• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.11a
• /
• pp.322-324
• /
• 2008

패션 시장은 항상 경쟁이 치열하고 고객의 변화 및 이탈이 심한 시장이다. 경쟁의 요소가 품질 등의 가격적인 요소에서 디자인 및 서비스 등 비 가격 적인 요소의 중요성이 부각되고 있다. 이에 따라 고객 정보에 대한 분석을 기반으로 한 마케팅 및 판매 전략이 중요한 것은 두말할 필요가 없다. 정보 기술과 다양한 분석 기법은 다양한 방법으로 고객의 행동을 분석하여 고객의 구매 형태를 분석 및 예측하여 고객별로 차별화된 마케팅과 서비스를 제공할 수 있도록 한다.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
• /
• 1999.11a
• /
• pp.225-230
• /
• 1999

Since changes in crude oil price exert colossal influence upon most national economy, it is important to investigate about factors that cause the change through an appropriate crude oil price forecast. This paper examines the relationship among crude oil price, OPEC production and U.S. inventory using cointegration and error correction model. We found that crude oil price is likely to increase significantly for a given decrease in not only the OPEC production but also the U.S. inventory. Furthermore, we found that crude oil price is more elastic with respect to OPEC production in the short-run, and more elastic with respect to U.S. inventory in the long-run. Moreover, in the long-run, U.S. inventory have more an effect on crude oil price than OPEC production. Finally, crude oil price adjusts to their respective long-run equilibrium at a moderate speed, about 12% of adjustment taking place in the first year.

• Korean Journal of Construction Engineering and Management
• /
• v.20 no.6
• /
• pp.23-33
• /
• 2019

The purpose of this study is to analyze the housing price variation within the redevelopment project district, affected by the characteristics of project and implementation stage. This study implemented the hedonic price model employing the actual transaction price with 24 dependent variables from 2006 to 2016 inside 19 redevelopment districts in Seoul. Research finding indicates that the larger ratio of the number of tenants and general distribution, the smaller ratio of rented households and the more positive effect of housing price. It is noteworthy that this study demonstrated the actual transaction price of houses located within the project districts by implementation stage. This study is expected to help the policy makers, the developers and the investors make more reliable decisions on the feasibility study related to the redevelopment project.

• KDI Journal of Economic Policy
• /
• v.32 no.4
• /
• pp.35-73
• /
• 2010

This paper examines consumption dynamics in relation to asset prices in Korea. Empirical analysis based on the error correction model shows that personal consumption is affected by changes in asset prices but the consumption converges to the long-run level of consumption corresponding to the total income flow in two years. This adjustment in consumption implies that the consumption error, reflected in the error correction term, should have predictability for the future consumption growth during the adjustment period. It is found that the error correction term has a long-run predictability for consumption over up to about 3 years; thus, confirming the error correction model. It is also found that housing prices have larger effects on consumption compared with stock prices in Korea. In addition, the effects of income and asset prices on consumption show bigger effects during contractionary period than expansionary period in business cycles. This paper also analyzes effects of asset wealth that reflects changes in both price and quantity. It is found that asset wealth has a long-run effect on consumption in addition to total income as determinants of consumption. Since wealth effects usually indicate the long-run effect of changes in asset wealth on consumption that is not explained by labor income, which is the proxy for human source of wealth, it is estimated with labor income used as a control variable. According to the estimation, the marginal propencity to consume out of asset wealth is approximately 2%. It means that 1,000won increase in asset wealth may lead to 20 won increase in consumption.

• Horticultural Science & Technology
• /
• v.32 no.5
• /
• pp.721-729
• /
• 2014

This study was conducted to improve the consumption of floriculture plants by researching preferences of consumers for the main types of cut flowers. We analyzed the results of surveys, carried out by a company, that were largely about roses, chrysanthemums, and lilies. After departmentalizing consumers into groups and analyzing the results through conjoint and cluster analysis, we found that consumers showed a higher rate of use based on price and vase life than on flower color and flower shape in roses. The groups of rose consumers preferred a price of 1000 won, spray type flower shape, vase life of 7-8 days, and red flower color. In chrysanthemums, consumers showed higher rate of use for flower color than for vase life, flower shape, and price. The groups of chrysanthemum consumers preferred a price of 1000 won, standard flower shape, 16-20 days vase life, and yellow flower color. In lilies, consumers showed higher use rate for flower shape than vase life, price, and flower color. Lily consumers preferred a price of 2000 won, large flower shape, 4-7 days vase life, and yellow flower color. Thus, the major cut flowers (rose, chrysanthemum, and lily) all showed highest use rates in for vase life. These results highlight the importance of understanding the characteristics of consumer interests. They also emphasize that we should plan and create market-oriented and consumer-oriented products to improve the consumption of floriculture plants.

• Journal of the Korean Geographical Society
• /
• v.31 no.4
• /
• pp.648-661
• /
• 1996

The traditional von Thunen model has various shortcomings. Perhaps the greatest dificiency is the model's sole emphasis on the production side of the economy;that is, the agricultural markets are rarely closed for demand. In thes paoer a closed model for a three-activity, two-dimensional economy is developed. Equillibrium solutions are generated for prices, land areas, and outputs. Comparative static analysis then follows. Attention is next given to a maximum expected-return model under environmental uncertainty. Land uses for the traditional model and the closed model are then compared.

• Journal of Digital Convergence
• /
• v.12 no.5
• /
• pp.89-99
• /
• 2014

Correlation of KOSPI from stock market and Apartment Prices in Seoul HPPCI from real estate market has been found from this research. Furthermore, from the comparison of those indicators' flows, certain precedence was found as well. The purpose of this research is to analyze correlation and precedence among KOSPI, Apartment price in Seoul, HPPCI and CLI. As for predicting KOSPI of stock market and real estate market, it is necessary to find out preceding indices and analyzing their progresses first. For 27 years from the January 1987 to December 2013, KOSPI has been grown by 687%, while CLI showed 443%, Apartment of Seoul showed 391%, HPPCI showed 263% of growth rate in order. As the result of correlation analysis among Apartment of Seoul, CLI, KOSPI and HPPCI, KOSPI and HPPCI showed high correlation coefficient of 0.877, and Apartment of Seoul and CLI showed that of 0.956 which is even higher. Result from the analysis, CLI shows high correlation with stock and real estate market, it is a good option to watch how CLI flows to predict stock and real estate market.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1423-1431
• /
• 2022

Volatility is one of the variables that the Black-Scholes model requires for option pricing. It is an unknown variable at the present time, however, since the option price can be observed in the market, implied volatility can be derived from the price of an option at any given point in time and can represent the market's expectation of future volatility. Although volatility in the Black-Scholes model is constant, when calculating implied volatility, it is common to observe a volatility smile which shows that the implied volatility is different depending on the strike prices. We implement supervised learning to target implied volatility by adding V-KOSPI to ease volatility smile. We examine the estimation performance of KOSPI200 index options' implied volatility using various Machine Learning algorithms such as Linear Regression, Tree, Support Vector Machine, KNN and Deep Neural Network. The training accuracy was the highest(99.9%) in Decision Tree model and test accuracy was the highest(96.9%) in Random Forest model.

• Management & Information Systems Review
• /
• v.30 no.2
• /
• pp.237-255
• /
• 2011

This empirical study is focused on practical application of Range-Based Volatility which is estimated by opening, high, low, closing price of overall asset. Especially proper forecasting period is what I want to know. There is four useful Range-Based Volatility(RV) such as Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). So, four RV of KOPSI 200 index during 2000.5.22-2009.9.18 was used for empirical test. The emprirical result as follows. First, the best RV which shows the best forecasting performance is PK volatility among PK, GK, RS, YZ volatility. According to estimating period forcasting performance of RV shows delicate difference. PK has better performance in the period with financial crisis of sub-prime mortgage loan. if not, RS is better. Second, almost result shows better performance on forecasting volatility without sub-prime mortgage loan period. so we can say that forecasting performance is lower when historical volatiltiy is comparatively high. Finally, I find that longer estimating period in AR(1) and MA(1) model can reduce forecasting error. More interesting point is that the result shows rapid decrease form 60 days to 90 days and there is no more after 90 days. So, if we forecast the volatility using Range-Based volaility it is better to estimate with 90 trading period or over 90 days.

• Korean Journal of Agricultural Science
• /
• v.14 no.2
• /
• pp.263-271
• /
• 1987

The cyclical trend and seasonal variations of chestnut prices have been analyzed to find out the chestnut price fluctuation in Korea during 1966-1985. The optimum prices, production, and plantation area for the next twenty five years (1986-2010) have been forcasted by the derived equation models. The results of study can be summarized as follows: 1. The chestnut prices were increased by 14.67 percent per annum during 1966-1972, an d decreased by 9.24 percent during 1973-1985, due to the excessive production of chestnut. 2. The chestnut prices showed the lowest price during the harvesting season, especially in October (89.1), and highest in July (109.1). Seasonal fluctuation of chestnut prices were 0.0837 (C.V value) during 1966-1975, and 0.0706 during 1976-1985. Such a seasonal fluctuation of chestnut prices tends to be even with the passage of time. 3. The equation model of predicted chestnut prices was derived as follows : PR=117788.088 - 7.60 TC/Pop + 6.585 GNP/Pop The chestnut prices will be the lowest in 1988, but increased rapidly thereafter. 4. The equation model of optimum chestnut production was derived as follows : $${\ell}n\;PD/Pop=-8.5147-0.8267{\ell}n\;PR+3.3063{\ell}n\;GNP/Pop$$ To maintain optimum chestnut prices according to this model, chestnut production should be 133,000 ton for 1988, and 1,899,000 ton for 2010. 5. Optimum chestnut plantation area will be 4,000 ha in 1988, and thereafter total plantation area will be up to 57,400 ha in 2010.