• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.615-629
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• 2020

Conducting Focus Group Interview (FGI), this study examined the roles and discourses of cryptocurrency's online communities and media (legacy media and YouTube), and based on this, the study proposed the direction of cryptocurrency policy. By reviewing previous literature, this study analyzed the characteristics of investors, the online community, and YouTube, which is an investment environment factor. The study figured out the purpose of use and role of the community via interviews with cryptocurrency professional investors and online community members and analyzed main discussion themes of the five top-ranked YouTube channels related to cryptocurrency with the highest number of subscribers. The results suggested that cryptocurrency's investment was led by those who are in their 20s and 30s, the investors preferred and trusted information on new media than legacy media. The online community played the role of emotional homogeneity and empathy, and YouTube mainly performed the informational role. As a result of discourse analysis and interviews, this study argued that the legal stability of cryptocurrency's policy and protection of individual investors are needed. This study's significance indicates that it used various research methods such as literature research, interviews, content analysis of community/YouTube to analyze the informational role and emotional aspects of new media and suggested policy direction of the digital new deal blockchain technology and the fairness of financial industry.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.113-123
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• 2018

There are no studies related to the cryptocurrency exchange, unlike the explosive topic and the active transaction of the cryptourrency around the world. In this study, variables were constructed based on the previous researches to examine the effects of e-service qualities(information quality, transaction quality, design quality, safety quality), satisfaction and continuance intention of cryptocurrency exchange. The samples consist of 180 survey data drawn from the users of cryptocurrency exchange. The collected data were analyzed by SPSS 24.0 and AMOS 21.0. According to results of the reliability and validity test, all were found reliable, and all items were included. As a result of hypothesis testing through path analysis, First, the e-service qualities (information quality, transaction quality, design quality, safety quality) of the cryptocurrency exchange showed positive effects on satisfaction at the significance level of 1% and 5%. Second, e-service qualities (information quality, transaction quality, design quality, safety quality) of the cryptocurrency exchange were found to have positive effects on continuance intention at the significance level of 1% and 5%. Third, the satisfaction of the cryptocurrency exchange has a positive effect on continuance intention at 1% level of significance.

• 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.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.111-121
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• 2021

This study aims to provide implications for future research on cryptocurrency through examining domestic research trends in cryptocurrency. As a result of the study, domestic research on cryptocurrency has been in full swing since 2018, but research is still lacking, with a total of 30 academic papers and 14 dissertations. By detailed topic, research on legal, taxation and market aspects is relatively more than research on acceptance. In this study, research on legal, taxation, crime, market, and acceptance, which are classified as research topics, will have academic value, and future research on virtual currency needs to be actively conducted.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.694-706
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• 2019

In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.

• Journal of Smart Tourism
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• v.2 no.4
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• pp.5-10
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• 2022

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is everywhere. This research explores whether and how travelers' upfront exposure to a CAPTCHA influences their subsequent behaviors. In the travel decision-making context, we investigated the relationship between CAPTCHA and travelers' hotel preferences and intent to use cryptocurrency during the trip. In two experimental studies, we found that travelers exposed to a CAPTCHA (vs. not) preferred a robot-staffed to a human-staffed hotel (Study 1) and a pro-environmental to a quality hotel (Study 2). Exposure to a CAPTCHA also influences travelers' intent to use cryptocurrency during travel (Study 2). Preference for a pro-environmental hotel does not depend on the formats of CAPTCHA ("I am not a robot" or "I am human") while intent to use cryptocurrency is higher when travelers were exposed to the "I am not a robot" than "I am human" CAPTCHA. The results of two exploratory studies suggest several potential mechanisms by which CAPTCHAs affect travelers' behaviors and call for more research on this topic.

• East Asian Economic Review
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• v.27 no.3
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• pp.213-242
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• 2023

This paper investigates whether the price of cryptocurrency is determined by the US dollar index, the price of investment assets such gold and oil, and the implied volatility of the KOSPI. Overall, the returns on cryptocurrencies are best predicted by the trading volume of the cryptocurrency both in-sample and out-of-sample. The estimates of gold and the dollar index are negative in the return prediction, though they are not significant. The dollar index, gold, and the cryptocurrencies seem to share characteristics which hedging instruments have in common. When investors take notice of the imminent market risks, they increase the demand for one of these assets and thereby increase the returns on the asset. The most notable result in the out-of-sample predictability is the predictability of the returns on value-weighted portfolio by gold. The empirical results show that the restricted model fails to encompass the unrestricted model. Therefore, the unrestricted model is significant in improving out-of-sample predictability of the portfolio returns using gold. From the empirical analyses, we can conclude that in-sample predictability cannot guarantee out-of-sample predictability and vice versa. This may shed light on the disparate results between in-sample and out-of-sample predictability in a large body of previous literature.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.7-12
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• 2024

To trade cryptocurrency, traders require a personal cryptocurrency wallet. Cryptocurrency itself using blockchain technology is guaranteed excellent security and reliability, so the threat of blockchain hacking is almost impossible, but the exchange environment used by traders for transactions is most subject to hacking threats. Even if transactions are made safely through blockchain during the transaction process, if the trader's wallet information itself is hacked, security cannot be secured in these processes. Exchange hacking is mainly done by stealing a trader's wallet information, giving the hacker access to the victim's wallet assets. In this paper, to prevent this, we would like to reconstruct the existing Hyperledger Fabric structure and propose a system that verifies the identity integrity of traders during the transaction process using whitelisting. The advantage is that through this process, damage to cryptocurrency assets caused by hackers can be prevented and recognized. In addition, we aim to point out and correct problems in the transaction process that may occur if the victim's wallet information is stolen from the existing Hyperledger Fabric.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.91-106
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• 2022

Cryptocurrency, stood out the sharp cost rising of Bitcoin has been spotlighted by means of the solution for stagflation because it is decentralized with an existing currency differently. Especially getting into 4th industrial revolution, technologies using block chain and internet of things have been used in the many fields, and the power of influence is also widespread. Nevertheless like a remark of Elon Musk of Tesla CEO, the problems of environmental contamination for cryptocurrency have been pointed out continuously and the most representative of them is an enormous electric usage as the use of fossil fuels. Also the amount generated of carbon dioxide result in the acceleration of global warming mainly based on the climate changes of earth if the existing mining method is continued. On the other hand, review researches have been conducted restrictively as the connection with environmental contamination as the mining of cryptocurrency. In this study, it intended to review problems for environmental contamination as the diversification of ecological system of cryptocurrency concretely. Upon investigation existing prior documents on the putting recent data first, the mining of cryptocurrency has affected on the environmental contamination conflicting with carbon neutrality as increasement of the electric usage and electronic wastes. And POS method without the mining process appeared, but it had a demerit collapsing a decentralization and then we met turning point on appearing various environmental-friendly cryptocurrency. Finally the appearance of cryptocurrency using new renewable energy acted on the opportunity of the usage maximization of energy storage apparatus and the birth of national government intervention. Based on these results, we mention clearly that hereafter cryptocurrency will regress if not go abreast the value of currency as well as environmental approach.

• Journal of Contemporary Eastern Asia
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• v.18 no.2
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• pp.1-8
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• 2019

The blockchain is still new and unfamiliar. But blockchain appears to shake an entire technology innovation system. Blockchain is rapidly drawing attention in that it will be able to fundamentally revolutionize industry ecosystem. While cryptocurrency transactions and market capitalization have been popular in mass media, several platform operators in non-cryptocurrency areas such as jewelry, social networks, and entertainment, are also moving to introduce blockchain technology in full swing. In this brief note, we intend to present integrated theoretical strands to summarize various prospects for blockchain technology. Further, we want to provide a reflection as to whether this new technology gives opportunities, challenges, or risks to future society. Particularly, we point out one of its alternative and promising adoption that gives way to new forms of decentralized and autonomous organizations (DAOs).