• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.1
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• pp.123-133
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• 2003

The specific objectives of the study were as follows: 1) To investigate the composition system (design, usability and interactivity) of web sites of textile exchange of B to B 2) To examine and valuate contents and marketing (announcement, satisfaction and variety of contents) of web sites of textile exchange of B to B. The data were collected from search engine, portal sites of evaluation, direct contact, interview over the phone with web master of concerned web sites and the result of analytical valuation of web sites. The results of this study were as fellows: 1) The Dongsung trading intended to mainly use their homepage as a inside communication place by intranet network. The Daechang trading was mainly using their homepage as a tool of expansion of their outside export market. The etextiler was selling their web solutions through homepage. The texcom was offering the web place and useful informations to trading companies in Asia. 2) The texcom consisted text with little image to speed up for loading and navigation for usability of users. The Dongsung trading made intranet network for communication and exchange of informations of company inside. The etextiler offered a booking menu to inquiry in homepage. The Daechang trading tried to give good impression from the introduction page at homepage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2658-2663
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• 2014

To minimize low latency and improve the processing speed of the stock trading system, various technologies have been introduced. However, expensive network equipment has limitation for improving speed of trading system. Also, it is true that there is not much advantage by introducing those kind of systems. In this paper, we propose a low-Latency SPT(Safe Proper Time) scheme for overcoming the stock trading system in a cloud. The proposed method minimizes the CPI in order to reduce the CPU overhead that is based on the understanding of the kernel. and this approach satisfies the data timeliness.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.135-143
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• 2021

Information has an essential role in decision-making for investors who will invest in financial markets, especially regarding the policies on the condition of COVID-19. The purpose of this study is to determine the market reaction to the information published by the government regarding the policy changes to the provisions of Trading Halt on the IDX in an emergency using the event study method. The population in this study was companies listed on the Indonesia Stock Exchange in March 2020; the sample selection technique was purposive sampling. Data analysis used a normality test and one sample T-test. The results of the study found that there were significant abnormal returns on the announcement date, negative abnormal returns around the announcement date, and significant trading volume activity occurring three days after the announcement. The existence of a significant positive abnormal return on the announcement date indicates that the market responds quickly to information published by the government. The practical implication of this research can be taken into consideration for investors in making investment decisions to analyze and determine the right investment options so that investors can minimize the risk of their investment and maximize the profits they want to achieve.

• Journal of Distribution Science
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• v.21 no.3
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• pp.123-134
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• 2023

Purpose: The no-contact and economic downturn caused by COVID-19 have further grown the used market. The second-hand trading industry has established itself as a popular consumption culture, leading to exponential growth in the size of the market. This study aims to identify the types of shopping motivation for used products targeting Korean consumers, and to examine the relationship between shopping motivations for second-hand transactions, consumption values, and re-use intentions. Research design, data and methodology: The first study was conducted on 63 used trading platform users and the second study was conducted on 441 used trading platform users to identify the types of consumers' motivation for shopping for used products. Results: As a result of the first study, the shopping motivation types of Korean used product consumers were classified into convenience motivation, economic motivation, hedonistic motivation, information Acquisition motivation, and free time utilization motivation. As a result of the second study, it was found that convenience motivation had the greatest influence on functional values and hedonic motivation had the greatest influence on emotional values, and that functional values had a great influence on platform reuse intentions. Conclusions: This study provides practical implications for the establishment of marketing strategies for used trading platforms and academic implications for research related to used trading.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.37-48
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• 2023

Purpose - This study aims to explore the influence of emotional discrepancies among investors on the cryptocurrency market. It focuses on how varying emotions affect market dynamics such as volatility and trading volume in the context of Bitcoin trading. Design/methodology/approach - This study involves analyzing data from Bitcointalk.org, consisting of 57,963 posts and 2,215,776 responses from November 22, 2009, to December 31, 2022. Tools used include the Linguistic Inquiry and Word Count (LIWC) software for classifying emotional content and the Python Pattern library for sentiment analysis. Findings - The results show that heterogeneous emotional feedback, whether positive or negative, significantly influences Bitcoin's intraday volatility, skewness, and trading volume. These findings are more pronounced when the underlying emotion in the feedback is amplified. Research implications or Originality - This study underscores the significance of emotional factors in financial decision-making, especially within the realm of social media. It suggests that investors and market strategists should consider the emotional landscape of online forums when making investment choices or formulating market strategies. The research also paves the way for future studies regarding the behavioral impact of emotions on the cryptocurrency market.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.86-91
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• 2018

This paper is a review of accounts balancing time in small distributed power trading platform using blockchain technology. First, the national VPP energy management system using the AMI applied to this study is introduced and then the accounts balancing time and process of the cryptocurrency coin payment which based on the power generation of pro-consumer certified by power big data analysis in a test bed environment is discussed. Futhermore the configuration of a power Big Data analysis system with GPU Fast Big Data that applies MapD to current lambda architecture is also introduced.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.498-508
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• 2003

In the field of finance, Trading System of Securities is a very vulnerable application when it faces any small problems just for one minute. Since Trading System changes its environment from mainframes to client/server, its safety becomes the most important factor. Even though most If systems are configured by general guidelines currently, Trading System is an exception that it is configured by specific and rather ad hoc guidelines in order to ensure its safe management. In this thesis, I will prove the validity of specific and ad hoc configuration in the environment of Trading Systems where I use both XA interface system and Non-XA interface to configure its system based on 3-Tier Client/server computing environment through middleware, TP-Monitor, in the X/Open DTP Model. In order to validate the Trading System, I will compare and analyze the error of data of an order and ability to restore using both XA and Non-XA interfaces while testing take-over scenario on the assumption of the system's failure.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.36-46
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• 2019

If stock market is efficient, any well-devised trading rule can't consistently outperform the average stock market returns. This study aims to verify whether the strategy based on bid-ask volume information can beat the stock market. I suggested a day trading strategy using order imbalance indicator and empirically analyzed its profitability with the KOSPI 200 index futures data from 2001 to 2018. Entry rules are as follows: If BSI is over 50%, enter buy order, otherwise enter sell order, assuming that stock price rises after BSI is over 50% and stock price falls after BSI is less than 50%. The empirical results showed that the suggested trading strategy generated very high trading profit, that is, its annual return runs to minimum 71% per annum even after the transaction costs. The profit was generated consistently during 18 years. This study also improved the suggested trading strategy applying the genetic algorithm, which may help the market practitioners who trade the KOSPI 200 index futures.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.259-264
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• 2021

Recently, as the number of used trading sites supporting used trading increases, users want to search for a variety of information in real time. This new change has enabled a new type of C2C (Commerce to Commerce) transaction in the e-commerce base. However, since each used trading site has its own characteristics, it is difficult to standardize the whole. Therefore, in this paper, we studied a system that provides the transaction data used by the user in real time and provides the desired information quickly. In this paper, we researched the crawler system necessary for the development of the integrated trading system for used goods through Internet e-commerce, and made it possible to provide information in the web environment desired by the user through the defined morpheme analyzer. Therefore, in this study, we designed a system that provides information desired by users without accessing various used goods sites.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.105-111
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• 2023

Recently, research on prediction algorithms using deep learning has been actively conducted. In addition, algorithmic trading (auto-trading) based on predictive power of artificial intelligence is also becoming one of the main investment methods in stock trading field, building its own history. Since the possibility of human error is blocked at source and traded mechanically according to the conditions, it is likely to be more profitable than humans in the long run. In particular, for the virtual currency market at least for now, unlike stocks, it is not possible to evaluate the intrinsic value of each cryptocurrencies. So it is far effective to approach them with technical analysis and cryptocurrency market might be the field that the performance of algorithmic trading can be maximized. Currently, the most commonly used artificial intelligence method for financial time series data analysis and forecasting is Long short-term memory(LSTM). However, even t4he LSTM also has deficiencies which constrain its widespread use. Therefore, many improvements are needed in the design of forecasting and investment algorithms in order to increase its utilization in actual investment situations. Meanwhile, Prophet, an artificial intelligence algorithm developed by Facebook (META) in 2017, is used to predict stock and cryptocurrency prices with high prediction accuracy. In particular, it is evaluated that Prophet predicts the price of virtual currencies better than that of stocks. In this study, we aim to show Prophet's virtual currency price prediction accuracy is higher than existing deep learning-based time series prediction method. In addition, we execute mock investment with Prophet predicted value. Evaluating the final value at the end of the investment, most of tested coins exceeded the initial investment recording a positive profit. In future research, we continue to test other coins to determine whether there is a significant difference in the predictive power by coin and therefore can establish investment strategies.