Chiara Oldani, Giovanni S. F. Bruno, Marcello Signorelli
This paper investigates the existence of bubbles in the daily prices of the most popular cryptocurrencies, Bitcoin (BTC), Ether (ETH), and Ripple (XRP), employing the recursive methods of Phillips et al. (2015) and Phillips et al. (2011) for testing and date-stamping episodes of exuberant behaviour over a period spanning seven years (2018â2024), including the COVID-19 pandemic crisis (2020â2021). The critical values of the tests are computed through the composite wild bootstrap technique by Phillips and Shi (2020) to make them robust to time-varying unconditional heteroscedasticity and the multiplicity issue in recursive tests. Results indicate that the prices of the most popular cryptocurrencies traded on decentralized ledgers, BTC and ETH, exhibited multiple episodes of exuberant behaviour, unambiguously for BTC and depending on the tests for ETH. Bubbles detected in the prices of BTC were due to the halving of the crypto, to market exuberance and to the pandemic crisis; bubbles detected on ETH prices were due to the launch of NFTs on the Ethereum blockchain, and to the change in investorsâ expectations (from exuberant to pessimistic); the change in the stance of monetary policy burst the bubbles of BTC and ETH prices in 2024. No test supports the exuberance of XRP that is traded on a centralized ledger; weekly data confirm the absence of multiple bubbles. By looking at the presence of bubbles in these different digital ecosystems, we also consider how the technological differences can impact, possibly asymmetrically, bubbles' formation.
The development of the world economy, especially in Indonesia, cannot be separated from the element of information technology. The development of information technology will be related to all fields including the financial sector. Cryptocurrency or often referred to as virtual/digital currency is the result of the development of financial technology. Digital currency is starting to be widely used as a means of payment on the internet. The purpose of this currency is to provide convenience and security in payments. With the Blockchain technology in it, it makes transaction costs cheaper. However, the Government in this case Bank Indonesia prohibits transactions using digital/virtual money because it has a dangerous impact on the Financial System, Monetary Stability and Payment System in Indonesia. This study explains the impact of Cryptocurrency on the Indonesian Economy and the government's attitude towards the technology in it. In terms of the technology offered, cryptocurrency is a development of financial technology that allows paper money to be replaced with digital money in financial transactions in the future. It is hoped that the government can study the technology contained in cryptocurrency in more depth so that the policies made later do not prohibit the technology contained in cryptocurrency and provide knowledge to the public to better understand cryptocurrency.
ABSTRACT This study employed both bibliometric analysis and a comprehensive review of the existing literature to examine 3844 publications in cryptocurrency research, which were collected from the Web of Science Core Collection Database. The study has utilized bibliometric methods to analyze the most productive countries and regions, research institutions, and authors in cryptocurrency research. Cluster analysis of coâcitation articles indicates three main themes in cryptocurrency research over the past decade: the efficiency of the cryptocurrency market, innovation, application, and governance of blockchain technology as well as risk management of cryptocurrencies. Keyword coâoccurrence analysis reveals three major future research directions regarding cryptocurrency: (1) using machine learning methods to forecast price returns of cryptocurrencies; (2) how to enhance the security, legitimacy, and environmental sustainability of cryptocurrencies; (3) further exploration of the impact of various unexpected events on the risks of cryptocurrencies under global instability. In the section of literature review, two to three representative papers from the five mostâcited authors in cryptocurrency research are summarized. Additionally, 28 of the most noteworthy papers, selected based on three different criteria, are presented. These papers cover different periods and research topics, and a brief yet comprehensive overview of these 28 influential papers is provided.
Dirin Mchirgui, Mohammed Ali Sulyman Digheem, Fawzi Salem Adwela
This paper explores the interconnectedness and spillover relationships among Bitcoin, gold, gold-backed cryptocurrencies, and energy commodities during the COVID-19 pandemic and the Russia-Ukraine military conflict. Using a quantile connectedness approach, we reveal diverse influence dynamics among digital assets, with Gold, DGX, and PAXG emerging as key contributors to the networkâs total connectedness. Notably, the cTCI/TCI ratio underscores substantial direct linkages, emphasizing significant interconnections among digital assets. DGX acts as a principal information transmitter, while gas plays a crucial role as a primary receiver, suggesting its potential as a diversifier. The time-quantile analysis highlights heightened connectedness during significant events, providing valuable insights for investors and risk managers. Results underscore varying roles of assets, with PAXG persistently acting as a net transmitter and Bitcoin and Gold displaying nuanced patterns. Interestingly, Gold demonstrated certain safe haven characteristics only during the Russia-Ukraine war. The time-frequency analysis at the median quantile emphasizes the dominance of short-term dynamics, prompting the need for adaptive risk management strategies. Overall, this study facilitates a nuanced understanding of market dynamics, offering practical insights for different periods.
This paper investigates the temporal evolution of cryptocurrency time series using information measures such as complexity, entropy, and Fisher information. The main objective is to differentiate between various levels of randomness and chaos. The methodology was applied to 176 daily closing price time series of different cryptocurrencies, from October 2015 to October 2024, with more than 30 days of data and not completely null. Complexityâentropy causality plane (CECP) analysis reveals that daily cryptocurrency series with lengths of two years or less exhibit chaotic behavior, while those longer than two years display stochastic behavior. Most longer series resemble colored noise, with the parameter k varying between 0 and 2. Additionally, Natural Language Processing (NLP) analysis identified the most relevant terms in each white paper, facilitating a clustering method that resulted in four distinct clusters. However, no significant characteristics were found across these clusters in terms of the dynamics of the time series. This finding challenges the assumption that project narratives dictate market behavior. For this reason, investment recommendations should prioritize real-time informational metrics over whitepaper content.
This study explores the role of gold-backed cryptocurrencies (PAXG and XAUT) as effective diversifiers, hedges, and safe havens for NFTs and DeFi assets, particularly during market crises such as the COVID-19 pandemic and the 2022 cryptocurrency crash. By employing a dynamic GARCH-copula approach, the research analyzes the interconnectedness and volatility spillovers between these digital asset classes, providing insights into their behavior during times of heightened uncertainty. We also compute the optimal hedge ratio for each gold-backed cryptocurrencies/stabelcoins-NFT/DeFi/Traditional cryptocurrencies pair and evaluate their dynamic hedging effectiveness. The findings reveal that gold-backed cryptocurrencies offer superior hedging capabilities compared to stablecoins (USDT and BUSD), enhancing portfolio diversification and risk management. The results underscore the importance of incorporating gold-backed assets into digital portfolios to improve resilience and achieve better risk-adjusted returns during periods of market turmoil.
The increasing interaction between the equity market and cryptocurrencies has raised concerns about volatility spillovers; however, empirical evidence about sectoral-specific spillover effects in emerging markets is scarce and hard to find. Existing research mainly concentrates on developed markets and aggregate equity indices, leaving a research gap in comprehending how sectoral indices variations impact market interactions in developing financial markets like Thailand. This article investigates the mean and volatility spillover effects between the Thai stock market and leading cryptocurrencies from April 2019 to April 2024. Applying bivariate VAR (1)-BEKK-GARCH (1,1) with an asymmetry model, this study examines the aggregate and sectoral-specific mean and volatility spillovers across major Thai stock market sectors. The findings reveal the significant mean spillover effect from cryptocurrencies to the Thai stock market with sectoral variation, while sectors such as industrials and financials exerted significant linkages, and the agricultural and food sector remains unaffected. Additionally, volatility spillovers were predominantly transmitted from the Thai equity market to cryptocurrency. Moreover, asymmetry effects were observed, with the asymmetry effects mainly transmitted from the Thai equity market to cryptocurrency. These findings provide critical insights for both individual and institutional investors on risk management and portfolio diversification while also helping policymakers with guidance on regulatory measures to mitigate systemic risks in emerging financial markets.
This paper provides the first empirical evidence of whether the introduction of US spot Bitcoin ETFs affected the returns and volatility of major cryptocurrencies. Using data from December 18, 2017 to March 15, 2024, we apply an event-study methodology within a GARCH-based framework. Our results reveal a significant effect of the introduction of spot Bitcoin ETFs on cryptocurrency returns and volatility. The analysis shows a positive impact for Bitcoin, Ethereum, and Litecoin spot price returns around the event date. The volatility of Bitcoin and Ripple spot markets decreased following the introduction of spot Bitcoin ETFs, which supports the stabilization hypothesis for these two cases. We also examine the volatility spillovers using a wavelet coherence approach, and reveal significant volatility spillovers from Grayscale Bitcoin ETF to Bitcoin futures and to a lesser extend to the Bitcoin spot market. Our findings enhance the limited understanding of the price discovery and functioning of the cryptocurrency markets, which could be useful for investors, regulators, and policymakers. ⢠Study the impact of introduction of Spot Bitcoin ETFs on the cryptocurrency market. ⢠Apply event study methodology within a GARCH framework. ⢠Find a positive impact for Bitcoin, Ethereum, and Litecoin spot price returns. ⢠Volatility of Bitcoin and Ripple decreased, supporting the stabilization hypothesis. ⢠Wavelet coherence analysis reveals volatility spillovers from Bitcoin ETF to Bitcoin futures.
Diego Mazzitelli, Elia Fiorenza, Inès Belgacem, Carmelo Arena
Objective of this manuscript is both to tracing the evolution of money, and examining its transition from commodity money to fiat money, up to the emergence of cryptocurrencies. It highlights the inherent issues of the barter system, emphasizing the urgencies and necessities that favored the adoption of legal tender. Subsequently, the impact of the creation of the Euro on the European economyâboth historically and geopoliticallyâwill be analyzed, contextualizing the European Union's institutional process. In a response to the crisis, Bitcoin (the first decentralized cryptocurrency) will be introduced, along with an illustration of the supporting Blockchain technology will be provided. Finally, the proposal of American Senator Lummis, who suggests a massive purchase of Bitcoin to be used as a strategic reserve through the âBitcoin Actâ program, will be explored, prompting several reflections on the future of the petrodollar as a reserve instrument. Through these reflections, the reader could develop their own thoughts on the importance of evolving towards forms of money more suited to an increasingly digitized and decentralized economy. In conclusion, by proposing an analogy between the ancient monetary practices on Yap and cryptocurrencies, we aim to stimulate the reflection that innovation is not only desirable in this fast-paced world but essential.
Cryptocurrencies have attracted significant attention due to their high risk, extreme volatility, regulatory controversies, and scandals. Investors and policymakers are drawn to them for their potential to enhance diversification and deliver high returns. This study examines the impact of incorporating cryptocurrencies into investment portfolios, focusing on their ability to improve risk-adjusted returns and diversification. A rolling asset allocation strategy employing the maximum Sharpe Ratio within a Markowitz framework was applied to weekly data from 2018 to April 2024. The analysis compares two unconstrained portfolios and two constrained portfolios, which impose a concentration limit on cryptocurrency investments. Results reveal that in 70% of the rolling periods examined, portfolios with cryptocurrency allocations outperformed non-cryptocurrency portfolios in terms of Sharpe Ratios. However, the heightened volatility of cryptocurrencies significantly increased portfolio risk, with annualized weekly standard deviations ranging from 18% to 25%, compared to 12% to 15% for portfolios without cryptocurrency exposure. These findings illustrate the dual nature of cryptocurrencies: they can act as both a source of instability and an opportunity for diversification. The study underscores the necessity of a cautious and strategic approach to incorporating cryptocurrencies into investment plans, given their inherent risks and unpredictable behavior.
Kamel Touhami, Ilyes Abidi, Mariem Nsaibi, Maissa Mejri
This study investigates the impact of environmental variables, such as carbon emissions and temperature anomalies, on cryptocurrency returns. While existing research has primarily focused on economic and financial determinants, the influence of environmental factors remains underexplored. Using Dynamic Conditional Correlation GARCH (DCC-GARCH) and Time-Varying Coefficients Vector Autoregression (TVC-VAR) models, this study provides empirical evidence that environmental variables significantly affect the volatility and returns of Bitcoin, Ethereum, and Tether. The results show that Bitcoin and Ethereum are highly sensitive to CO2 emissions and temperature fluctuations, while Tether demonstrates a more moderate response. Moreover, the impact of these environmental factors evolves over time, underscoring their dynamic nature in cryptocurrency valuation. These findings highlight the importance of incorporating environmental variables into forecasting models to enhance risk management and investment strategies. This study contributes to the literature by bridging the gap between environmental concerns and cryptocurrency market behavior, offering valuable insights for investors, regulators, and policymakers.
Kripto paralar 21. yĂźzyÄąlÄąn ilk çeyreÄine damgasÄąnÄą vuran finansal varlÄąklardÄąr. Finansal piyasalarda iĹlem gĂśrmeye baĹlamalarÄąnÄąn ardÄąndan kÄąsa sĂźre içerisinde iĹlem hacimlerinin artmasÄą ile çok sayÄąda yeni kripto para birimi Ăźretilerek piyasada iĹlem gĂśrmeye baĹlamÄąĹtÄąr. Kripto paralarÄąn Ăźretim sĂźreçleri, fiziksel varlÄąÄa sahip olmamalarÄą, merkeziyetsiz yapÄąlarÄą gibi geleneksel finansal varlÄąklardan ayrÄąlan Ăśzellikleri dikkat çekmiĹtir. Dikkat çeken bir diÄer Ăśnemli Ăśzellikleri ise ĹĂźphesiz kripto para birimlerinde yaĹanan ciddi fiyat dalgalanmalarÄą olmuĹtur. Kripto para birimlerinin yaĹamĹŠolduklarÄą bu fiyat dalgalanmalarÄą piyasanÄąn volatil yapÄąsÄąnÄą Ăśn plana çĹkarmÄąĹtÄąr. Bu nedenle kripto varlÄąklar arasÄąndaki volatilite yayÄąlÄąmÄąn analiz edilmesi gerek yatÄąrÄąmcÄąlar gerekse araĹtÄąrmacÄąlar açĹsÄąndan Ăśnem kazanmÄąĹtÄąr. Bu çalÄąĹmada kripto para piyasasÄąnda en yĂźksek piyasa deÄerine sahip 4 kripto para birimi arasÄąndaki volatilite yayÄąlÄąmÄą analiz edilmiĹtir. Analizlerde BTC (Bitcoin), ETH (Ethereum), BNB (Binance Coin) ve SOL (Solano) için 13.07.2020 ile 05.09.2024 tarihleri arasÄąna ait gĂźnlĂźk getiriler kullanÄąlmĹŠve volatilite yayÄąlÄąmÄąnÄąn analizi için TVP-VAR modeli oluĹturularak kripto para birimleri arasÄąndaki dinamik baÄlantÄą incelenmiĹtir. Analiz bulgularÄąndan, kripto para birimlerinin volatilitelerindeki toplam dinamik baÄlantÄąnÄąn Covid-19 Pandemisi ve Bitcoin ETFâlerinin onaylanmasÄąna iliĹkin geliĹmelerden etkilendiÄi ve bu dĂśnemlerde artĹŠgĂśsterdiÄi tespit edilmiĹtir. AyrÄąca, kripto para birimleri arasÄąndaki toplam volatilite yayÄąlÄąmÄąnÄąn gĂźcĂźnĂźn yĂźksek olmadÄąÄÄą, kripto para birimlerinden BNB ve BTCânin analiz dĂśnemi içerisinde volatilite yayÄącÄąsÄą, ETH ve SOLâun ise volatilite alÄącÄąsÄą Ăśzellik gĂśsterdiÄi bulgusu elde edilmiĹtir. Kripto para birimleri arasÄąnda volatilite yayÄącÄąsÄą olan deÄiĹkenler etki gßçleri açĹsÄąndan sÄąralandÄąÄÄąnda en gßçlĂź volatilite yayÄącÄąsÄą olan para biriminin BNB olduÄu ve bunu BTCânin takip ettiÄi belirlenmiĹtir. DiÄer yandan SOL, volatilite alÄącÄąsÄą olan kripto para birimleri arasÄąnda volatiliteyi en çok alan kripto para birimi olurken, ETH ise ikinci sÄąradadÄąr. Kripto para birimlerinin volatilitelerindeki deÄiĹimin açĹklanmasÄąnda Ăśncelikle ilgili kripto para biriminin kendi geçmiĹ fiyat ĹoklarÄąnÄąn etkili olduÄu belirlenmiĹtir. Analizlerde dikkat çeken bir diÄer husus ise Ăśzellikle BNB ve BTCânin SOLâa gßçlĂź Ĺekilde volatilite yaymasÄądÄąr. Analize dahil edilen 4 kripto para biriminin volatilite yayÄąlÄąm iliĹkisinin çok yĂźksek olmamasÄą, aynÄą portfĂśyde bulundurulabilecekleri ve birbirlerine risk bulaĹtÄąrÄącÄą etkilerinin sÄąnÄąrlÄą olabileceÄi Ĺeklinde deÄerlendirilebilir. Bunun yanÄą sÄąra BNBânin en yĂźksek volatilite yayÄącÄąsÄą olma ĂśzelliÄi dikkate alÄąnarak portfĂśylerin oluĹturulmasÄą ve takip edilmesi, yatÄąrÄąm verimliliÄi açĹsÄąndan Ăśnem taĹÄąyacaktÄąr. Benzer Ĺekilde SOLâun da diÄer kripto para birimlerinden gßçlĂź Ĺekilde volatilite almasÄą, yatÄąrÄąm sĂźreçlerinde dikkat edilmesi gereken bir diÄer husus olarak deÄerlendirilebilir.
We investigate the long-range cross-correlation and cross-multifractality between the âdirtyâ and âcleanâ cryptocurrencies and the major financial assets: the Dow Jones Index (DJI), the EuroâDollar exchange rate (EURUSD), and Gold. The analysis shows a high long-range correlation between most pairs with some exceptions, including the DJIâRipple and GoldâPolygon. When the DJI is paired with clean cryptocurrencies such as Polygon and Cardano, they exhibit multifractal properties. As for the EURUSDâBTC and GoldâBTC, these two pairs demonstrated the highest level of multifractality in their corresponding pairs. All pairs of cryptocurrencies and main financial indices are persistent, with the exceptions of EURUSDâPOLYGON (H = 0 . 4970 Âą 0 . 0048 for q =2), GOLDâBTC (H = 0 . 5039 Âą 0 . 0058 for q =2) and GOLDâLTC (H = 0 . 5044 Âą 0 . 0057 for q =2) that are Brownian, and GOLDâPOLYGON (H = 0 . 4917 Âą 0 . 0055 for q =2) which is anti-persistent. For q =5, all are anti-persistent, except DJI-Eth, XRP, and ADA are Brownian, and EURUSD-XRP is persistent. We also assessed the asymmetric persistence behavior when the market is upward or downward and found that for the pairs involving dirty cryptocurrencies with DJI and EURUSD, there is a higher level of persistence during the downward market. On the other hand, Gold-related pairs were almost symmetric. Thus, we identified the complexity and variability of the cryptocurrency pairs with the traditional financial instruments, which shows their various reactions to the changes in the market and types of assets.
Riadh Benammar, Anas Elmelki, Nadia Arfaoui, Adel Boubaker
ABSTRACT This paper investigates how the geopolitical risk (GPRD), economic policy uncertainty (EPU) index, and Twitter economic uncertainty (TEU) related to the RussoâUkrainian conflict can affect cryptocurrency returns (Bitcoin [BTC], Ethereum [ETH], Ripple [XRP], Dogecoin [DOGE], Litecoin [LTC], Cardano [ADA], BNB, and TRON [TRX]) over the period ranging from January 1, 2020, to April 24, 2023. Using the Spectral Breitung Candelon causality and wavelet coherence methods, interesting findings are reported. This study reports noteworthy findings. First, we observe that during the armed battle, ADA, BNB, DOGE, LTC, TRX, and XRP appear as hedges against GPRD. However, we found a negative impact on BTC and ETH. Second, the results show that EPU and TEU have no effect on cryptocurrency, respectively. These findings provide a comprehensive overview of cryptocurrency fluctuations during the ongoing conflicts in Ukraine. Finally, findings show that only ADA, BNB, DOGE, LTC, TRX, and XRP could be used as hedging tools during times of uncertainty. These results have practical implications for cryptocurrency investors and elements influencing its returns, especially during uncertain times.
Ever since the emergence of cryptocurrencies, scholars have grappled with the question of whether they are forms of money or not. The most interesting problem, however, is not if these instruments are already money, but whether they could become money. One crucial aspect in this regard is the potential (or lack thereof) of a privately-issued cryptocurrency to become the monetary unit of account. Drawing on Marxâs theory of money and making the hypothesis that cryptocurrencies are digital commodities, the article argues that cryptocurrencies create a unit of account (BTC) to describe a novel monetary instrument (a Bitcoin coin) aspiring to become a new form of world money. So far, they have not been widely used to denominate prices, incomes, or credits/debts except in certain, still limited but growing, areas of the on-chain digital world. Things could change if the use of cryptocurrencies spills over to the off-chain (digital and non-digital) world. Nevertheless, the adoption of cryptocurrencies as units of account would face several challenges in international and national circulation, crucially among them, the action of states to remain in control of the monetary unit.
Cryptocurrencies have become a significant asset class, attracting considerable attention from investors and researchers due to their potential for high returns despite inherent price volatility. Traditional forecasting methods often fail to accurately predict price movements as they do not account for the non-linear and non-stationary nature of cryptocurrency data. In response to these challenges, this study introduces the Helformer model, a novel deep learning approach that integrates Holt-Winters exponential smoothing with Transformer-based deep learning architecture. This integration allows for a robust decomposition of time series data into level, trend, and seasonality components, enhancing the modelâs ability to capture complex patterns in cryptocurrency markets. To optimize the modelâs performance, Bayesian hyperparameter tuning via Optuna, including a pruner callback, was utilized to efficiently find optimal model parameters while reducing training time by early termination of suboptimal training runs. Empirical results from testing the Helformer model against other advanced deep learning models across various cryptocurrencies demonstrate its superior predictive accuracy and robustness. The model not only achieves lower prediction errors but also shows remarkable generalization capabilities across different types of cryptocurrencies. Additionally, the practical applicability of the Helformer model is validated through a trading strategy that significantly outperforms traditional strategies, confirming its potential to provide actionable insights for traders and financial analysts. The findings of this study are particularly beneficial for investors, policymakers, and researchers, offering a reliable tool for navigating the complexities of cryptocurrency markets and making informed decisions.
Eleni Koutrouli, Polychronis Manousopoulos, John Theal, Laura Tresso
As crypto assets become more widely adopted, crypto asset markets and traditional financial markets may become increasingly interconnected. The close linkages between these markets have potentially important implications for price formation, contagion, risk management and regulatory frameworks. In this study, we assess the correlation between traditional financial markets and selected crypto assets, study factors that may impact the price of crypto assets and identify potentially significant events that may have an impact on Bitcoin and Ethereum price dynamics. For the latter analyses, we adopt a Bayesian model averaging approach to identify change points in the Bitcoin and Ethereum daily price time series. We then use the dates and probabilities of these change points to link them to specific events, finding that nearly all of the change points can be associated with known historical crypto asset-related events. The events can be classified into broader geopolitical developments, regulatory announcements and idiosyncratic events specific to either Bitcoin or Ethereum.
This study investigates return spillovers among the 15 most capitalized cryptocurrencies during the Russia-Ukraine war and the COVID-19 pandemic. Data were extracted from the Coin Market Cap database to ensure a comprehensive analysis of market behavior, covering a daily series from January 2020 to December 2023. The research employs three autoregressive techniques (TVP-VAR, LASSO VAR, and Ridge VAR) to verify the robustness of findings regarding market fragility influenced by non-economic shocks. The study identifies extensive return spillovers primarily driven by Bitcoin and Ethereum, with considerable influences from Cardano, Litecoin, and Polkadot. The results show Ethereum as a primary spillover transmitter in the cryptocurrency market, taking that position formerly held by Bitcoin. Despite the speculative nature of cryptocurrencies, there is potential for diversification through two stablecoins, Tether and USD Coin, which exhibit limited spillover effects from other cryptocurrencies and negative correlations with one another. As a stablecoin, DAI served as a potential diversifier during the COVID-19 pandemic but not during the Ukraine war. The study offers practical insights for investors on managing crypto portfolios during geopolitical and global health crises and the strategic use of stablecoins. Societally, the study examines the need for enhanced regulatory frameworks to reduce systemic risks in the highly interconnected cryptocurrency market. JEL Classification: G01, G11.
The development of the cryptocurrency segment within the global financial market has emerged as one of the most transformative phenomena of the digital economy over the past decade. The present study aims to analyse the global imperatives driving this development, focusing on the key trends, challenges, and opportunities shaping the cryptocurrency market. Methodology. This study uses a combination of analytical and comparative methodologies to examine the cryptocurrency segment within the global financial market. The analytical approach is used to assess the structural dynamics, market trends and capitalisation growth of cryptocurrencies, while the comparative method facilitates the assessment of differences and similarities in the adoption of cryptocurrencies across different countries and financial systems. Data was collected by reviewing publicly available financial reports, cryptocurrency market data and institutional studies. Quantitative analysis was performed to evaluate numerical trends in market capitalisation, transaction volumes, and cryptocurrency usage in payment systems. Furthermore, a qualitative analysis was conducted to elucidate the regulatory challenges and their ramifications for financial stability. Results. The findings indicate the preeminence of Bitcoin, its evolution into a global asset, and the expanding role of altcoins, utility tokens and stablecoins. The analysis reveals the rising use of cryptocurrencies in commercial payments, the issuance of national digital currencies, and the substantial adoption of blockchain technologies by global corporations. However, the study also identifies critical challenges, including regulatory ambiguities, security vulnerabilities, and systemic risks associated with financial stability. The value and originality of this research lie in its comprehensive approach to assessing the multifaceted nature of the cryptocurrency market. The integration of quantitative insights with policy implications has resulted in the formulation of a novel framework for comprehending the strategic role of cryptocurrencies in the evolving global financial landscape. The study's findings offer actionable recommendations for policymakers, investors, and financial institutions seeking to navigate the intricacies of the cryptocurrency ecosystem.
Aktham Maghyereh, Mohammad AlâShboul, Basel Awartani
Research background: This paper explores the hedging and safe-haven properties of gold-backed cryptocurrencies within the context of conventional cryptocurrencies such as Bitcoin, Ethereum, Tether, and Binance. With the rise of blockchain technology, cryptocurrencies have gained recognition as alternative investment assets, drawing comparisons to traditional safe-haven assets like gold. However, the risk management potential of crypto gold, especially during periods of extreme market volatility, remains under-examined. Purpose of the article: The purpose of this article is to assess the effectiveness of gold-backed cryptocurrencies as hedging instruments and safe havens for investors in conventional cryptocurrencies. By analyzing their tail dependence during extreme market fluctuations, the study aims to determine their risk management utility. Methods: To achieve this, we employ a Studentâs t copula structure integrated with an ARMA-GJR-GARCH model to measure the time-varying tail dependence between gold-backed and conventional cryptocurrencies. This approach allows for a comprehensive analysis of both normal and extreme market conditions. We use the Digix Gold Token (DGX) as a representative of gold-backed cryptocurrencies. The study examines four major conventional cryptocurrencies â Bitcoin (BTC), Ethereum (ETH), Tether (USDT), and Binance (BNB) â by analyzing daily closing prices from May 14, 2018, to January 31, 2023, which comprise 1702 observations. The dataset, sourced from coincodex.com, includes periods of significant market stress, such as the COVID-19 pandemic and the Russian-Ukrainian conflict. Findings & value added: The findings reveal a weak association between gold-backed cryptocurrencies and conventional cryptocurrencies, resulting in medium-to-low hedging effectiveness during the sample period. Nevertheless, during crisis periods, a negative association is observed, indicating that gold-backed cryptocurrencies act as effective safe havens in times of market distress. The study contributes to the literature by providing empirical evidence on the risk management benefits of crypto gold, particularly during financial crises, and highlights its potential inclusion in portfolios with cryptocurrency investments to enhance resilience.
Weiwei Guo, Hossein Jahanshahloo, Laima Spokeviciute, Qingwei Wang
This paper examines how on-chain factors (number of active wallets, transaction fees, and transaction volume) and off-chain factors (liquidity and investor attention) impact Bitcoin market efficiency from April 2014 to April 2022. We identify three periods in Bitcoinâs market development: development, growth, and additional development stage. We propose three hypotheses: (1) increased investor attention enhances market efficiency, (2) a rise in active users improves efficiency directly and through liquidity and investor attention, and (3) higher transaction fees and on-chain volume positively impact efficiency directly and indirectly. Our findings support these hypotheses during Bitcoinâs development and growth periods. However, in the additional development stage, the total effect of active users, transaction fees, and transaction volume becomes negative when considering mediating effects, and largely insignificant when focusing on direct effects. Additionally, we find increased netflow between whales and exchanges, a proxy for institutional activity, improves efficiency. We conclude that as Bitcoinâs market develops, factors such as changing user composition and increased regulatory scrutiny alter the dynamics of on-chain factors and their influence on market efficiency.
Since its creation in 2008, Bitcoin has often been compared to precious metals due to their shared characteristics as safe havens, hedges, and risk diversification tools. This study uses the DCC-GARCH model to analyze dynamic conditional correlations and volatility spillovers between Bitcoin and the returns of gold, copper, silver, and platinum. The findings reveal persistent volatility and clustering in the returns of both Bitcoin and these metals. There is a one-way volatility spillover from gold to Bitcoin, and from Bitcoin to copper, silver, and platinum. Significant dynamic conditional correlations are observed between Bitcoin and both gold and copper, while no significant correlations are found with silver and platinum. These results provide valuable insights for portfolio diversification strategies and inform policymaker decisions in financial markets.
This study investigates the causal relationships between Bitcoin and the US Dollar (USD), Gold, and BIST100 Index as alternative investment instruments. Employing Hongâs variance causality test, the research explores spillover effects in mean and volatility. Using daily data from September 17, 2014, to October 13, 2023, the study reveals a one-way average causality from Bitcoin to BIST100 and the USD. Variance test results show a two-way volatility spillover between Bitcoin and USD, Gold, and BIST100. Hacker-Hatemi-J symmetric causality test detects a one-way causality from Bitcoin to the USD, while Hatemi-J asymmetric test reveals a unidirectional causality from positive Bitcoin shocks to negative shocks of BIST100 and Gold, and bidirectional causality with USD's negative shocks. Additionally, a bidirectional causality exists from Bitcoin's negative shocks to Gold's positive shocks and a unidirectional causality to USD's negative shocks. Recognizing Bitcoin as a financial asset sheds light on its interaction with traditional markets, aiding investors in refining strategies. In summary, this study enhances comprehension of cryptocurrency's role by emphasizing the causal link between Bitcoin and the USD.
We discover a novel flight-to-safety (FTS) effect from cryptocurrency markets to stock markets, triggered by a series of hacking attacks on cryptocurrency exchanges. This phenomenon is driven by heightened uncertainty, which increases investorsâ risk awareness and prompts asset reallocation in favour of safer stock markets over riskier cryptocurrency markets. We conduct an extensive global examination of this effect across 39 countries and confirm this novelty. This effect is amplified by frequent attacks when investorsâ risk awareness is strengthened. Notably, social media sentiment surrounding these attacks serves as both a timely warning indicator for upcoming hacking events and a measure of the FTS pressure following such attacks. We conclude that the collapsed investor confidence and increased risk aversion are the primary cause of such an effect. We further substantiate the FTS hypothesis by offering evidence of significant abnormal fund flows into US mutual funds following these hacking events. As such, through the lens of cyber attacks, we document how a shock in cryptocurrency markets is transmitted into stock markets via investorsâ FTS behaviour. ⢠We discover a flight-to-safety (FTS) effect from cryptocurrency to stock markets. ⢠The FTS effect is amplified by more frequent cyberattacks. ⢠Social media sentiment can warn upcoming hacking events and measure FTS pressure. ⢠The FTS is driven by collapsing investor confidence and heightened risk aversion. ⢠Evidence from US mutual fund supports our novel FTS effect.