• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.1
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• pp.3-13
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• 2004

E-Commerce is suddenly spreading in a daily life. A rights trading system is a system that circulates digital-tickets such as plane tickets, software license, coupon. There are two main approaches so far account-based and smart-card based systems. The NTT Proposed FlexToken, a new smart card based copy prevention scheme for digital rights. They Proposed using pseudonymous self certified keys of Petersen and Horster in order to ensure anonymity of users. However. Petersen and Holster's scheme should register a pseudonymous key pair at TTP (One-time) every time so that users create the signature which is satisfied with unlinkability property In this paper, we propose a new anonymous rights trading system using group signature. This paper has a meaning having applied to digital rights trading system an efficient smart card based group signature.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.327-353
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• 2022

With the development of technology and media and the pursuit of non-face-to-face due to the corona pandemic, the influence of live commerce, a real-time streaming shopping channel, is growing. Starting from China, the popularity of live commerce is growing all over the world, and it has become an interesting topic among many practitioners and researchers. However, compared to its popularity, there are few studies on live commerce. Therefore, we build a theoretical model in terms of IT affordance such as visibility, guidance shopping, trading, and meta-voicing and investigate how live commerce affects engagement with customers. We empirically measure 428 individuals who have used live commerce using survey data. In addition, we conduct four types of scenario experiments on whether social cues on exposures of other consumers, influence customer engagement. Our results show that trading affordance has the most significant effect. This shows that the live commerce platform may want to devise a program that helps make payment easier for users who prefer a quick and simple process. Our study contributes to the literature by presenting the importance of IT affordance for live commerce.

• Knowledge Management Research
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• v.12 no.4
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• pp.41-54
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• 2011

Given the prevalence of home trading systems, it has become important to examine user behaviors in a stock investment environment. In this vein, this paper developed an integrated model to deeply understand the key determinants of user's continuance intention to use investment information through constructs prescribed by incorporating trust and perceived risk into expectation-confirmation model. The proposed research model was tested by using survey data collected from 160 users who have experience with stock investment. PLS (partial least squares) was employed for the analysis of the data. The findings of this study showed that the proposed framework provides a statistically significant explanation of the variation in continuance intention to search investment information. The findings revealed that trust and perceived risk are more prevalent predictors of continuance intention to use investment information compared to perceived usefulness. It was also found that user satisfaction serves as the salient antecedents of continuance intention to use investment information. The theoretical and practical implications of the findings were described.

• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.1-12
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• 2000

Since Black Monday there has been a rash of systems developments which aimed at automating and upgrading the surveillance mechanism of monitoring the many facets of security trading. A more sophisticated mathematical model for detecting abnormal trading activities was created by Davis and Ord of Penn State along with Nobel prize laureates Solow and Modigliani of MIT. They used CAPM(Capital Asset Pricing Model) to explain the movements of stock price and applied an idea of residuals to detect unusual movements. In this paper, their idea is discussed and a new method is proposed, which involves a confidence interval of future observation in linear regression. One of the examples of the stock watch system adopting this statistical method is also presented.

• The Journal of Information Technology
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• v.3 no.4
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• pp.23-40
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• 2000

Because the international trading community has witnessed a number of significant technical and commercial changes, documentary credit practices will quite clearly need to be updated to meet both the business and technical demands of the latest commercial and technical developments in international trade. The potential for developing "paperless credit" should, therefore, be examined. TradeCard is a B2B(business-to-business) e-commerce infrastructure that enables buyers and sellers to conduct and settle international trade transactions securely over the Internet and objective of TradeCard is to provide a secure, reliable cost-effective and user-friendly solution for conducting and settling international trade transactions. This paper analyzes the reviews of TradeCard by Electronic Message and the various problems which come to application of TradeCard, with particular attention to existing international frameworks for Payment systems based on Documentary Credit.ry Credit.

• IE interfaces
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• v.24 no.4
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• pp.379-386
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• 2011

The importance of renewable energy technology is discussed and next generation power transmission networks, which is called the smart grid, are constructed in developed countries. However for construction and operation of the smart grid, it is required not only to develop the electrical power generation technologies and transmission equipments but also to study systematic analysis and optimization for design and operation of the smart grid. In this paper we study electrical power trade in the smart grid using operations research models and simulation methods. We also consider future electrical power exchange markets in Korea and build four scenarios and the related optimization and simulation models, which reflect electrical power transaction pricing strategies of stake-holders. We can also simulate electrical power exchange market and analyze the results of electrical power trading, which can give us some insights for future electrical power exchange market.

• IE interfaces
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• v.16 no.spc
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• pp.123-126
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• 2003

In this paper, we use three cluster algorithms (K-means, Self-Organizing Map, and Fuzzy K-means) to find proper graded stock market brokerage commission rates based on the cumulative transactions on both stock exchange market and HTS (Home Trading System). Stock trading investors for both modes are classified in terms of the total transaction as well as the corresponding mode of investment, respectively. Empirical analysis results indicated that fuzzy K-means cluster analysis is the best fit for the segmentation of customers of both transaction modes in terms of robustness. We then propose the rules for three grouping of customers based on decision tree and apply different brokerage commission to be 0.4%, 0.45%, and 0.5% for exchange market while 0.06%, 0.1%, 0.18% for HTS.

• Journal of Korea Port Economic Association
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• v.19 no.2
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• pp.221-239
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• 2003

In the last decade, the issue of supply chain management(SCM) has emerged as a significant topic in the logistics literature in the developed countries. Also recently the concept of SCM has generated considerable interest in korean firms. However, there has been little systematic analysis of the experience of those companies that have used such SCM philosophy. This paper studies introduction and Application of Korean Trading Companies using SCM philosophy. This study forcuses on how Korean firms can use the SCM by reinforcing their logistics systems. The objectives of this paper are. 1. To develop an understanding of the forces that have created an interest in SCM. 2. To examine the obstacles encountered in implementing SCM. 3. To suggest the impact of the use of SCM and the directions for institutional Development.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1431-1436
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• 2018

We study the scaling of the price fluctuation in the Korean housing market. From the numerical analysis, we show that the normalized return distribution of the housing price, P(r), has a fat-tail and is well approximated by a power-law, $P(r){\sim}r^{-({\alpha}+1)}$, with ${\alpha}{\simeq}3$ for the whole data set. However, if we divide the data into groups based on the trading patterns, then the value of ${\alpha}$ for positive tail and negative tail can be different depending on the trading patterns. We also find that the autocorrelation function of the housing price decays much slower than that of the stock exchange markets, which shows a unique feature of the housing market distinguished from the other financial systems.