• East Asian Economic Review
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• v.23 no.2
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• pp.149-168
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• 2019

Public information arrivals and their immediate incorporation in asset price is a key component of semi-strong form of the Efficient Market Hypothesis. In this study, we explore the impact of public information arrivals on cryptocurrency market via Twitter posts. The empirical analysis was conducted through various methods including Kapetanios unit root test, Maki cointegration analysis and Markov regime switching regression analysis. Results indicate that while in bull market positive public information arrivals have a positive influence on Ripple's value; in bear market, however, even if the company releases good news, it does not divert out the Ripple from downward trend.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.1-9
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• 2022

Recently, a large number of cryptocurrencies and block chains have been continuously released. However, these cryptocurrencies and block chains are open to users without authorized verification and testing procedures, causing various reliability problems. Existing cryptocurrencies and blockchain test methods build a blockchain Testnet for a certain period of time by the developer without external verification by a third party, and after repeatedly self-testing and self-operating processes, commercialization is in progress by switching to the Mainnet. This self-verification method does not guarantee objectivity and publicness, and high reliability of customers cannot be realized. This study proposes a cryptocurrency and blockchain test interface and test control system as a third-party open test method.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.22-26
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• 2018

In this paper, we propose a model that classifies different transaction information by clustering and learning through similarity and transaction pattern of cryptocurrency transaction information. By using characteristics of genetic algorithms, we can get better clustering performance by eliminating unnecessary elements in clustering process. The transaction information including the clustering value is set as the training data, and the transaction information can be predicted through the classification algorithm. This can be used to automatically detect abnormal transactions from various transaction information of the cryptocurrency.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.433-439
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• 2021

The purpose of this research is to discuss the concept of measuring cryptocurrency literacy, especially Bitcoin. This research uses a qualitative approach. The data source comes from a literature review on cryptocurrency and opinions from Bitcoin academics, traders, and investors. Data collection was conducted through desk evaluations and interviews to determine what attributes should be considered for assessing Bitcoin literacy. The results of a literature review reinforced by discussion show that eight attributes can be used to assess basic level Bitcoin literacy, namely Bitcoin supply, regulatory guarantees, transaction recording, the role of third parties, treatment of transfer transactions, initial coin offerings, the smallest Bitcoin unit, and conversion with another currency. These eight attributes can be used to measure Bitcoin literacy through various questions with the choice of true, false, and do not know answers. This research is essential because there is no method to measure Bitcoin literacy. This research can be a measuring tool that becomes a reference or standard in assessing or measuring Bitcoin literacy. This study's results provide benefits to the development of science in the form of a tool that can be used to assess Bitcoin literacy and become a standard in assessing a person's level of understanding of Bitcoin.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.77-83
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• 2021

The dependency on technology has increased with the increase in population. Technology plays a crucial role in facilitating, organizing and securing people's life nowadays. The Internet has penetrated every face of present-day lifestyles. Yet another ubiquitous use of digital technology today is evident in transferring money and speeding cross border payments that are done through digital transactions. This paper investigates transferring money and data through banks and companies by using the Blockchain concept through decentralized distributed system. The present research also peruses several contexts in which this technology has already been implemented successfully and demonstrates the advantages of replacing the paper money with digital money. Using cryptocurrency will facilitate people's life by reducing time, securing the process of money transfer, and increasing data integrity. The primary benefit of this content analysis is that it addresses an innovative subject, in a new light and using timely recent research references drawn from 2018-2020. Thus, our study is a contemporary and conclusive source for all present and future endeavours being undertaken in the domain of using blockchain for e-transactions.

• International Journal of Contents
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• v.17 no.1
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.21-26
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• 2023

Recently, cryptocurrencies such as Ethereum and Bitcoin, which are called digital assets, Cryptocurrency has completely different characteristics from real assets and must be handled carefully and safely. But The disadvantage of digital assets is that anyone who knows the private key of the wallet can easily steal the digital assets. If the seed card is lost, stolen, or exposed when used, you can use the wallet by recovering the private key using the seed card acquired by someone else. In this paper We aim to safely protect encrypted assets by using QR codes when providing mnemonic words needed to create seed cards.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.52-57
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• 2022

In this study, keywords from representative online portal sites such as Naver, Google, and Youtube were collected based on text mining analysis technique using Textom to check the changes in metqaverse after COVID-19. before Corona, it was confirmed that social media platforms such as Kakao Talk, Facebook, and Twitter were mentioned, and among the four metaverse, consumer awareness was still concentrated in the field of life logging. However, after Corona, keywords from Roblox, Fortnite, and Geppetto appeared, and keywords such as Universe, Space, Meta, and the world appeared, so Metaverse was recognized as a virtual world. As a result, it was confirmed that consumer perception changed from the life logging of Metaverse to the mirror world. Third, keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above.

• Journal of Information Technology Applications and Management
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• v.29 no.2
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• pp.17-25
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• 2022

Although the two types of currencies compete, the possibility of a virtual currency price bubble is diagnosed by assuming an economic model with currencies (won, virtual currency) that are intrinsically worthless. The won is supplied by the central bank to achieve the price stability target, while the supply of virtual currency increases by a fixed number. According to the basic price theory equation, as a simple proposition, cryptocurrency prices form a Martin Gale process [Schilling and Uhlig, 2019, p.20]. Based on the existing theoretical proposition, we applied the variance ratio verification method [Linton and Smetanina, 2016] and a simple technical chart method for empirical analysis. For the purpose of this study, the possibility of a bubble was empirically analyzed by analyzing the price volatility formed in the Korean virtual currency market over the past year, and brief policy implications for this were presented.