Cryptocurrency Research Articles

Addressing Gender Stereotyping in the Emergent World of Block-Chain and Cryptocurrency Administration

The study seeks to address the gender gap in the crypto world by exploring strategies for promoting financial literacy, creating opportunities for women in the industry and addressing the “bro culture”. Several empirical evidence has been done by researchers which indicates that men are more interested in crypto currencies than women. This work will show how crypto currency-based approaches to development interact with gender, which are part of neoliberal beliefs about entrepreneurialism, financial inclusion, and gender roles. Block-chain technology has the potential to address gender inequality. The research methodology borders around the use of descriptive methods of analysis and content analysis. The work attempts to look into the rise of decentralized finance, specifically block chain-based applications and calls for a more feminine-friendly analysis. Findings by Gemini’s State of US Crypto report showed that women make up only 26% of the investors in the space. Forex analyzed the top 50 crypto company founders to find only 6% of these have female CEOs. The World Bank explores how block chain can be leveraged to advance gender equality, particularly in the context of humanitarian response and financial services. As such, the gender gap in the cryptocurrency world is a complex issue that requires a multifaceted approach to address. The study recommended that blockchain technology holds promise for promoting gender equality

Uncertain Regulations, Definite Impacts: The Impact of the U.S. Securities and Exchange Commission's Regulatory Interventions on Crypto Assets

This study employs an event study methodology to investigate the market impact of the U.S. Securities and Exchange Commission's (SEC) classification of crypto assets as securities. It explores how SEC interventions influence asset returns and trading volumes, focusing on explicitly named crypto assets. The empirical analysis highlights significant adverse market reactions, notably returns plummeting 12% over one week post-announcement, persisting for a month. We demonstrate that the severity of market reaction depends on sentiment and asset characteristics such as market size, age, volatility, and illiquidity. Further, we identify significant ex-ante trading volume effects indicative of pre-announcement informed trading.

Tax Treatment of Crypto Assets Under Serbian Law – Status Quo and Future Challenges

Abstract The present paper provides a comprehensive analysis of the legal framework relevant for the taxation of transactions and activities involving crypto assets in Serbia. In the introductory part, the author provides a classification of crypto assets intended to serve as the methodological framework within which the taxation of various transactions and activities in the crypto domain will be analyzed, taking into account the principle of tax neutrality. The core of the paper elucidates the results of comparative legal research that the author had undertaken in order to identify diverging approaches jurisdictions around the world embraced regarding the taxation of generation, acquisition, holding and disposal of crypto assets. The choices made by the Serbian tax policy makers are juxtaposed to those applicable in comparative jurisdictions and, where appropriate, improvements are suggested. The author concludes by commending the recent trend in the application of Article 9, para. 1 of the Law on Tax Procedure and Tax Administration as a tool that could mitigate the need for recurrent and, ultimately, unsuccessful tailoring of the tax legislation to the novelties in the crypto domain.

A Systematic Literature Review of Blockchain-Based Triple-Entry Accounting in Crypto Assets

The digital revolution in accounting is a major change that affects the way we view, manage, and report financial information. One form of the digital revolution in accounting is the emergence of blockchain technology and Triple-entry Accounting (TEA). This research aims to examine the application of triple-entry accounting with blockchain in the recording of crypto assets. This research uses a qualitative approach with a systematic literature review using the WATASE UAKE platform. This method summarizes research from many sources into specific topics based on items determined by the researcher. The results show that the application of blockchain technology can help achieve a country's economic development goals and can establish more secure, transparent, and efficient business practices by reducing various existing risks.

A Study on the Impact of Indian Taxation on Virtual Digital Assets in India

The study explores the implications of India's taxation policies on Virtual Digital Assets (VDAs), including crypto currencies and non-fungible tokens (NFTs). With the introduction of the Finance Act of 2022, which imposed a 30% tax on VDA profits and a 1% Tax Deducted at Source (TDS) on transactions, the digital asset landscape in India has undergone significant shifts. This research examines the economic and behavioural impact of these regulations on individual investors, start-ups, and the broader VDA ecosystem. The findings suggest that the flat tax rate and TDS have led to reduced market liquidity and deterred small-scale traders, highlighting challenges in compliance and record-keeping. However, these measures also formalize the VDA market, potentially attracting institutional investors by providing regulatory clarity. The study identifies gaps in the current policies and offers recommendations to balance regulation with market growth, ensuring a sustainable future for India's VDA sector.

A Study on the viability of Crypto currency (with reference to Bitcoin) – As an alternative future investment option.

Some concepts become economically relevant as new technologies emerge, as is the case with cryptocurrencies in general, or Bitcoin and Ethereum in particular. Because of the importance of these tools, a thorough bibliometric study that allows us to obtain all information about cryptocurrencies is required. This study will aid related research that has been and is currently being conducted. The bibliometric analysis includes 11 articles that highlight the most related papers, research fields, countries, organizations, authors, publications, and trends over the last few years. Finally, the number of papers published has increased over the last three years. The analysis depicts the evolution of blockchain technology, which is used in this type of cryptocurrency. And finally, it will help the reader to find the answer to the research Question

Optimizing Bitcoin Price Prediction with LSTM: A Comprehensive Study on Feature Engineering and the April 2024 Halving Impact

This research aims to develop a Bitcoin price prediction model using machine learning techniques, with a specific focus on Long Short-Term Memory (LSTM) neural networks. The Bitcoin market is characterized by unique features such as high volatility and the influence of various external factors, which differ significantly from traditional financial markets. As such, precise feature engineering is crucial for accurately modelling Bitcoin prices. Utilizing historical Bitcoin price data from 2014 to 2023, this study extensively evaluates LSTM models. The results indicate that LSTM models provide highly accurate predictions, with a Mean Squared Error (MSE) of 0.0001798 and a Mean Absolute Error (MAE) of 0.0101322. These results demonstrate that LSTM effectively captures the complex and dynamic patterns of Bitcoin prices, outperforming other methods. The findings have significant implications for financial market analysis, especially within the rapidly evolving domain of crypto assets. By leveraging machine learning methodologies, this research enhances understanding of the complexities of the crypto market and offers potential strategies for smarter investment decisions. The success of the LSTM model in improving Bitcoin price prediction accuracy underscores its importance in navigating the volatile and dynamic nature of the crypto market. Overall, this study highlights the substantial potential of machine learning approaches, particularly LSTM models, in analyzing and predicting crypto market behavior. It contributes to the growing academic discourse on the application of advanced technologies in finance and can stimulate further discussions on how machine learning can address challenges and opportunities in the crypto market.

Determinants of Crypto Investment Decisions: Ra-tional Behavior or Irrational Behavior?

The current phenomenon is that crypto asset investment is considered high risk, yet the number of crypto asset investors is increasing. This research investigates the determinants of crypto investment decisions: driven by rational or irrational behavior, specifically testing the moderating role of social influence on the determinants of investment decisions. The research combines technological factors (crypto platforms) and psychological factors (herding behavior FOMO (Fear of Missing Out)) with external factors of social influence a moderating variable. This study uses quantitative research methods and primary data from respondents who are crypto asset investors domiciled in Indonesia. The sample consisted of 124 respondents consisting of 95 male respondents and 29 female respondents. Statistical analysis including analysis of the Outer Model, Inner Model and direct effect and Moderated Regression Analysis was carried out using SmartPLS 0.3 software. The results showed that crypto platforms, financial literacy, herding behavior, FoMO had an effect on investment decisions, and social influence was able to moderate the influence of crypto platforms, financial literacy, herding behavior, FoMO on investment decisions. Suggestions given for further research are: develop further research models that can represent the determinants of investment decisions in crypto by using other research variables in predicting their influence on investment decisions such as regret experience, attitude, risk tolerance, etc.

Asymmetric dynamic correlations and portfolio management between Bitcoin and stablecoins

ABSTRACT This study unveils the unique properties of crypto assets and investigates the dynamic connectedness between six prominent stablecoins and Bitcoin in comparison with Bitcoin/stablecoin pairs involving portfolio management. Empirically, using the DCC-GJR-GARCH and partial wavelet coherence approaches, we show that Bitcoin provides greater diversification potential benefits compared to stablecoins during the COVID-19 crisis. The evidence suggests that Bitcoin, as the dominant cryptoasset, can serve as a suitable asset for portfolio diversification against stablecoins. Besides, we evaluate potential hedging benefits of cryptocurrencies for market participants and find that stablecoins are poor hedging products in most of the cases considered. The optimal portfolio for the hedging strategy involving a mix of Bitcoin and stablecoins reveals that the weights assigned to stablecoins are lower than those for Bitcoin. In particular, our results provide timely implications for market participants whose crypto portfolios include stablecoins, especially after Terra’s collapse.

ESG crypto coins: speculative assets, or, the future of green money?

ESG crypto coins: speculative assets, or, the future of green money?

Good vs. bad volatility in major cryptocurrencies: The dichotomy and drivers of connectedness

Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. Our findings indicate that crypto connectedness reflects important events and oscillates substantially while reaching lower limit values when compared to traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that market downturns spill over substantially faster than comparable market surges. Overall, the connectedness dynamics are driven by a combination of both crypto (momentum, on-chain activity, off-chain activity) and legacy financial and economic (financial and economic uncertainty, and financial market performance) factors, while the asymmetry is more connected to the off-chain crypto activity and the combination of economic, financial, and monetary factors. In both the total connectedness and asymmetry modeling, these can serve as hands-on indicators to be further translated into specific portfolio re-balancing decisions, risk management, and regulatory frameworks.

Bitcoin's Effect on Selected Crypto Assets: Quantitative Evidence

The main objective of the study is to systematically investigate the effects of Bitcoin on specific crypto assets. In this context, a sample of 135 observations between 2020W01 and 2022W33 for seven crypto assets with the highest value in the financial markets, including Ethereum, Tether, USD Coin, BNB, XRP, and Cardano, has been included in the study sample. These crypto assets, along with Bitcoin, constitute almost 95% of the total crypto asset portfolio. This situation increases the importance of representing a broad universe in the study and contributes to the academic literature. To examine the effects of Bitcoin on the selected crypto assets, a Multivariate Dynamic VAR Model has been used. The model assumes causality among variables. Variables that do not meet this assumption have been excluded from the study sample. The results of the study demonstrate that Bitcoin exhibits significant and one-way effects on all cryptocurrencies. However, the impact of other crypto assets on Bitcoin has been negligible. In this context, it is emphasized that investment decisions obtained from two-way evaluations may be risky and misleading. In order to reduce investment risks for crypto assets to more acceptable levels, the use of comprehensive analysis methods is recommended.

The legal nature of crypto assets and its reflection in the civil and tax legislation of the Russian Federation

The article analyzes the legal nature of crypto assets in Russian legislation and the specifics of their taxation, focusing on the need to form a legal framework that promotes effective protection of the rights of participants in the turnover of crypto assets.The methodological basis of the research is the dialectical method, the formal logical method, the formal legal method and the method of interpretation of law.The lack of a unified terminology base in the field of digital economy in Russian legislation creates additional difficulties in creating comfortable conditions for the development of the crypto asset market. Currently used various terms such as “virtual assets”, “digital assets”, “crypto assets”, “cryptocurrency” are not fixed in the current legislation. At the same time, the terms existing in Russian legislation do not allow for effective regulation in the field of taxation and civil turnover, since they intentionally exclude the most common crypto assets from their scope. Without clear and unambiguous legal regulation, it is difficult to ensure proper control and taxation of transactions with crypto assets, which can lead to significant tax losses and a decrease in budget revenues.Moreover, the concept of “digital currency” used in Russian legislation does not correspond to the generally accepted meaning in international practice and is mainly considered in an economic context, rather than in a legal one. Such a discrepancy in terminology creates additional difficulties for participants in the cryptocurrency market and creates obstacles to the formation of an effective legal framework for the regulation of the digital economy. According to the results of the study, it was concluded that the current approaches to the development of the terminological apparatus of the regulation of crypto assets have flaws, since they allow for a mixture of concepts and do not imply the formation of a clear hierarchy. The definition of “the digital asset” is proposed for the purpose of filling existing terminological gaps in the current legislation.

Information diffusion in referral networks: an empirical investigation of the crypto asset landscape

Information diffusion in referral networks: an empirical investigation of the crypto asset landscape

Analyzing the energy markets and financial markets linkage: A bibliometric analysis and future research agenda

AbstractThis study has been conducted using 200 articles from 1984 to 2023, by undertaking a meta‐literature review on the subject of energy markets and financial markets linkage (EFML). Our study consists of content analysis of 200 articles along with other analyses such as (i) co‐citation analysis, (ii) co‐authorship analysis, and (iii) cartographic analysis. We have identified five research streams: (1) Oil, stock, commodities markets, crypto currency, real estate, exchange rate linkage; (2) Oil and stock market linkage; (3) Energy as a portfolio diversification tool; (4) Dynamic linkage between the oil‐commodity market and stock market; and (5) Oil and other market linkages with respect to the COVID‐19 pandemic, the subsequent financial crisis, and other events. We have performed a comprehensive review of the EFML literature and provided the influential aspects of top journals and authors, the characteristics of the most studied topics, past and current key research streams in the EFML literature. We have also suggested 63 future research questions. Looking at the widespread interest of finance scholarship in the area of energy market linkages, the assessment of energy market linkages, and possible portfolio diversification opportunities and benefits, is of great importance and interest to researchers, policy holders, and portfolio managers.

An Empirical Analysis of Tax Evasion among Companies Engaged in Stablecoin Transactions

This research investigates the relationship between stablecoin usage and tax evasion. We present a model that includes variables related to transactions such as intensity, frequency, environment on-chain (P2P) vs. off-chain (IntraVasp), and company characteristics such as age, sector, and size. Our model was empirically tested using a logistic regression based on data from the Brazilian Federal Revenue Service (Receita Federal do Brasil (RFB)) in 2021. This novel approach aims to understand the tax behaviours associated with stablecoin use in corporate financial practices. Our results indicate that the intensity, frequency, environment of transactions (specifically IntraVasp and P2P transactions), age, sector, and size are factors significantly associated with tax evasion behaviour. However, we found no evidence to suggest that firms engaging in only P2P transactions have a higher propensity for tax evasion than those engaging only in IntraVasp transactions. Our findings reveal that younger and medium-sized companies with intensive use of stablecoin, with high stablecoin transaction frequency, engaging in IntraVasp and P2P transactions, and belonging to the service sector are more likely to evade tax. Therefore, our research provides a detailed understanding of how digital financial practices with crypto assets (blockchain-based technology) intersect with corporate tax strategies, which can offer valuable insights for regulators, industry practitioners, and policymakers.

Examining the Factors Affecting the Use of Crypto Assets as Foreign Payment and Investment Instruments: A Quantitative Study

The aim of the study is to examine the factors affecting individuals' intentions to use crypto assets as foreign payment and investment instruments. A research model based on the UTAUT-2, a widely accepted model that examines individuals' attitudes toward information technologies, was formed, and the factors affecting two dependent variables, "intention to use in foreign payments" and "intention to invest," were analyzed with PLS-SEM. Path coefficients (β) demonstrated that the variables significantly affecting the intention to use in foreign payments were "performance expectancy," "social influence," and "perceived risk," respectively. Moreover, in order of importance, "performance expectancy," "social influence," "awareness," and "perceived risk" were determined as the variables significantly affecting the intention to invest. Along with path coefficients, f² and q² effect sizes were also analyzed to examine the interaction between the variables. In the context of empirical findings, it was evaluated that the most significant factors in the participants' tendency to use crypto assets in foreign payments and investment transactions were "performance expectancy" and "social influence”. Contrary to the widespread approach in the literature, the study has revealed crucial results for the literature and future studies by addressing the two main financial functions of crypto assets and the factors significantly affecting these functions.

A fair multi-attribute data transaction mechanism supporting cross-chain

Reliable storage and high-speed data networks enable individuals to access high-quality Internet of Things (IoT) data for scientific research through global transactions. Blockchain technology provides transparency for institutions to securely store and manage IoT data, while cross-chain transaction mechanisms facilitate the flow of IoT data. However, fairness issues may arise when it comes to cross-chain transactions of IoT data. This paper proposes a mechanism for multi-attribute data transactions to support cross-chain. The solution utilizes Vickrey–Clarke–Groves (VCG) auction, Paillier, Intel SGX, and other technologies to design a secure and equitable data seller selection scheme. The scheme ensures that the selection process for data sellers is both informed and private. Additionally, we generate a key pair for each attribute in the dataset to produce the corresponding attribute data signature. The dataset’s legitimacy is verified through batch verification to ensure that the data seller’s purchased attributes align with their requirements. The exchange of crypto assets and private keys between data sellers and buyers is designed to achieve fair payment. Our research suggests that the scheme meets the necessary security standards, and simulation results confirm its feasibility and effectiveness.

Investment Behavior and Strategy in Cryptocurrency in Indonesia

Investor behavior in making investment decisions is always based on clear reasons, whether for reasons of the future, profit, or hedging. This also provides a more precise portrait of investor behavior and the learning process if you want to enter the crypto asset industry. Apart from that, future suggestions for future researchers are expected to include female informants as a new perspective in researching investor behavior. The aim of carrying out this research is to find out what strategies can be implemented by cryptocurrency asset investors in order to get an optimal level of return. The method approach used in this research is qualitative library research. The data sources used as references in this research are data originating from articles, books, and newspapers from electronic media with the search keywords: how to invest in crypto, crypto investing techniques, and crypto investing strategies. The data obtained was then analyzed using NVivo 10 Plus software. From the results of this research, several strategies for investing in cryptocurrency assets were obtained, namely: determining the type and purpose of investment, studying the cryptocurrency assets you are interested in, choosing trusted cryptocurrency assets, choosing safe exchanges and wallets, paying attention to service fees and spreads, don't be afraid of missing out ( FOMO), buying when prices are low (support) and selling when prices are high (resistance), diversifying and mitigating risk, investing on various platforms, not easily panicking and oriented towards holding on for dear life (HODL), always following development information cryptocurrency, following and joining cryptocurrency communities, and regularly doing dollar-cost averaging (DCA).

Twenty-Four Hour Live Chat Feature and Customer Satisfaction

Purpose –This paper wants to describe the e-service quality of customer support in handling crypto asset consumer problems using the 24-hour live chat feature, and an overview of customer satisfaction ratings at PT Akunku Dotcom Indonesia Methodology/approach –The survey was conducted on 100 Reku friend respondents who had interacted with customer support via the 24-hour live chat feature. The instrument used is a questionnaire with 4 Likert scales and customer satisfaction rating data. The assessment of e-service quality is presented in the form of an average answer score and the level of agreement between Reku friends. Findings –E-Service Quality through the 24 Hour Live Chat Feature on Reku received a positive response from Reku users with an agreement rate of almost 90%. Reku Indonesia's Customer Satisfaction Rating is dominated by the Good Rate category. Both the Good Rate and Bad Rate sections are mostly influenced by Customer Support services. Novelty/value –Customer support needs to provide a sense of security to customers of digital products such as crypto assets, through maximum e-service quality, so that this can have an impact on maximum customer satisfaction ratings too