• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7672-7676
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• 2015

This study examines the dynamic relations between housing price and trading volume in a set of apartment markets in Republic of Korea to explore the informational role of trading volume in predicting the price volatility. Using monthly index data, EGARCH model is utilized to test for volume effect. To estimate the EGARCH-based volatility, two different sets of region are applied for the monthly return. Strong evidence has been found towards housing turnover leading price volatility, this supports previous studies on financial sector(s). These findings also support that trading volume in the housing market contains information on investor sentiment which, in turn, has a valuation effect on the price.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.337-346
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• 1999

In this paper, we propose the rough set approach to extract trading rules able to discriminate between bullish and bearish markets in stock market. The rough set approach is very valuable to extract trading rules. First, it does not make any assumption about the distribution of the data. Second, it not only handles noise well, but also eliminates irrelevant factors. In addition, the rough set approach appropriate for detecting stock market timing because this approach does not generate the signal for trade when the pattern of market is uncertain. The experimental results are encouraging and prove the usefulness of the rough set approach for stock market analysis with respect to profitability.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.211-221
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• 2013

This study investigated the effect of service quality and using experience on a royalty in a electronic commerce. Expecially, used HTS (Home Trading System of securities companies)as a online service system. HTS (Home Trading System) is a electronic commerce system of securities companies that is a most progressive tool of it. Almost securities companies are offering these typical trading system, because it is a required factor for a competitive position in their compound market. This paper made hypotheses of five cases, and collected some data through survey questionnaire for an analysis of actual proof. For attaining the object of this research, used a structure equation modeling, and found that almost paths of the research model are supported among the service quality, using experience, involvement and royalty. This study could provide academic and managerial implications in a electronic commerce business.

• The Journal of Information Systems
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• v.14 no.2
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• pp.155-172
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• 2005

Securities companies which faced with severe competition should not only attract new customers but also retain their on-line customers. This study examines the factors affecting loyalty of on-line stock trading customers. The research model based on the previous studies was established and the research hypotheses were generated. The test results based on the data gathered from 87 users of on-line stock trading services show that user satisfaction, learning cost, transaction fees, and reputation influence customer loyalty. User satisfaction, learning cost and reputation are positively related to customer loyalty, whereas transaction fee is negatively related to customer loyalty. The results also support that information quality and system quality are positively related to user satisfaction. The hypothesis that transaction fee is related to user satisfaction is not supported. There is no significant information to say that security risk is related to user satisfaction. It is considered that the study results may help managers to increase customer retention.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.151-162
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• 2010

Recent developments in financial market liberalization and information technology are accelerating the interdependence of national stock markets. This study explores the information spillover effect of the US stock market on the overnight and daytime returns of the Korean stock market. We develop a profitable intra-day trading strategy based on the information spillover effect. Our study provides several important conclusions. First, an information spillover effect still exists from the overnight US stock market to the current Korean stock market. Second, Korean investors overreact to both good and bad news overnight from the US. Therefore, there are significant price reversals in the KOSPI 200 index futures prices from market open to market close. Third, the overreaction effect is different between weekdays and weekends. Finally, the suggested intra-day trading system based on the documented overreaction hypothesis is profitable.

• International Commerce and Information Review
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• v.10 no.1
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• pp.259-277
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• 2008

This paper empirically analyzes the influence of export insurance on export promotion using panel data for the Korean case during the sample period from 2003 to 2006. We use the Korean export's share in trading partners' imports as a weight for the weighted least square (WLS) estimation to measure the effect of export insurance on the export promotion. Our main finding is that export insurance subsidy seems to enhance the export performance when the Korean export takes greater share in other countries' markets. On the other hand, under weaker monopoly power of the Korean export, export risk and trading partners' GDP growth rate has more influence on the export promotion rather than export insurance subsidy. Our finding implies that policy makers and practitioners should discern the Korean exports' monopoly power differential across trading countries for better performing export insuarnce policy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.545-546
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• 2021

최근 주식시장의 관심이 급격하게 높아지고 있으며, 코로나 19의 영향으로 신규 투자가 더욱더 늘어나고 있다. 하지만 개인의 투자자의 경우 기관보다 취득할 수 있는 정보의 양이 제한적이고 정보의 취득 시점이 늦기 때문에 개인의 투자자는 정보를 주관적으로 판단할 수밖에 없는 문제점이 있다. 따라서 본 논문에서는 주식매매의 객관적인 판단을 위하여 페어 트레이딩 기반 빅데이터 분석을 이용하여 주식 매매 시기를 사용자에게 알려주는 알림 시스템을 제안한다. 주식 매매 시기 알림 시스템을 적용할 때 사용자에게 객관적인 주식 매매 시기를 알려주어 투자 손해를 줄일 수 있을 것으로 기대한다.

• Information Systems Review
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• v.18 no.2
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• pp.23-38
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• 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 Intelligence and Information Systems
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• v.29 no.1
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• pp.377-396
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• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.

• Asia pacific journal of information systems
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• v.15 no.2
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• pp.171-193
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• 2005

Small firms are considered as the last mile in electronic networks of business enterprises. Since small firms lack in their resources and capabilities for IT deployment, it seems a challenging project to make them electronically linked to their trading partners. This study aims to investigate the factors that influence the intent of small firms to adopt electronic linkage to their trading partners. This study considers the context where small firms already have transaction relationships with partner firms and where their adoption of electronic linkage may influence the nature and performance of the transactional relationships. This study considers the expected value of electronic linkage and the joint actions of the trading firms as the major factors. Its research model also includes traditional factors such as influences from the industry and the trading partner, the support of CEO, and the readiness of the trading partner. Based on the survey data from more than 1000 small firms, the present study performs regression analysis and finds that all but one factor are significant in explaining the variations in the adoption intention of small firms. The exception is the joint action, which is shown to decrease the intention. Based on the results, this study offers business and policy implications that would be useful to business managers and policy makers.