• 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.251-257
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• 2020

The study investigates the role of commodity prices and tax purpose recognition on bitcoin prices. Since the introduction of bitcoin in 2008, emphasis has focused on economists, policy-makers and analysts drastically increasing bitcoin's accessibility and commodity values (Dumitrescu & Firică, 2014). This study employs GARCH and EGARCH from ARCH/GARCH family on daily nature data. We measure the volatile behavior of bitcoin by employing auto-regressive conditional heteroscedasticity model with the aim to explore the relationship between major commodities and bitcoin volatility. We focus on major commodities like gold, silver, platinum, and crude oil to be regressed with bitcoin. The daily prices of commodities were retrieved from www.investing.com and bitcoin prices from www.coindesk.com for the period from 29April 2013 to 16 October 2018. Results confirmed the currency's long-term volatile behavior, which is due to its composition and market dynamics, whereas the existence of asymmetric information effect is not confirmed. Tax recognition by other countries may in future help in controlling the volatility as bitcoin is not a country-specific security. But, only silver impacts on volatility in comparison to oil prices and platinum, which is due to its similar features with gold. Eventually, bitcoin can be used for risk diversification and money making.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.1009-1019
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• 2018

Bitcoin is the first application utilizing the blockchain, but it has limitations in terms of scalability. The concept of Lightning Network was recently introduced to address the scalability problem of Bitcoin. In this paper, we found that the real-world Bitcoin Lightning Network shows the scale-free property. Therefore, the Bitcoin Lightning Network can be vulnerable to the intentional attacks targeting some specific nodes in the network while it is still robust to the random node failures. We experimentally analyze the robustness of the Bitcoin's Lightning Network via the simulation of network attack model. Our simulation results demonstrate that the real-world Lightning Network is vulnerable to target attacks that destroy a few nodes with high degree.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.717-727
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• 2018

When illegal transactions are made with bitcoin, it's not easy to track all the bitcoins used in the transaction and seize them. Especially, if criminals distribute illegal transactions by spreading them to several bitcoin addresses, it's difficult to track hidden bitcoins other than confiscated bitcoins even if some bitcoins are confiscated. This paper proposes a method for tracking and monitoring all bitcoin transactions suspected of illegal transactions. This method estimates bitcoin addresses that are highly relevant to crime among all bitcoin addresses that dealing with the address based on the bitcoin address list of the alleged crime, and keeps track of addresses that are relevant to crime and help to investigate illegal bitcoin transaction.

• Journal of Distribution Science
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• v.16 no.12
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• pp.47-56
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• 2018

Purpose - The potential use of cryptocurrencies in a retail environment proposes a rapid shift from the traditional financial system. Nakamoto(2008) defines Bitcoin as an open source alt-coin based on the blockchain technology. Luther(2016) insists that the new technology will be widely adopted for the digital payment processes. However, the use of Bitcoin is in the real world is still sparse. Despite the growing attention and purported benefits, it is doubtful whether the Bitcoin will be eagerly accepted by ordinary consumers in the mainstream market. To answer this question, this paper develops a causal model that has a dual path to explain the motivation to adopt Bitcoin. According to Glaser, Zimmermann, Haferkorn, Weber, and Siering(2014), Bitcoin is both an asset and a currency at the same time. In summary, the attitude towards Bitcoin may vary depending on whether the fin-tech product is viewed as an asset or as a currency. Based on the arguments, we propose that asset attitude and currency attitude will give influence to consumers' intention to adopt Bitcoin. Research design, data, and methodology - Quantitative data collection is conducted from a Bitcoin SIG(special interest group) working in an internet community. As a result, 192 respondents who know Bitcoin completed the survey. To analyze the causal relations in the research model, PLS-SEM(partial least squares structural equation modeling) method is used. Also, reliability and validity of measures are tested by performing Cronbach's alpha test, Fornell-Larcker test and confirmatory factor test. Results - Our test results show that every hypothesis is supported except the influence of perceived ease of use. In addition, we find that the relationships between constructs are different between the high innovative group and low innovative group. Conclusions - We provide evidence that asset attitude and currency attitude are key antecedents of Bitcoin adoption.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.1-9
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• 2017

Recently, Bitcoin which is digital currency and cryptocurrency is getting worldwide attention since Bitcoin has an ability to replace legal tender unlike other existing cyber currency. Especially, most Bitcoin trading is done between two traders such as P2P method and it does not require a third-party to make sure reliability and it records every transaction details, so it is more transparent then traditional financial trade, so the number of users is increasing. However, Bitcoin, which has been recognized for transparency, confidentiality and stability among traders has recently been threatened by illegal transactions such as money laundering and the attack on the exchange. These threats to Bitcoin are becoming social problems. At first, it seems that most of the digital currency is difficult to get hacked due to the Blockchain technology. However, threats such as digital money leaks by user account hacking and paralyzing the servers are increasing. In this paper, it will examine the features of the Bitcoin and the threatening elements to secure marketability of digital currency such as Bitcoin and receive more interest from public in domestic. The paper will examine the problems of Blockchain technology on speculative transactions and fraudulent behavior by analyzing the problems of Bitcoin transaction. Lastly, it will propose ways to make transparent and secure digital currency transactions.

• KNOM Review
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• v.22 no.1
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• pp.68-76
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• 2019

Bitcoin, based on the blockchain technology is an online crypto-currency developed by Satoshi Nagamoto. Bitcoin, which was first issued on January 3, 2009, is rapidly evolving with increasing number of transactions. However, untoward incidents are occurring due to an increase in the number of Bitcoin transactions. Predicting the number of Bitcoin transactions is important to prepare for any issues that can occur in the Bitcoin network. This paper proposes to design model for predicting the number of Bitcoin transactions by applying two machine learning algorithms and then a model for predicting the number of Bitcoin transactions through experiments.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.109-118
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• 2019

As a result of the United States (U.S) -China trade conflict, the recent instability of the stock market has led many people to invest in Bitcoin, a commodity that many previous studies have interpreted as a safe asset. However, recent Bitcoin market price fluctuations suggest that the asset's stability stems from speculative purchasing trends. Therefore, classifying the characteristics of Bitcoin assets can be an important reference point in analyzing relevant accounting information. To determine whether Bitcoin is a safe asset, this study analyzed the correlation between Bitcoin and economic indicators to verify whether gold and Bitcoin responded similarly in time series analyses. These show that the regression explanatory power between the price of gold and bitcoin is low, thus no relation between the two assets could be drawn. Additionally, the Granger causality analyses of six individual economic variables and Bitcoin did not establish any notable causality. This can be interpreted that short-term price fluctuations have a significant impact on the nature of Bitcoin as an asset.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1287-1295
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• 2021

During the past decade, it seems apparent that Bitcoin has been the best performing asset class. Even without a centralized authority that takes control over, Bitcoin, which started off with basically no value at all, reached around 65000 dollars in 2021, showing a movement that will definitely go down in history. Thus, even those who were skeptical of Bitcoin's intangible nature are stacking bitcoin as a huge part of their portfolios. Bitcoin's exponential growth in value also caught the attention of traditional banking and investment firms. Along with the spotlight Bitcoin is getting from the investment world, research using macro-economic variables and investor sentiment to explain Bitcoin's price movement has shown progress. However, previous studies do not make use of On-Chain Data, which are data processed using transaction data in Bitcoin's blockchain network. Therefore, in this paper, we will be utilizing LSTM, a method widely used for time-series data prediction, with On-Chain Data to predict the price of Bitcoin.