• Information Systems Review
• /
• v.18 no.2
• /
• pp.23-38
• /
• 2016

Previous studies on information systems (IS) and finance suggest that information on stock message boards influence the investment decisions of individual investors. However, how information on online stock message boards influences an individual investor's buy or sell decisions is unclear. To address this research question, we investigate the relationship between a number of posts on stock message boards and order imbalance in stock markets. Order imbalance is defined as the difference between the daily sum of buy-side shares traded and the daily sum of sell-side shares traded. Therefore, order imbalance can suggest the direction of trades and the strength of the direction with trading volumes. In this regard, this study examines how the number of posts (information on stock message boards) influences order imbalance (stock trading behavior). We collected about 46,077 messages of 40 companies on the Korea Composite Stock Price Index from Paxnet, the most popular Korean online stock message board. The messages we collected were divided based on in-trading and after-trading hours to examine the relationship between the numbers of posts and trading volumes. We also collected order imbalance data on individual investors. We then integrated the balanced panel data sets and analyzed them through vector regression. We found that the number of posts on online stock message boards is positively related to prior order imbalance. We believe that our findings contribute to knowledge in IS and finance. Furthermore, this study suggests that investors should carefully monitor information on stock message boards to understand stock market sentiments.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.14 no.6
• /
• pp.97-109
• /
• 2011

Korea introduced the cooperation charge on conservation of ecosystem for minimizing damage of ecosystem due to development projects and their effects and for preparing resources for natural environment conservation projects. Advanced countries have made efforts by expanding investment in natural environment conservation and restoring projects to promote prevention of global warming and improvement of biological diversity, are establishing nationwide strategies and plans. To examine the reality of projects by returns of the cooperation charge on conservation of ecosystem, microsite projects in schools and public facilities take the largest share while their project budgets are only about 100~300 KRW, relatively small, which might be attributable to budget restrictions in accordance with the calculating method of levying cooperation charge on conservation of ecosystem and problems of project proceeding in the system of returning fund for projects in general. The conclusion which this study suggests on invigoration of cooperation charge on conservation of ecosystem and its operation are as followings. First, although the cooperation charge on conservation of ecosystem has been introduced in 2001, the amount of imposition per unit area remains unchanged. It is desirable to increase the amount into $1,400KRW/m^2$ as of August, 2011 as the price index has been continuously rising for the past 10 years and the upward adjustment of imposition per unit area should be notified by the decree of the Ministry of Environment every January. Second, the ceiling amount of the cooperation charge on conservation of ecosystem should be abolished. Now the ceiling amount is defined as 1 billion KRW but it was found that there was not any ceiling amount specified according to the comparative analysis of similar systems with the Korean environmental improvement fund. The ceiling should be abolished so that medium level businesses are carried out and ecosystem recovering projects in the true sense of the word can be made smoothly. Third, weight should be introduced in calculating amounts in accordance with ecologic and economic values. Harmony between development and environment can be achieved by applying differentiated weights of constant regional coefficient by use zone and ecologic and economic values. Continuous efforts of improving cooperation charge on conservation of ecosystem should be made more than anything else so that projects by returns of cooperation charge on conservation of ecosystem get effectiveness.

• Journal of the Korean Society of Food Culture
• /
• v.20 no.5
• /
• pp.594-602
• /
• 2005

The purpose of this study was to investigate eating behaviors related to snack and self-purchasing snack (SPS) among elementary school children. Self-administered questionnairs were completed by 352, 5th and 6th grade elementary school students living in 3 different regions which included apartment region in Bundangn, Sungnam (apartment group, n=116), residences in Seodaemun-Gu and Mapo-Gu, Seoul (kang-buk group, n=103) and residence in industrial region in Sungnam (industry group, n=133). The results were as follows: A significantly higher proportion (64.7%) of the apartment group had breakfast every morning than those of kang-buk (48.6%) or industry (52.1%) group (p<0.01). As for the frequency rate of snack and self-purchasing snack (SPS), 53.9% of the subjects answered taking snack more than once per day, 22.8%, once for few days and 23.3%, almost not. However, 15.5% of the subject had SPS once or more per day, 30.7%, 1-2 times per week and 22.4%, almost not. Those of apartment group showed significantly lower SPS frequencies (p<0.01), since higher proportions answered having SPS 1-2times per week (40.9%) and almost not (31.3%) compared to other groups. The reasons for having SPS turned out to be 'hunger' 54.7%, 'being habitual', 15.9%, 'bing bored', 15.7% and 'with peers' 13.7%. When subjects selected SPS foods, they considered taste (31.5%), price (23.0%), mood at the time (14.1%), sanitorial aspect (10.2%) and quantity (10.1%) rather than nutritional aspect (7.2%). Subjects' pocket money was estimated as 3736 won per week and SPS expense per time as 706 won. But subjects who spent more than 2000 won for SPS expense were significantly higher (33.0%) in apartment group than those of other groups (p<0.01). The favorite snack items that subjects having at home were fruit, ice cream, milk and yoghurt, cookies, ramen and bread in order. And favorite SPS items turned out to be ice cream, cookies, duckbokki, frozen bars, gum, chocholate and candy in order. The frequency rate of SPS were evaluated to be significantly related by several variables: those living in apartment area (p<0.01), those taking breakfast regularly (p<0.01), those of normal weight status by Rohrer index (p<0.05) and those receiving less pocket money (p<0.01) showed lower SPS frequency rate.

• Korean Journal of Construction Engineering and Management
• /
• v.14 no.2
• /
• pp.12-21
• /
• 2013

The purpose of this study is to determine a national construction industry's competitiveness and establish strategies to expand into overseas construction markets. To evaluate the international competitiveness of overseas construction businesses, this study were selected as the target range of international comparisons among the countries cited by ENR, Global-Insight, IMF, OECD, and Transparency International. In result the United States ranked first, followed by China $2^{nd}$, Italy$3^{rd}$, U.K.$4^{th}$, and Germany $5^{th}$, while Korea ranked $9^{th}$ overall. In particular, Korea's competitiveness in the construction infrastructures by country ranking($11^{th}$) was higher than the competency assessment results of construction companies by country, therein ranking $12^{th}$. In addition, while Korea ranks $12^{th}$ among 22 countries, $3^{rd}$ in price competitiveness, $12^{th}$ in construction competitiveness, and $19^{th}$ in design competitiveness.

• KDI Journal of Economic Policy
• /
• v.36 no.3
• /
• pp.121-168
• /
• 2014

After analyzing and finding the explaining factors about the "Effect of My Mom's Friend's Son (MMFS Effect)" with online-surveyed data, we introduce this concept into the conventional job search theory to develop it further. We try to estimate its effects on the hazard rate of youth pre-employment duration with some proxy variables such as his/her parents' schooling, living with parents dummy, increasing rate of consumer price index representing the burdens of parents, monthly temporary/daily workers ratio, relative ratio of quarterly 90th percentile urban household income, monthly average wage differentials between the workers of large and small firms, etc. The results confirm us the fact that so called "MMFS Effect" has been effective enough and strengthened up to recently. The conventional job search theory should be extended to be able to introduce the influencing effects of other person's success, for instance MMFS's success, on the job search behavior of youths, too.

• Journal of Intelligence and Information Systems
• /
• v.16 no.1
• /
• pp.71-92
• /
• 2010

As the use of trading systems increases recently, many researchers are interested in developing intelligent trading systems using artificial intelligence techniques. However, most prior studies on trading systems have common limitations. First, they just adopted several technical indicators based on stock indices as independent variables although there are a variety of variables that can be used as independent variables for predicting the market. In addition, most of them focus on developing a model that predicts the direction of the stock market indices rather than one that can generate trading signals for maximizing returns. Thus, in this study, we propose a novel intelligent trading system that mitigates these limitations. It is designed to use both the technical indicators and the other non-price variables on the market. Also, it adopts 'two-threshold mechanism' so that it can transform the outcome of the stock market prediction model based on support vector machines to the trading decision signals like buy, sell or hold. To validate the usefulness of the proposed system, we applied it to the real world data-the KOSPI200 index from May 2004 to December 2009. As a result, we found that the proposed system outperformed other comparative models from the perspective of 'rate of return'.

• International Area Studies Review
• /
• v.20 no.2
• /
• pp.3-23
• /
• 2016

In this study, we used actual proof analysis, based on SVAR model according to economy theory, to observe the impact of actual and financial market of Korea, Japan, and China that have adopted quantitative easing export based strategy of growth, an unconventional monetary policy of the U.S. As a result of estimation, it appears that real effective exchange rate rise shock of Korea, Japan, and China against U.S. dollar has a negative influence on current account and index of industrial product, which are real economy. It can be implied that the result is driven from the fact that strong home currency of Korea, Japan, and China decreases price competitiveness of exports, causing negative influence on real economy. The real effective exchange rate shock against U.S. dollar appeared to decrease national bond rate of Korea and Japan, while increasing that of China. In instances of Korea and Japan, it is implied that national bond rate decreases as foreigner investment funds flow in, considering foreign-exchange profit through advanced financial market with high opening extent. On the other hand, because there are strong regulation on opening extent of Chinese financial markets, the influence seems to be greater for domestic policy, rather than a foreign influence. Lastly, Korea showed a more dramatic variable reaction to exchange rate shock compared to Japan or China. It is implied from the result that Korea is relatively more susceptible and fragile in regards of international status of economic size and currency.

• Journal of the Korea Convergence Society
• /
• v.12 no.6
• /
• pp.9-16
• /
• 2021

In the past, there have been various studies on predicting the stock market by machine learning techniques using stock price data and financial big data. As stock index ETFs that can be traded through HTS and MTS are created, research on predicting stock indices has recently attracted attention. In this paper, machine learning models for KOSPI's up and down predictions are implemented separately. These models are optimized through a grid search of their control parameters. In addition, a hybrid machine learning model that combines individual models is proposed to improve the precision and increase the ETF trading return. The performance of the predictiion models is evaluated by the accuracy and the precision that determines the ETF trading return. The accuracy and precision of the hybrid up prediction model are 72.1 % and 63.8 %, and those of the down prediction model are 79.8% and 64.3%. The precision of the hybrid down prediction model is improved by at least 14.3 % and at most 20.5 %. The hybrid up and down prediction models show an ETF trading return of 10.49%, and 25.91%, respectively. Trading inverse×2 and leverage ETF can increase the return by 1.5 to 2 times. Further research on a down prediction machine learning model is expected to increase the rate of return.

• The Journal of the Korea Contents Association
• /
• v.21 no.12
• /
• pp.34-46
• /
• 2021

In the domestic data exchanging market, unreasonable pricing of purchase data is consistently mentioned as a major obstacle in data trading. This is a problem caused by the inability to properly evaluate the value of data products due to lack of product information and experience in using them. In order to activate trading, the data exchanges need to provide information that allows consumers to comprehensively judge the value of data products in addition to prices. The cost-based, income-based, and market-based methods, which are mainly applied to data valuation, are insufficient as data valuation methods to stimulate trading and distribution because only price information, a result of valuation from a supplier's point of view, can be shared with consumers. This study aims to develop a measurable valuation method that allows data trading stakeholders (exchanges, suppliers, and consumers) to judge and share the value of data products from a common perspective. To this end, we identified the value drivers of data products, which are considered important in overseas data exchanges and related research, and derived an evaluation method that can quantitatively measure each value driver. In addition, evaluation criteria in the form of a rating table were developed using data products for transactions, and a value evaluation index was developed through stratification analysis (AHP) to enable relative value comparison. As a result of applying the evaluation criteria to actual data products, it was found that the evaluation values were differentiated according to the characteristics of individual data products, so it could be used as a relative value comparison tool.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.3
• /
• pp.65-84
• /
• 2023

In order to establish a balanced development plan at the local government level, it is necessary to understand the current urban spatial structure. In particular, since the central area is a key element of balanced development, it is necessary to accurately identify its location and size. Therefore, the purpose of this study was to identify the central area system for Busan and to derive underprivileged areas that were alienated from the service areas where the functions of the central area could be used. To identify the central area system, four indicators(De facto Population, Land Price, Commercial Buildings, Credit Card Consumption) were used to calculate the central area index, and Getis-Ord Gi* and DBSCAN analysis were performed. Next, the hierarchy of the central areas were classified and the service areas were derived through network analysis by using it. As a result of the analysis, a total of 12 central areas were found in Seomyeon, Jungang, Yeonsan, Jangsan, Haeundae, Deokcheon, Dongnae, Daeyeon, Sasang, Pusan National University, Busan Station, and Sajik. Most of the underprivileged areas affected by the central area appeared in the Eastern area of Busan and the Western area of Busan, and were derived from old industrial areas, residential areas, and some new cities. Based on the results of the study, we can find three meanings. First, we have made a new attempt to apply a machine learning methodology that has not been covered in previous studies. Second, our data show the difference between the actual data and the existing planned central areas. Third, we not only found the location of the central areas, but also identified the underprivileged areas.