• 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.45-53
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• 2020

Past literatures have not studied the impact of real-world events or information on the return and volatility of virtual currencies, particularly on the COVID-19 event, day-of-the-week effect, daily high-low price spreads and information flow rate. The study uses the ARMA-GARCH model to capture Bitcoin's return and conditional volatility, and explores the impact of information flow rate on conditional volatility in the Bitcoin market based on the Mixture Distribution Hypothesis (Clark, 1973). There were 3,064 samples collected during the period from 1^st of January 2012 to 20^th April, 2020. Empirical results show that in the Bitcoin market, a daily high-low price spread has a significant inverse relationship for daily return, and information flow rate has a significant positive relationship for condition volatility. The study supports a significant negative relationship between information asymmetry and daily return, and there is a significant positive relationship between daily trading volume and condition volatility. When Bitcoin trades on Saturday & Sunday, there is a significant reverse relationship for conditional volatility and there exists a day-of-the-week volatility effect. Under the impact of COVID-19 event, Bitcoin's condition volatility has increased significantly, indicating the risk of price changes. Finally, the Bitcoin's return has no impact on COVID-19 events and holidays (Saturday & Sunday).

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.9
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• pp.143-154
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• 2021

This study aims to explore the dynamic conditional correlation (DCC) between ten Asian stock indexes, the US stock index, and Bitcoin by using the dynamic conditional correlation model. The time span of the daily data is between January 2015 to May 2021, the total observation is 1,116. DCC(1,1)-EGARCH(1,1) with multivariate t and normal distributions for the DCC and EGARCH models, respectively, outperforms other models by the goodness of fit values. Except for Bitcoin, we discovered that the majority of the securities' volatilities have a very high volatility persistence. Furthermore, the negative shocks/news have more impact on the volatilities than positive shocks/news in most of the cases, except the stock index of China and Bitcoin. Most of the correlation pairs exhibit higher correlation during the COVID-19 pandemic compared to the pre-COVID-19, except Hong Kong-The US and Malaysia-Indonesia. Moreover, the correlation between Asian stock indexes during the COVID-19 pandemic is statistically higher than the pre-COVID-19 pandemic. However, there are a few instances where the Hong Kong stock index and a few countries are identical. The result of correlation size shows the connectedness between Asian stock markets, which are well-connected within the region, especially with South Korea, Singapore, and Hong Kong.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.695-704
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• 2020

Bitcoin and other prominent cryptocurrencies have gained much attention since the last several years. Globally known as digital coin and virtual currency, this cryptocurrency is gained and traded within the blockchain system. The blockchain technology adopted in using the cryptocurrency has raised the eyebrows within the banking sector, government, stakeholders and individual investors. The rise of the cryptocurrency within this decade since the inception of Bitcoin in 2009 has taken the market by storm. Cryptocurrency is anticipated as the future currency that might replace the current paper currency worldwide. Even though the interest has caught the attention of users, many are not aware of its opportunities, drawbacks and challenges for the future. Researches on cryptocurrencies are still lacking and still at its infancy stage. In providing substantial guide and view to the academic field and users, this paper will discuss the opportunities in the cryptocurrency such as the security of its technology, low transaction cost and high investment return. The originality of this paper is on the discussion within law and regulation, high energy consumption, possibility of crash and bubble, and attacks on network. The future undertakings of cryptocurrency and its application will be systematically reviewed in this paper.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.171-179
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• 2021

In the international markets, financial variables can be volatile and may affect each other, especially in the crisis times. COVID-19, which began in China in 2019 and spread to many countries of the world, created a crisis not only in the global health system but also in the international financial markets and economy. The purpose of this study is to analyze the contagious effect of the COVID-19 pandemic on the volatility of selected financial variables such as Bitcoin, gold, oil price, and exchange rates and the connections between the volatilities of these variables during the pandemic. For this aim, we use the ARMA-EGARCH model to measure the impact of volatility and shocks. In other words, it is aimed to measure whether the impact of the shock on the financial variables of the contagiousness of the epidemic is also transmitted to the markets. The data was collected from secondary and daily data from September 2th 2019 to December 20th, 2020. It can be said that the findings obtained have statistically significant effects on the conditional variability of the variables. Therefore, there are findings that the shocks in the market are contaminated with each other.

• Journal of Distribution Science
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• v.17 no.11
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• pp.93-101
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• 2019

Purpose: Blockchain technology suggests ways to solve the problems in the existing industry. Among them, Cryptocurrency system, which is an element of Blockchain technology, is a very important factor for operating Blockchain. While Blockchain cryptocurrency has attracted attention, studies on cryptocurrency prices have been mainly conducted, however previous studies mainly conducted on Bitcoin prices. On the other hand, in the context of the creation and trading of various cryptocurrencies based on the Blockchain system, little research has been done on cryptocurrencies other than Bitcoin. Hence, this study attempts to find variables related to the prices of Dash, Litecoin, and Monero cryptocurrencies using machine learning techniques. We also attempt to find differences in the variables related to the prices for each cryptocurrencies and to examine machine learning techniques that can provide better performance. Research design, data, and methodology: This study performed Dash, Litecoin, and Monero price prediction analysis of cryptocurrency using Blockchain information and machine learning techniques. We employed number of transactions in Blockchain, amount of generated cryptocurrency, transaction fees, number of activity accounts in Blockchain, Block creation difficulty, block size, umber of created blocks as independent variables. This study tried to ensure the reliability of the analysis results through 10-fold cross validation. Blockchain information was hierarchically added for price prediction, and the analysis result was measured as RMSE and MAPE. Results: The analysis shows that the prices of Dash, Litecoin and Monero cryptocurrency are related to Blockchain information. Also, we found that different Blockchain information improves the analysis results for each cryptocurrency. In addition, this study found that the neural network machine learning technique provides better analysis results than support-vector machine in predicting cryptocurrency prices. Conclusion: This study concludes that the information of Blockchain should be considered for the prediction of the price of Dash, Litecoin, and Monero cryptocurrency. It also suggests that Blockchain information related to the price of cryptocurrency differs depending on the type of cryptocurrency. We suggest that future research on various types of cryptocurrencies is needed. The findings of this study can provide a theoretical basis for future cryptocurrency research in distribution management.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.465-471
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• 2021

The study investigates the dynamic correlation of cryptocurrencies and equity in Vietnam and tests the safe-haven property of them from the perspective of the stock market in Vietnam during the pandemic crisis by applying the dynamic conditional correlation (DCC) GARCH model and regression with a dummy variable, respectively. This study employs time series data on the daily dataset from September 2014 to September 2021 with the focus on the two most popular cryptocurrencies - Bitcoin and Litecoin. The results show that the dynamic conditional correlations between cryptocurrencies and equity in Vietnam increased during the pandemic, however, in most periods, positive dynamic correlations often dominate. Besides, the regression results also indicate that Bitcoin and Litecoin act as weak safe-haven investments for stocks in Vietnam during the COVID-19 turmoil. They are more suitable for diversification purposes although the dynamic correlations between them and the stock index in Vietnam vary stronger during the pandemic crisis than before. The findings of this study suggest that in the period of pandemic crisis, cryptocurrencies are not concerned as effective safe-haven assets for stock in Vietnam. Instead, cryptocurrencies are only playing a potential role in diversification benefit in this economy.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.51-56
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• 2020

Cryptocurrencies, including Bitcoin, has decentralization, distribution and P2P properties unlike traditional currencies relies on trusted central party such as banks. All transactions are stored transparently and distributively, hence all participants can check the details of those transactions. Due to the properties of cryptographic hash function, deletion or modification of the stored transations is computationally not possible. However, cryptocurrencies only provide pseudonymity, not anonymity, which is provided by traditional currencies. Therefore many researches were conducted to provide anonymity to cryptocurrencies such as mix-based methods. In this paper, I will propose more efficient hybrid mix-based method for anonymity than previous mix-based one.