As the cryptocurrency market rapidly evolves and solidifies its significance within the global financial system, understanding the dynamic characteristics of returns has become increasingly critical. This study examines nine major cryptocurrencies by market capitalization from 1 January 2017, to 22 November 2023, employing the Mann-Kendall breakpoint test, Pettitt test, wavelet analysis, and TVP-VAR model to uncover the trends, breaks, and cross-category correlations of returns. The findings reveal that most cryptocurrencies exhibit no significant return trends. However, the smart contract platform category experienced a pivotal shift in the latter half of 2019, followed by a substantial improvement in market performance. Additionally, smart contract platforms and alternative currencies exhibit similar return patterns, whereas stablecoins remain relatively independent. Nevertheless, during exceptional periods, the trends of all three asset classes tend to converge. Before breakpoints, cryptocurrency correlations generally intensify, while post-breakpoint correlations gradually weaken. During special market events, smart contract platforms exert a pronounced influence, whereas stablecoins maintain stability. This study bridges the gap in long-term return dynamics and cross-category interactions, providing investors with profound insights into market mechanisms and offering policymakers crucial guidance for regulatory and risk management strategies.
Diego Mazzitelli, Elia Fiorenza, InĂšs 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.
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 ± 0 . 0048 for q =2), GOLDâBTC (H = 0 . 5039 ± 0 . 0058 for q =2) and GOLDâLTC (H = 0 . 5044 ± 0 . 0057 for q =2) that are Brownian, and GOLDâPOLYGON (H = 0 . 4917 ± 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.
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.
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.
Cryptocurrencies have rapidly emerged as a significant financial asset class, influencing global monetary systems and financial markets. However, their extreme volatility, speculative nature, and evolving regulatory landscape pose challenges to investors, policymakers, and financial analysts. This study presents an in-depth quantitative analysis of cryptocurrency volatility and risk assessment, focusing on Bitcoin (BTC-USD) and its correlation with traditional financial assets, including the EUR/USD exchange rate and S&P 500 index. Our research employs Generalized Autoregressive Conditional Heteroskedasticity (GARCH) modeling to measure the dynamic volatility patterns of Bitcoin, revealing the assetâs substantial fluctuations over time and its sensitivity to market shocks. Additionally, we utilize Monte Carlo simulations to forecast potential future price movements of Bitcoin, highlighting risk scenarios and the probability distribution of price trajectories over a one-year period. The Value-at-Risk (VaR) model is implemented to estimate potential losses within a given confidence interval, providing a robust measure of downside risk. Furthermore, the study examines the integration of cryptocurrency markets with traditional financial instruments by analyzing cross-asset correlations and volatility spillover effects. The findings suggest that while Bitcoin remains a highly volatile asset, its correlation with the broader financial system is increasing, indicating a potential shift towards mainstream financial adoption. The results contribute to the ongoing debate on whether cryptocurrencies serve primarily as speculative instruments or as viable components of diversified investment portfolios. These insights are valuable for institutional investors, risk managers, and policymakers in designing more effective risk mitigation strategies for cryptocurrency investments.
Purpose This study aims to examine the impact of climate-related risks on cryptocurrency volatility during crisis periods, focusing on the physical risk index (PRI) and transition risk index (TRI). It investigates how acute and chronic climate events, alongside regulatory and technological changes, influence market dynamics in major cryptocurrencies, including Bitcoin, Ethereum, Litecoin and Ripple. Design/methodology/approach A fuzzy logic model is employed to evaluate the effects of PRI and TRI on cryptocurrency volatility. The modelâs accuracy is validated using root mean square error (RMSE) metrics to ensure reliability. Findings The results reveal that acute events (e.g. hurricanes and wildfires) and chronic risks (e.g. long-term environmental disruptions) significantly heighten cryptocurrency volatility. Transition risks, including regulatory and technological shifts, also play a pivotal role. Bitcoin and Ethereum exhibit the highest sensitivities, reflecting the critical influence of climate risks on market stability. Research limitations/implications This study enriches the literature by integrating climate risk factors into cryptocurrency market analysis and advancing fuzzy logic models to assess non-linear interactions in financial markets. It provides a novel framework for evaluating external shocksâ impact on digital assets. Practical implications Investors and market participants can use these findings to incorporate climate risks into their investment strategies, diversify portfolios and anticipate periods of instability. The insights also guide policymakers in developing resilient frameworks that align cryptocurrency regulations with environmental goals. Social implications By linking climate risks to cryptocurrency market behavior, this research emphasizes the need for sustainable investment practices and collaborative policy efforts. It advocates for integrating environmental sustainability into financial systems to mitigate systemic risks and promote economic resilience. Originality/value This research is among the first to apply PRI and TRI within a fuzzy logic framework to cryptocurrency markets, offering new insights into how climate risks drive financial volatility during crisis periods.
Klaus Grobys, James W. Kolari, Davide Sandretto, Syed Jawad Hussain Shahzad · 5 authors
Abstract This paper explores the tail behavior of cryptocurrency momentum strategies and the profitability of volatility-managed momentum portfolios. Our main results derived from using a sample of large-cap cryptocurrencies and equal-weighted momentum portfolios indicate that cryptocurrency momentum is subject to severe crashes. Even a single cryptocurrency can cause insignificant momentum portfolio returns. In line with the literature on volatility-managing equity portfolios, our findings suggest that volatility management is a useful tool for mitigating cryptocurrency momentum crashes. Further corroborative evidence suggests that cryptocurrency momentum appears to be a phenomenon associated with large-cap cryptocurrencies.
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.
Erveton P. Pinto, Marcelo A. Pires, Rone N. da Silva, SıÌlvio M. Duarte QueirĂłs
We report the first application of a tailored Complexity-Entropy Plane designed for binary sequences and structures. We do so by considering the daily up/down price fluctuations of the largest cryptocurrencies in terms of capitalization (stable-coins excluded) that are worth $circa \,\, 90 \%$ of the total crypto market capitalization. With that, we focus on the basic elements of price motion that compare with the random walk backbone features associated with mathematical properties of the Efficient Market Hypothesis. From the location of each crypto on the Binary Complexity-Plane (BiCEP) we define an inefficiency score, $\mathcal I$, and rank them accordingly. The results based on the BiCEP analysis, which we substantiate with statistical testing, indicate that only Shiba Inu (SHIB) is significantly inefficient, whereas the largest stake of crypto trading is reckoned to operate in close-to-efficient conditions. Generically, our $\mathcal I$-based ranking hints the design and consensus architecture of a crypto is at least as relevant to efficiency as the features that are usually taken into account in the appraisal of the efficiency of financial instruments, namely canonical fiat money. Lastly, this set of results supports the validity of the binary complexity analysis.
Financial assets often exhibit explosive price surges followed by abrupt collapses, alongside persistent volatility clustering. Motivated by these features, we introduce a mixed causalânoncausal invertibleânoninvertible autoregressive moving average generalized autoregressive conditional heteroskedasticity (MARMAâGARCH) model. Unlike standard ARMA processes, our model admits roots inside the unit disk, capturing bubble-like episodes and speculative feedback, while the GARCH component explains time-varying volatility. We propose two estimation approaches: (i) Whittle-based frequency-domain methods, which are asymptotically equivalent to Gaussian likelihood under stationarity and finite variance, and (ii) time-domain maximum likelihood, which proves to be more robust to heavy tails and skewnessâcommon in financial returns. To identify causal vs. noncausal structures, we develop a higher-order diagnostics procedure using spectral densities and residual-based tests. Simulation results reveal that overlooking noncausality biases GARCH parameters, downplaying short-run volatility reactions to news (α) while overstating volatility persistence (ÎČ). Our empirical application to Bitcoin and Ethereum enhances these insights: we find significant noncausal dynamics in the mean, paired with pronounced GARCH effects in the variance. Imposing a purely causal ARMA specification leads to systematically misspecified volatility estimates, potentially underestimating market risks. Our results emphasize the importance of relaxing the usual causality and invertibility assumption for assets prone to extreme price movements, ultimately improving risk metrics and expanding our understanding of financial market dynamics.
Wided Khiari, Azhaar Lajmi, Amira Neffati, Ahmed El Fahem
Purpose This study aims to examine the effect of cryptocurrency frauds on the price fluctuations of the cryptocurrency market. Design/methodology/approach To examine the effects of cryptocurrency frauds on cryptocurrency market, the authors have collected data of 38 cryptocurrencies price fluctuations between 01/01/2020 and 28/11/2021. The authors have used the multidimensional scaling method (MDS) to explore the price fluctuations of the cryptocurrency market and its relationship with the cryptocurrency market between 2020 and 2021. Findings The study results showed that even though cryptocurrencies are categorised into Bitcoin, Altcoins and Stablecoins, the effect of the frauds is specific to their usage cases. Bitcoin and certain Altcoins were affected in a certain way compared to Ethereum and cryptocurrencies specialised in smart contracts. Cryptocurrencies such as Tron and Elrond with the specifications of staking had a different reaction and cryptocurrencies that contribute to the development and enhancement of blockchain infrastructure had a different reaction throughout these incidents. Stablecoins, however, were unaffected by the fraud incidents because of their reliability and their correlation to real assets such as fiat money, petrol and gold. Practical implications The study enables financial institutions to understand how to react to cryptocurrencies, which are both an opportunity and a challenge for them. Consequently, banks should strengthen their security measures to protect customer funds from the risks associated with fraud and cyber-attacks. They should also implement risk management measures and guarantee the integrity of their systems to ensure stability and confidence in the use of cryptocurrencies. In addition, institutions should work in collaboration with the authorities to overcome regulatory challenges and create a favourable framework for the use of cryptocurrencies. Originality/value The main contribution of this paper is to examine this topic, which has been very little explored in previous work. The lack of theoretical and empirical evidence concerning this study represented a challenge, and an originality as studies concerning cryptocurrency fraud are limited, if not non-existent. The second contribution is quantitative and uses a MDS to examine price fluctuations in the cryptocurrency market and its relationship with the cryptocurrency market.
Abstract During the last years, financial market contagion has become a critical concern for policymakers and investors, particularly with respect to the financial stability of cryptocurrency platforms. This paper explores the contagion effect among crypto exchanges employing the SusceptibleâInfectedâRecovered (SIR) model with time delay and investigates possible cooperative strategies. The SIR dynamical system is integrated with the replicator equation of evolutionary game theory to study the interplay between the spread of risk and the propensity of cryptocurrency platforms to become cooperative under the pressure of financial contagion. Different equilibrium points which correspond to both pure and mixed cooperative strategies characterize the resulting model. We carry out a theoretical analysis of the problem by studying the asymptotic behavior in the steady state. In addition, using extensive cryptocurrency market data from 2017 to 2023, we identify the key factors driving contagion and assess the dynamics of cooperative versus non-cooperative behavior. Our findings point out that cooperative strategies are essential to ensure financial stability, particularly in the long term, as they mitigate systemic risks and foster resilience. These results provide critical insights for policy makers and investors, offering actionable strategies to enhance the robustness of crypto markets and address the growing challenges of financial contagion in the digital asset ecosystem.