Cryptocurrency Market Research Articles

DYNAMICS OF THE UKRAINIAN BANKING SYSTEM’S ATTRACTION AND USE OF CASH SURROGATES

This study is devoted to the analysis of transformations in the use of monetary surrogates within the Ukrainian banking system from 2015 to 2023. Through an extensive examination of financial data, key factors driving the rising prevalence of electronic money and cryptocurrencies have been identified. This phenomenon unfolds against a backdrop of profound technological shifts and economic volatility, compounded by regulatory challenges. The findings underscore a strong interconnection between technological advancements, changes in consumer behavior, and the evolution of the regulatory framework. A notable increase in the volume of electronic money transactions, coupled with the significant expansion of the cryptocurrency market, points to a paradigm shift from traditional banking services towards novel financial instruments. Specifically, electronic money, cryptocurrencies, and digital tokens are emerging as prominent alternatives to conventional currency, offering users avenues for conducting transactions and preserving value amid economic instability. The research also provides an in-depth analysis of the regulatory hurdles confronting financial institutions and government agencies, particularly regarding adherence to anti-money laundering (AML) protocols and know-your-customer (KYC) regulations, alongside the imperative to safeguard consumer rights amid heightened cryptocurrency market volatility. Furthermore, this study addresses the potential long-term ramifications of the proliferation of monetary surrogates on Ukraine’s banking system, including shifts in conventional banking practices, potential risks to financial stability, and implications for monetary policy. Despite notable progress in the integration of new financial technologies, several unresolved challenges persist, particularly concerning the provision of adequate regulatory support for innovation while maintaining the stability of the financial system. In conclusion, this research offers a valuable contribution to the understanding of how technological development and socio-economic changes are reshaping financial systems in emerging economies, with a particular focus on Ukraine. The insights derived from this study may prove instrumental for policymakers and financial institutions as they navigate the evolving conditions and challenges of a rapidly transforming financial landscape.

Consumer confidence and cryptocurrency excess returns: A three-factor model

This study examined the relation between consumer confidence and cryptocurrency excess returns using a three-factor model of market, size and momentum. We analysed a dataset comprising 3318 cryptocurrencies from 1 January 2014 to 31 December 2022 based on the CoinMarketCap website. Results indicate a significant negative relation between the United States Consumer Confidence Index and cryptocurrency excess returns. The findings were reinforced based on robustness tests. This study contributes to consumer behaviour research and financial management within the cryptocurrency market. It also provides valuable insights for investors to strengthen their investment portfolios and for relevant authorities seeking to formulate effective policies for monitoring the cryptocurrency market.

Complex and Multifaceted Nature of Cryptocurrency Markets: A Study to Understand its Time-Varying Volatility Dynamics

Complex and Multifaceted Nature of Cryptocurrency Markets: A Study to Understand its Time-Varying Volatility Dynamics

Estimating and forecasting bitcoin daily prices using ARIMA-GARCH models

PurposeThe goal of the study is to offer important insights into the dynamics of the cryptocurrency market by analyzing pricing data for Bitcoin. Using quantitative analytic methods, the study makes use of a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and an Autoregressive Integrated Moving Average (ARIMA). The study looks at how predictable Bitcoin price swings and market volatility will be between 2021 and 2023.Design/methodology/approachThe data used in this study are the daily closing prices of Bitcoin from Jan 17th, 2021 to Dec 17th, 2023, which corresponds to a total of 1065 observations. The estimation process is run using 3 years of data (2021–2023), while the remaining (Jan 1st 2024 to Jan 17th 2024) is used for forecasting. The ARIMA-GARCH method is a robust framework for forecasting time series data with non-seasonal components. The model was selected based on the Akaike Information Criteria corrected (AICc) minimum values and maximum log-likelihood. Model adequacy was checked using plots of residuals and the Ljung–Box test.FindingsUsing the Box–Jenkins method, various AR and MA lags were tested to determine the most optimal lags. ARIMA (12,1,12) is the most appropriate model obtained from the various models using AIC. As financial time series, such as Bitcoin returns, can be volatile, an attempt is made to model this volatility using GARCH (1,1).Originality/valueThe study used partially processed secondary data to fit for time series analysis using the ARIMA (12,1,12)-GARCH(1,1) model and hence reliable and conclusive results.

Islamic cryptocurrency integration for enhanced sustainable finance: evidence from time-frequency volatility transmission investigation

ABSTRACT This study explores the potential of Islamic gold-backed cryptocurrencies in sustainable finance by focusing on volatility transmission between these cryptocurrencies and conventional digital assets like Bitcoin and PaxGold. Using a Time-Varying Parameter Vector Autoregression (TVP-VAR) approach, we analyze data from December 2019 to July 2023, including the COVID-19 pandemic period. Findings reveal a complex volatility network, with Bitcoin and HelloGold as major transmitters of spillover shocks, while X8X and PaxGold mainly serve as net recipients. Notable interactions between Bitcoin and Islamic gold-backed cryptocurrency markets show short-lived pairwise volatility interactions. Islamic gold-backed cryptocurrencies, net recipients of volatility, absorb market shocks, making them suitable for hedging against volatility. This can aid in diversifying portfolios, mitigating adverse market impacts, and informing risk management and regulatory approaches. Our research emphasizes the importance of Islamic finance in ethical and sustainable investment within the evolving cryptocurrency market.

The promises and pitfalls of cryptocurrencies and blockchain for marginalized communities

ABSTRACT Cryptocurrencies, and the blockchain technology that underlies them, have attracted much attention over the last decade from scholars, tech communities, financial institutions, states and more. The extreme volatility of the cryptocurrency market has made some people very rich and cost others almost everything. Importantly, there are many indications that marginalized communities are especially attracted to this new technology while being more vulnerable to issues such as fraud and exploitation in this field. This paper reviews academic research – predominantly social scientific – on cryptocurrencies and financial blockchain to determine the extent to which they engage with the experiences, agencies, and knowledges of marginalized communities. Overall, the findings show that, bar a few important exceptions that take seriously marginalized communities, academic research has largely focused on traditionally dominant actors such as crypto evangelists, fintech developers, states, and banks. Furthermore, the knowledges of marginalized communities are almost entirely absent while research privileges already dominant theories and research methodologies. Such trends in academic research on cryptocurrencies and blockchain technology reproduce existing knowledge hierarchies and lead to the further material marginalization of already vulnerable communities. In light of these findings, we conclude with some recommendations for further research that can challenge these problematic dynamics.

Mitigating digital market risk with conventional, green, and Islamic bonds: Fresh insights from new hybrid deep learning models

We examine the impact of conventional, green, and Islamic bonds on the long-term memory of cryptocurrency market risk. Utilizing a time-varying parameter vector autoregressive deep learning model, we integrate time-varying parameter vector autoregressive methods with advanced deep learning sequence modeling architectures, including temporal convolutional network, gated recurrent unit, and long short-term memory for December 18, 2017, to April 19, 2024. Results indicate that incorporating all fixed-income securities reduces digital market risk. However, conventional and green bonds have a particularly strong impact on improving the long-term memory of digital market risk, while this is not the case for Sukuk.

Exploring Calendar Anomalies and Volatility Dynamics in Cryptocurrencies: A Comparative Analysis of Day-of-the-Week Effects before and during the COVID-19 Pandemic

This study investigates calendar anomalies and their impact on returns and volatility patterns in the cryptocurrency market, focusing on day-of-the-week effects before and during the COVID-19 pandemic. Using advanced statistical models from the GARCH family, we analyze the returns of Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Our findings reveal significant shifts in volatility dynamics and day-of-the-week effects on returns, challenging the notion of market efficiency. Notably, Bitcoin and Solana began exhibiting day-of-the-week effects during the pandemic, whereas Cardano and Dogecoin did not. During the pandemic, Binance USD, Ethereum, Tether, USD Coin, and Ripple showed multiple days with significant day-of-the-week effects. Notably, positive returns were generally observed on Sundays, whereas a shift to negative returns on Mondays was evident during the COVID-19 period. These patterns suggest that exploitable anomalies persist despite the market’s continuous operation and increasing maturity. The presence of a long-term memory in volatility highlights the need for robust trading strategies. Our research provides valuable insights for investors, traders, regulators, and policymakers, aiding in the development of effective trading strategies, risk management practices, and regulatory policies in the evolving cryptocurrency market.

A private-preserved IoT and blockchain-based system in the cryptocurrency market

A private-preserved IoT and blockchain-based system in the cryptocurrency market

Spillover effect of the geopolitical uncertainty on the cryptocurrency market

PurposeThis study aims to examine the influence of geopolitical uncertainty on cryptocurrency markets (CM).Design/methodology/approachUtilizing two distinct sets of daily returns data spanning from January 1, 2019, to May 4, 2023, the analysis employs the geopolitical risk (GPR) index formulated by Caldara and Iacoviello (2022), which encapsulates two pivotal events: the COVID-19 pandemic and the Russia–Ukraine conflict. The cryptocurrency market (CM) encompasses Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC) and Dogecoin (DOGE). Employing the DCC-GARCH model and supplementing it with wavelet coherence analysis to discern perceptual distinctions between short- and long-term market reactions.FindingsThe main findings indicate that the GPR index clearly impacts the return of CM in the short-, mid- and long-term periods. BTC exhibited the highest volatility in response to changes in the GPR index. The cryptocurrency market offers a better diversification opportunity, and the impact of geopolitical events varies across time, with their direction and magnitude closely related to the specificity of the CM.Practical implicationsThis research is helpful for financial market investors, portfolio and risk managers, make informed decisions about including cryptocurrencies in their investment portfolios to mitigate the risks in uncertainty period.Originality/valueCryptocurrency market volatility is treated weakly during the risk period. With advanced statistical method, this study links two important events: the COVID-19 pandemic and the Russia–Ukraine conflict and selects the top four cryptocurrencies constituting 80% of the market. This study examines the impact of geopolitical risk on the cryptocurrency market and shows that this market is considered a safe haven.

Price delay and herding: evidence from the cryptocurrency market

PurposeThe purpose of this study is to investigate how the price delay of cryptocurrencies to market news affects the herding behavior of investors, particularly during turbulent events such as the COVID-19 period.Design/methodology/approachThe paper investigates the presence of herding behavior by using Cross-Sectional Absolute Deviation (CSAD) measures. We also investigate the herding activity in the crypto traders’ behavior during up and down-market movements periods and under investor extreme sentiment conditions. The speed of cryptocurrencies’ price response to the information embedded in the market is assessed based on the price delay measure proposed by Hou and Moskowitz (2005).FindingsOur findings suggest that cryptocurrencies characterized by high price delays exhibit more herding among investors, thereby highlighting higher degrees of market inefficiencies. This is also apparent during periods of extreme investor sentiment. We also document an asymmetric herding behavior across cryptocurrencies that present different levels of price speed adjustments to market news during bullish and bearish market conditions. Our results are consistent and robust across different sub-periods, various market return estimations and different price delay frequencies.Practical implicationsThe study provides crucial guidelines for investors’ asset allocation and risk management strategies. This study is also valuable to regulators and policymakers, particularly in light of the increasing importance of financial reforms aimed at mitigating market distortions and enhancing the resilience of the cryptocurrency market. More specifically, regulations that improve the market’s information efficiency should be prioritized to speed up the response time of cryptocurrency prices to market information, which can help reduce the investors' herding behavior.Originality/valueThis paper makes a novel contribution to the academic literature by investigating the unexplored relationship between cryptocurrency price delays and the presence of herding behavior among investors, especially in times of uncertainty such as the COVID-19 pandemic.

Identification of Expected Growth in Crypto Currency

Identifying the expected growth in cryptocurrency involves analyzing a combination of market trends, technological advancements, regulatory developments, and economic indicators. Historical performance and adoption rates of major cryptocurrencies provide insight into market trends, while innovations in blockchain technology, such as Ethereum 2.0 and Layer 2 solutions, along with the rise of decentralized finance (DeFi) and non-fungible tokens (NFTs), highlight significant technological advancements. Regulatory developments, including supportive legislation and the involvement of institutional investors through financial products like Bitcoin ETFs, play a crucial role in shaping market confidence and investment. Economic indicators, such as inflation, monetary policies, and global events, also influence interest in cryptocurrencies as alternative assets. Investor sentiment, driven by public perception, media coverage, and social media activity, impacts market dynamics. Additionally, research from financial analysts, market research firms, and academic studies, along with corporate partnerships and the integration of crypto solutions with traditional systems, contribute to growth predictions. Monitoring market capitalization and trading volumes further helps gauge market interest and liquidity. By considering these multifaceted factors, a more comprehensive understanding of the potential growth in the cryptocurrency market can be achieved.

Green gold or carbon beast? Assessing the environmental implications of cryptocurrency trading on clean water management and carbon emission SDGs

This study addresses the ongoing debate concerning the environmental implications of cryptocurrencies. Specifically, it investigates the impact of Bitcoin trading volume on water and sanitation (Sustainable Development Goal (SDG) 6) and climate action (SDG 13). The research employs Ordinary Least Squares (OLS) panel data analysis to examine these relationships using a sample of 32 countries with available Bitcoin trading volume data from 2013 to 2020. The findings indicate that Bitcoin trading significantly and positively impacts progress towards SDG 6, suggesting potential benefits for water and sanitation initiatives. However, the study reveals a significant negative impact of higher Bitcoin trading volume on increased carbon emissions, underscoring the environmental costs associated with cryptocurrency activities. Similar impacts are observed for gold reserves, as their mining necessitates substantial energy consumption. These results highlight the need to regulate cryptocurrency trading and promote voluntary sustainable practices, particularly given the disparities between developed and emerging markets based on their governance frameworks. Additionally, the study considers the disparities between countries based on technology exports and economic policy uncertainty as influential determinants. The study's results emphasize the importance of proactive measures to ensure the responsible and sustainable use of cryptocurrencies. While cryptocurrencies offer significant economic returns, their early adoption stage necessitates further investigation into environmentally friendly approaches. Potential strategies include directing financial returns from cryptocurrencies towards alternative energy projects and supporting other environmental SDGs, thereby fostering a positive impact on the overall ecosystem. The study's implications extend to policymakers, regulators, and stakeholders, advocating for comprehensive and collaborative efforts to integrate sustainability into the rapidly evolving cryptocurrency market. This integration is crucial to ensure that the economic benefits of cryptocurrencies do not come at the cost of our environment.

Does the carbon market signal the market efficiency of clean and dirty cryptocurrencies? An analysis of quantile directional dependence

The role of the carbon market in the market efficiency of cryptocurrencies has not received much attention from scholars, despite its particular relevance for integrating environmental externalities into the theory and practice of digital financial markets. We investigate whether and how the performance of the carbon market during busts and booms affects the market efficiency of both clean and dirty cryptocurrencies. Overall, our results underscore the complex quantile dependence of cryptocurrency market efficiency on carbon market performance, highlighting significant variability in how different types of cryptocurrencies respond to carbon market. These results have significant implications for regulatory policies, investment strategies, industry practices, public perceptions, and technological advances in the pursuit of aligning cryptocurrency markets with environmental sustainability goals.

Digital shadows: analyzing factors influencing sentencing in child sexual abuse material (CSAM) cases

Purpose Exhibiting an unprecedented rate of advancement, technology’s progression over the past two decades has regrettably led to a disturbing increase in the distribution of child sexual abuse materials (CSAM) online. Compounded by the emergence of an underground cryptocurrency market, which serves as a primary distribution channel for these materials, the investigation and sanctioning of CSAM present a complex and unique set of challenges. The purpose of this study is to accurately diagnose the CSAM sentencing landscape and build a more comprehensive, evidence-based legal framework in penology. Design/methodology/approach The study collected and analyzed case details regarding CSAM sanctions in a database sourced from the US Department of Justice for 2020. Various factors were analyzed such as the victim’s age, offender typology and previous conviction, accompanied by an analysis of how these factors affect the sentence length. Findings The study found that the hierarchical agency-level interactions give insight into resource allocation prioritization, as well as confirming a close relationship between prior conviction history and sentence length, with the victim’s age inversely related to sentence length. Leveraging data-driven insights, the study paves the way for more targeted and effective sanctions, ultimately contributing to the broader goal of safeguarding children from online sexual exploitation. Originality/value The paper provides a critical analysis of the complex landscape surrounding CSAM distribution and judicial sentencing. By examining case details and leveraging data-driven insights, it offers valuable contributions to understanding the interplay between various factors such as victim age, offender typology and prior convictions on sentencing outcomes. This comprehensive approach not only sheds light on the dynamics of CSAM sanctions but also lays the groundwork for evidence-based legal frameworks in penology. Its originality lies in its nuanced examination of hierarchical agency interactions and its potential to inform more targeted interventions for safeguarding children from online exploitation.

From scam to heist: the impact of cybercrimes on cryptocurrencies

ABSTRACT We analyse the impact of cybercrime, particularly cryptocurrency heists and scams, on dynamic conditional correlations and abnormal returns in cryptocurrency. Our high-frequency, hourly data set covers three years, from January 2020 to December 2022, and our results show that certain hacking events have a negligible negative impact on investors, especially when focusing on less popular tokens or coins. This new perspective has significant implications for the investment community. Existing literature generally assumes that the impact of cybercrime is situational and argues for increased awareness, proactive cybersecurity measures and multi-stakeholder collaboration in traditional financial markets such as equities and currencies. However, the cryptocurrency market – a relatively young and still developing area – has a unique dynamic. Less popular tokens or coins often have lower market integration and liquidity, indicating a lower impact of cybercrime. If such a token or coin already has a limited reputation or investor base, the overall negative sentiment may be further mitigated, lessening the expected negative impact.

Economic Behavioral Anomalies In Cryptocurrency Transactions During The Covid-19 Pandemic

The COVID-19 pandemic has had a significant impact on various aspects of life, including financial markets. The cryptocurrency market, already renowned for its volatility, experienced a surge in activity and significant changes in investor behavior during this period. This research aims to analyze various economic behavioral anomalies that emerged in cryptocurrency transactions during the COVID-19 pandemic. This research uses a literature study method to identify several dominant behavioral anomalies, such as FOMO (Fear of Missing Out), Herding Behavior, Noise Trading, Overconfidence, and Anchoring Bias. These behavioral anomalies trigger extreme market volatility, asset bubbles, and financial losses for investors. This research highlights the importance of investor education, market regulation, and technology development to minimize the impact of behavioral anomalies and protect investors in the cryptocurrency market.

Crypto-Mining and Electricity Market Nexus: Assessing the Evidence from the Nordic Electricity Prices

This paper examines the the dynamic relationship between the cryptocurrency market, through two major cryptocurrencies namely Bitcoin and Ethereum, and the Nordic electricity market. Specifically, it examines how the two main cryptocurrencies’ prices volatilities affect the Nordic electricity prices. Our analysis is based on daily spot prices from 08 August 2015 to 16 June 2020, using the dynamic conditional correlation DCC-GARCH model. Our results confirm the existence of a medium conditional correlation between cryptocurrencies and Nordic electricity market. Especially at the end of 2018, this correlation is significantly important. During this period, a peak in Ethereum prices was noticed which impact electricity prices via the high demand of power by miners who are attracted by such low prices, in the Nordic region, to increase the profitability of their activity.

Trading Strategy of the Cryptocurrency Market Based on Deep Q-Learning Agents

ABSTRACT As of December 2021, the cryptocurrency market had a market value of over US$270 billion, and over 5,700 types of cryptocurrencies were circulating among 23,000 online exchanges. Reinforcement learning (RL) has been used to identify the optimal trading strategy. However, most RL-based optimal trading strategies adopted in the cryptocurrency market focus on trading one type of cryptocurrency, whereas most traders in the cryptocurrency market often trade multiple cryptocurrencies. Therefore, the present study proposes a method based on deep Q-learning for identifying the optimal trading strategy for multiple cryptocurrencies. The proposed method uses the same training data to train multiple agents repeatedly so that each agent has accumulated learning experiences to improve its prediction of the future market trend and to determine the optimal action. The empirical results obtained with the proposed method are described in the following text. For Ethereum, VeChain, and Ripple, which were considered to have an uptrend, a horizontal trend, and a downtrend, respectively, the annualized rates of return were 725.48%, −14.95%, and − 3.70%, respectively. Regardless of the cryptocurrency market trend, a higher annualized rate of return was achieved when using the proposed method than when using the buy-and-hold strategy.

Cryptocurrency: A new player or a new crisis in financial markets? —— Evolutionary analysis of association and risk spillover based on network science

In recent years, cryptocurrency has attracted widespread research attention. Against the backdrop of financial globalization, the high volatility of cryptocurrency prices may pose a threat to the stability of the entire financial system. To explore the potential association and transmission of financial risks between cryptocurrency and traditional financial assets, this paper constructs a complex network using the Granger causality method and the DY spillover method. Based on data from 24 categories of assets or index returns from different markets, networks of association and risk spillover between cryptocurrency market and traditional financial markets are established under different time periods, the study covers the period from January 2015 to November 2023. Analyzing the mutual influence between cryptocurrency and traditional financial markets from the perspective of complex networks, and evaluating the market positioning, risk characteristics, and investment potential of cryptocurrency. Research findings indicate that cryptocurrency possesses not only monetary characteristics but also functions as an investment tool, significantly impacting the stability of traditional financial markets. Furthermore, different types of cryptocurrencies vary in market functions, risk characteristics, and investment potentials. Future research could further explore the nonlinear and dynamic associations between cryptocurrency and traditional financial markets, as well as the micro mechanisms and behavioral factors within cryptocurrency markets.