• Journal of Korean Electronics
• /
• v.11 no.4
• /
• pp.104-106
• /
• 1991

• Journal of Korean Electronics
• /
• v.12 no.1
• /
• pp.108-112
• /
• 1992

• Journal of Korean Electronics
• /
• v.11 no.7
• /
• pp.122-125
• /
• 1991

• Journal of Korean Electronics
• /
• v.1 no.10
• /
• pp.79-86
• /
• 1981

• Journal of Korean Electronics
• /
• v.11 no.8
• /
• pp.136-140
• /
• 1991

• Management & Information Systems Review
• /
• v.35 no.2
• /
• pp.1-12
• /
• 2016

In this study, price discovery between the KOSPI200 spot, and leveraged ETFs(Leveraged KODEX, Leveraged TIGER, Leveraged KStar) is investigated using the vector error correction model(VECM). The main findings are as follows. Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot are cointegrated in most cases. There is no interrelations between the movement of Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot markets in case of daily data. Namely, in daily data, Leveraged KODEX(Leveraged TIGER, Leveraged KStar) doesn't plays more dominant role in price discovery than the KOSPI200 spot.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2003.05a
• /
• pp.199-205
• /
• 2003

본 연구의 목적은 한일 온라인게임 시장의 고객을 세분화하여 국내기업이 일본 온라인게임 시장에 진출할 때 고려해야 될 전략을 도출하는데 있다. 이를 위해 MCFA와 SOM을 이용하고자 한다. 먼저 MCFA를 통해 한일 온라인게임 시장의 고객 몰입에 영향을 주는 요인들이 무엇이며, 이러한 요인의 측정 동질성이 같은지를 먼저 검증하였다. 이러한 방법을 통해 검증된 요인으로는 도구, 보상, 디자인, 정보제공, 공동체를 들 수 있다. 다음으로 SOM을 이용해 위에서 구한 요인을 기준으로 한일 온라인게임 시장의 고객을 세분화하고자 한다. 이후 이렇게 세분화된 고객의 특성을 도출하기 위해 Decision Tree를 이용하고자 한다.

• The Korean Journal of Financial Management
• /
• v.20 no.1
• /
• pp.163-190
• /
• 2003

This study tests the hypothesis of market efficiency through the information spillover effects over price and volatility across countries by using open-to-close(daytime) returns and close-to-open(overnight) returns of NASDAQ, KOSDAQ and JASDAQ data from January 3, 1997 to December 21, 2000. Based on Granger-causality and time-varying AR(1)-GARCH(1, 1)-M models we document that the evidence of statistically significant conditional mean and volatility spillovers effects from the daytime returns and volatility of NASDAQ to the overnight returns and volatility of KOSDAQ is observed both before and after the IMF foreign currency crisis but not to the close-to-open return before the IMF foreign currency crisis. We can understand the information spillover effect from NASDAQ to KOSDAQ on the overnight rather than the daytime grows more significantly after the IMF foreign currency crisis. We also find the interactive information spillover effect between NASDAQ and JASDAQ both before and after the IMF financial crisis, in particular, to close-to-open return. In addition, the market efficiency between KOSDAQ and NASDAQ is on an increasing trend through IMF foreign currency crisis.

• Journal of Intelligence and Information Systems
• /
• v.14 no.2
• /
• pp.103-119
• /
• 2008

Traditional market which is characterized by the folksy retailing market has lost its competitiveness rapidly due to the emergence of the Internet and the change of customer's purchasing behavior. The recession of the traditional market contracts the regional economy. We suggest a u-Market, a traditional market with ubiquitous computing capability, to revitalize traditional market. The suggested u-Market system applies ubiquitous computing technologies characterized by communications between customers and objects without limitations of time and location. The proposed u-Market system offers location information and specific contents of traditional market to customers. Furthermore, u-Market system recommends the store and product list that customers are likely to visit and purchase based on their contexts, so they can save their time and effort to search the products or contents.

• Journal of the Korea Society for Simulation
• /
• v.24 no.4
• /
• pp.97-106
• /
• 2015

In recent, hybrid market segmentation techniques have been widely adopted, which conduct segmentation using both general variables and transaction based variables. However, the limitation of the techniques is to generate incorrect results for market segmentation even though its methodology and concept are easy to apply. In this paper, we propose a novel scheme to overcome this limitation of the hybrid techniques and to take an advantage of product information obtained by customer's transaction data. In this scheme, we first divide a whole market into several unit segments based on the general variables and then agglomerate the unit segments with higher QAP correlations. Each product network represents for purchasing patterns of its corresponding segment, thus, comparisons of QAP correlation between product networks of each segment can be a good measure to compare similarities between each segment. A case study has been conducted to validate the proposed scheme. The results show that our scheme effectively works for Internet shopping malls.