digital Convergence
• /
• v.14 no.11
• /
• pp.173-179
• /
• 2016

This study was conducted to provide basic information for future Anseong local food policy and local food activation by finding the key factor determining consumer purchasing for Anseong local food. First, we conducted a survey and derived consumer purchasing attributes for the local food. Logistic regression analysis was performed to find the main factors that determine the consumers' purchase intention for Anseong local food out of such seven attributes as 'excellent quality', 'safety', 'good for health', 'activation of local economy', 'low price', 'accessibility', 'variety of items'. The results showed that the most influencing attributes on consumers' purchase decisions for Anseong local food were 'excellent quality' and 'low price' followed by 'accessibility' and 'activation of local economy'.

• Journal of the Korean Geographical Society
• /
• v.49 no.6
• /
• pp.917-934
• /
• 2014

Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

• Korean Business Review
• /
• v.11
• /
• pp.319-341
• /
• 1998

Transfer pricing is a process for determining the prices of products, technology and services among affiliated companies. Although taxation problems arising from international investment are not now, they have become more important in recent years as a consequence of the growing internationalization of economic activities. So, trans pricing to shift their income and expenses from one country to another has made it difficult for tax administrations to impose tax collectly. Our government also applies arm' length methods to decide equitable tax. In the case of intangibles, because of the characteristics of the market, it is not easy to find the comparable uncontrolled transactions and it is almost impossible to apply cost=plus method or resale price method. This paper treats these problem, examining U.S. regulations and OECD guidelines and analysing the practice of transactions and the application of other methods.

• The Korean Journal of Financial Management
• /
• v.21 no.2
• /
• pp.211-233
• /
• 2004

This purpose of paper is to propose a European option pricing formula when the rate of return follows the leptokurtic distribution instead of normal. This distribution explains well the volatility smile and furthermore the option prices calculated under the leptokurtic distribution are shown to be closer to the market prices than those of Black-Scholes model. We make an estimation of the implied volatility and kurtosis to verify the fitness of the pricing formula that we propose here.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.01a
• /
• pp.31-34
• /
• 2023

주택 매매에 있어서 가격에 대한 예측은 매우 중요하지만, 실거래 발생 전까지는 정확한 가격을 알 수 없다. 그렇기에 주택가격을 예측하는 많은 연구가 진행되어왔다. 주택가격을 결정하는 영향요인은 크게 주택의 내부요인과 주택의 외부 요인으로 구분되는데, 내부적인 요인 (공급면적, 전용면적, 층, 방 개수 등)에 대한 연구가 많이 진행되었다. 하지만 외부적인 요인 (위치 요인, 금융요인 등)에 대한 연구는 미비하였다. 본 연구는 주택 매수자 관점에서 가격 예측 시 외부적인 요인 역시 중요하다고 판단하여 외부요인을 적용하고자 한다. 본 논문에서 제안하는 방법은 다양한 외부요인 중 주택의 위치 정보를 활용하여, 해당 정보 기반으로 도출 가능한 데이터를 추가한다. 또한 이용량에 따른 지하철역 데이터를 추가하여 관련된 여러 영향요인들을 분석 및 적용 후 머신러닝 기반 예측 모델을 생성한다. 생성된 모델들에 주택매매 실거래 데이터를 적용하여 예측 정확도를 비교 후 높은 정확성을 보이는 모델 결과에 주요하게 영향을 끼치는 요인에 관하여 기술한다.