This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies – Bitcoin, Ethereum, Litecoin, and EOS – and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies – AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet – representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning- based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

This study investigates social media posts on Twitter concerning cryptocurrency marketing. We applied unsupervised Latent Dirichlet Allocation (LDA) topic modeling and sentiment analysis techniques to 98,716 tweets to examine the Twitter content for subjects and sentiments related to cryptocurrency. We discovered that tweets about cryptocurrency fell into four categories, with “cryptocurrency trading,” “NFT airdrop,” “cryptocurrency affiliate program,” and “Dogecoin on social media” being the most popular. Most of the topics had positive sentiments. Theoretical and practical implications for developing cryptocurrency marketing communication strategies are discussed.

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.

Cryptocurrency transactions are subject to private law regulations. This article reviews the legal nature of cryptocurrency from the perspective of general civil law theory. The undeniable nature of property in cryptocurrency has led to an increased demand for judicial systems to effectively operate in regards to cryptocurrency. The right to cryptocurrency cannot be regarded as intellectual property rights. Cryptocurrency cannot also be regarded as a bond, as it is merely units of information listed in the distributed ledger with no counterparty. Cryptocurrency can be understood as an “things” under civil law because there is a possibility of management through an electronic wallet private key and also independence through a distributed ledger. Among the requirements of an things, the requirement of ‘corporeal things’ or ‘natural force’ can be flexibly interpreted in regards of transactions between related parties. On the other hand, cryptocurrency cannot be regarded as “money” among things. Cryptocurrency cannot function as a “measure of value”, which is a fundamental function of money, due to its inherent nature of volatility and price differences between its exchanges. As a result, the legal nature of cryptocurrency can be recognized as a things, not money, through which current existing judicial systems such as compulsory execution law and bankruptcy law becomes able to operate in regards to cryptocurrency, ultimately promoting legal predictability. However, legislation on cryptocurrency should ultimately be completed through legislation, not interpretation. This requires further in-depth discussion in academic and practice sectors.

There is no single approach in the world regarding the legal regulation of cryptocurrency. Most countries are wary of legalizing this payment instrument, fearing problems associated with tax evasion, terrorist financing, fraud and other illegal transactions. Nevertheless, the issue of legalization of cryptocurrencies has recently moved to a different level as the market capitalization of cryptocurrencies grew to over USD 237 billion 2020, with several leading cryptocurrencies such as Bitcoin skyrocketing in value in 2021. The explosive growth has been lead in no small part by China, the world’s largest and most important market for cryptocurrency in terms of mining, investing and research. This article reviews the current trends in cryptocurrency regulation with a particular focus on China, including an analysis of current cryptocurrency laws in China, as well as the new Chinese Cryptography Law. Also, it explains recent developments in Chinese regulation and policy will continue to shape the development of the global cryptocurrency markets.

The cryptocurrency market has received immense consideration in media and academia since the beginning of 2013 because of its huge price fluctuation. This study focuses on Arab investors who invest in the cryptocurrency market by investigating the influence of behavioral finance factors on investment decisions in the cryptocurrency market. A quantitative approach was used by employing a snowball sampling method through 112 questionnaires. The results show that herding theory, prospect theory, and heuristic theory have a significant effect on investors’ investment decisions in the cryptocurrency market. This emphasizes the significant role of the proposed behavioral factors as determinants of the investors’ investment decisions. This study contributes to the existing research by consolidating the results of different researches in this study. It also contributes to the investors’ understanding of the dynamics of the cryptocurrency market and it enhances the ability to make informed decisions based on their understanding. The implication of the findings will prepare hit and run investors to be progressively prepared to stay in the cryptocurrency market and develop their abilities on the most proficient method to settle on sound venture choices. Furthermore, the findings of this study will encourage financial specialists to realize that information on the traditional finance theory is not adequate to excel in the cryptocurrency market.

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 study investigates herding behavior in cryptocurrencies in different situations. This study employs daily returns of major cryptocurrencies listed in CCI30 index and sub-major cryptocurrencies and major stock returns listed in Dow-Jones Industrial Average Index, from 2015 to 2018. Quantile regression method is employed to test the herding effect in market asymmetries, inter-dependency and intra-dependency cases. Findings confirm the presence of herding in cryptocurrency in upper quantiles in bullish and high volatility periods because of overexcitement among investors, which lead to high volume trading. Major cryptocurrencies cause herding in sub-major cryptocurrencies, but it is a unidirectional relation. However, no intra-dependency effect among cryptocurrencies and equity market is observed. Results indicate that in the CKK model herding exists at upper quantile in market that may be due when the market is moving fast, continuously trading, and bullish trend are prevailing. Further analysis confirms this narrative as, at upper quantile, the beta of bullish regime is negative and significant, meaning the main source of market herding is a bullish trend in investment, which increases market turbulence and gives investors opportunity to herd. Also, we found that herding in cryptocurrencies exits in high volatility periods, but this herding mostly depends on market activity, not market movement.

Purpose – The purpose of the research is to assess the current state of cryptocurrency in Vietnam and to provide several solutions and recommendations to the Government, the State Bank of Vietnam (SBV) and other relevant agencies for monitoring, managing, and controlling cryptocurrency effectively and efficiently. Research design, data and methodology - The study is based on the assessment and analysis of cryptocurrency in the world and the real situation of cryptocurrency in Vietnam in order to provide solutions to the controllable development of operation of this currency. Results - The study indicates the current operations of cryptocurrency in Vietnam and provides several suggestions to effectively control this currency. Conclusion - According to the study on current cryptocurrency and the situation of cryptocurrency in Vietnam, the author has proposed a number of solutions to provide suggestions to manage and develop the operations of cryptocurrency in a most practical manner. The governments of many countries in the world, including the Government of Vietnam, need more time as well as appropriate technology improvements to take advantage of these new digital currencies; therefore, they still need to ensure safety in compliance with the control and regulatory capabilities of the central government and central banks.