Benjamin Mudiangombe Mudiangombe, John Weirstrass Muteba Mwamba
This study explores the new insights into the integration and dynamic asymmetric volatility risk spillovers between Bitcoin, currency pairs (USD/ZAR, GBP/ZAR and EUR/ZAR), and traditional financial assets (ALSI, Bond, and Gold) in South Africa using daily data spanning the period from 2010 to 2024 and employing Time-Varying Parameter Vector Autoregression (TVP-VAR) and wavelet coherence. The findings revealed strengthened integration between traditional financial assets and currency pairs, as well as weak integration with BTC/ZAR. Furthermore, BTC/ZAR and traditional financial assets were receivers of shocks, while the currency pairs were transmitters of spillovers. Gold emerged as an attractive investment during periods of inflation or currency devaluation. However, the assets have a total connectedness index of 28.37%, offering a reduced systemic risk. Distinct patterns were observed in the short, medium, and long term in time scales and frequency. There is a diversification benefit and potential hedging strategies due to goldâs negative influence on BTC/ZAR. Bitcoinâs high volatility and lack of regulatory oversight continue to be deterrents for institutional investors. This study lays a solid foundation for understanding the financial dynamics in South Africa, offering valuable insights for investors and policymakers interested in the intricate linkages between BTC/ZAR, currency pairs, and traditional financial assets, allowing for more targeted policy measures.
We quantify the economic consequences of Ethereumâs transition from Proof-of-Work to Proof-of-Stake. We document a structural break in inflation dynamics, shifting to an ARIMA(2,1,1) process with deflationary tendencies. The relationship between inflation and staking returns weakens post-Merge, challenging assumptions about incentive structures in Proof-of-Stake systems. Analysis reveals significant changes in market microstructure, including reduced spot trading volume and altered futures market behavior. We identify complex feedback loops between on-chain metrics and market variables, defying traditional equilibrium models. Our results suggest the need for new economic models to understand Proof-of-Stake systems and their market implications.
The goal of this research is to analyze political uncertainty's short- and long-term impact on the volatility of Bitcoin throughout the US presidential election period (2023-2024), and test its value as a hedge asset in the face of rising political tensions. The GARCH-MIDAS model used here selects high-frequency daily returns on Bitcoin and low-frequency macroeconomic and political data, such as the Economic Policy Uncertainty Index (EPU), the Volatility Implied Index (VIX), and an irregular dummy variable for political events (POL_EVT). The empirical evidence depicts how Bitcoin is highly sensitive to political shocks, both sudden (short-run) and institutional (long-run), with its volatility speeding up as uncertainty increases. In contrast to traditional safe-haven securities such as gold or government bonds, Bitcoin does not exhibit hedging behavior during times of political turmoil. Instead, it is a high-risk speculation asset, responding in real-time but destabilizing to evolving political events. Moreover, the GARCH-MIDAS model proved to be outstanding in capturing the time and non-linear impacts of uncertainty compared to standard models, buttressing the importance of including political factors when studying the volatility dynamics of cryptocurrencies.
Abstract This paper presents a systematic literature review of 137 peer-reviewed publications from 41 journals, examining the interconnectedness between cryptocurrencies and traditional financial markets. Using a rigorous three-stage methodology for study selection, we identify key research themes including spillover effects, volatility transmission, interdependence, hedge effectiveness, and safe-haven properties of cryptocurrencies. Our analysis reveals that GARCH-based models dominate early work on volatility and contagion, while more recent studies adopt advanced approaches, such as cross-quantilogram, wavelet coherence, and multifractal detrended cross-correlation, to capture non-linear, time-varying relationships without assuming stationarity. Our review offers three major contributions. First, we provide a comprehensive classification of the interconnectedness between different types of cryptocurrencies and financial markets, highlighting their evolving roles as hedges, safe havens, or diversifiers. Second, we synthesize empirical findings to show how spillovers, time-varying correlations, tail dependencies, and contagion risks intensify under major events, such as COVID-19, regulatory shifts, and geopolitical conflicts. Third, we draw attention to overlooked areas, including emerging market dynamics and macroeconomic determinants. We recommend that policymakers implement early warning systems and proactively monitor volatility and connectedness in crypto markets to reduce contagion risks and maintain financial stability. Policy frameworks should consider the unique features of crypto markets and the time-varying interlinkages between cryptos, commodities, fiat currencies, and equities. Investors, in turn, should track cryptocurrency price movements closely, as they provide valuable signals for forecasting broader market trends and improving portfolio risk management. These insights have practical implications for risk mitigation and decision-making in increasingly integrated financial systems.
The FTX collapse marked a significant shock to global crypto markets, prompting concerns about systemic contagion. This paper investigates the dynamic connectedness between cryptocurrencies, DeFi tokens, and tech stocks, focusing on the systemic impact of the FTX collapse. We decompose total, internal, and external connectedness across asset groups using a time-varying parameter VAR model. The results show that post-FTX, Bitcoin and Ethereum intensified their roles as core shock transmitters, while Tether consistently acted as a volatility absorber. DeFi tokens exhibited heightened intra-group spillovers and occasional external influence, reflecting structural fragility. Tech stocks remained largely insulated, with reduced cross-market linkages. Network visualizations confirm a post-crisis fragmentation, characterized by denser internal crypto-DeFi ties and weaker inter-group contagion. These findings have important policy implications for regulators, investors, and system designers, indicating the need for targeted risk monitoring and governance within decentralized finance.
Amid growing global urgency for climate action, innovative financial mechanisms are critical for advancing renewable energy transitions in developing economies. This study investigates the role of financial technology (fintech), with a focus on foreign portfolio investment (FPI), in influencing renewable energy investment (REINV) across 54 developing countries in Africa, Asia, and Latin America from 2010 to 2023. Employing a multi-method empirical approach, comprising Spatial Durbin Models (SDM), Quantile Regression (QR), Stochastic Frontier Analysis (SFA), and Spatial Quantile Regression (SQR), the research captures spatial dependencies, distributional heterogeneity, and efficiency dynamics. The SDM results indicate that FPI significantly increases REINV both directly (1.112) and indirectly through spillover effects (0.445), supported by significant spatial autocorrelation (0.334). Economic development and institutional quality also play key roles, with GDP per capita and institutional quality exerting positive and significant direct effects. Quantile regression reveals that FPI has a stronger influence at higher quantiles of REINV, with coefficients rising from 0.745 to 1.445, highlighting distributional inequality in fintech impact. SFA results show that FPI also enhances technical efficiency (0.912), though diminishing marginal returns are evident. Greater financial depth and electricity access reduce inefficiency, while inflation worsens it. Spatial quantile regression further confirms that regional spillovers are more pronounced among high-investment countries, underscoring the role of spatial dynamics in clean energy financing. The findings suggest that fintech can be a catalyst for renewable energy growth, especially in countries with higher institutional and financial capacity. Policy recommendations include strengthening digital infrastructure, enhancing regulatory coordination, and ensuring macroeconomic stability to fully leverage fintech's potential. Future research should explore emerging fintech tools such as decentralized finance and blockchain-based green bonds.
This paper examines the interconnection and wavelet coherence between the green cryptocurrency market and the green conventional market, utilizing daily data. The research period covers 1 July 2020 to 30 September 2024. Employing the time-varying parametric vector autoregression (TVP-VAR) model and wavelet coherence analysis, we capture both short- and long-term spillovers across markets. The results show that cryptocurrencies, particularly Binance and Litecoin, act as dominant transmitters of volatility and return shocks, while green conventional indices function mainly as receivers with strong self-dependence. Spillover intensity is highly time-varying, with peaks during periods of systemic stress, particularly during the COVID-19 pandemic, and troughs indicating diversification opportunities. These findings advance the literature on systemic risk and portfolio design by showing that crypto assets can simultaneously amplify vulnerabilities and enhance diversification when combined with green finance instruments. For policy, the results highlight the need for regulatory frameworks that integrate sustainability taxonomies, mandate environmental disclosures for digital assets, and incentivize energy-efficient blockchain adoption to align crypto markets with sustainable finance objectives. This research enhances our understanding of the interrelationship between green investments and cryptocurrencies, providing valuable insights for investors and policymakers on risk management and diversification strategies in an increasingly sustainable financial landscape.
Accreditation has historically played a central role in securities regulation, seeking to balance investor protection, market access, and capital formation. Traditionally, regulatory frameworks have relied on wealth or income thresholds as proxies for investor sophistication, premised on the assumption that individuals with greater financial resources are better equipped to manage risk and obtain professional advice. However, in rapidly evolving crypto-asset markets, these wealth-based criteria have become increasingly misaligned with market realities. Such thresholds frequently exclude technically proficient but less affluent participants, thereby perpetuating inequality and conflicting with the inclusive ethos of digital finance. Moreover, these criteria have failed to prevent significant losses among wealthy accredited investors, as evidenced by the collapses of Terra-Luna, Three Arrows Capital, and FTX. Competence-based frameworks are still underdeveloped, unevenly applied, and can become overly formal, while traditional disclosure rules do not fully address the technical and behavioral challenges of decentralized finance. This article takes a critical look at accreditation in crypto-asset markets, drawing on legal, empirical, and normative analysis. By comparing the United States, European Union, Singapore, and Russia, and examining cases like the ICO boom, Singaporeâs regulatory sandboxes, and the Terra-Luna and FTX collapses, the article shows that wealth-based accreditation falls short in fairness and effectiveness. It proposes a hybrid approach that combines competence assessments, crypto-specific disclosure, prudential safeguards, regulatory sandboxes, and international cooperation. This article contends that reforming accreditation constitutes a fundamental transformation in the approach to investor protection, advancing principles of fairness, legitimacy, and systemic robustness. By introducing a hybrid framework grounded in fairness and empirical evidence, the article contributes to policy discourse and informs scholarly understanding of the evolution of financial regulation in the context of digital innovation.
We examine how Bitcoin and Ethereum volatilities react to macroeconomic data releases from the US, Germany, and Japan before, during, and after their official announcements. Analyzing 5-minute observations from 2016 to 2023, we find that volatility responds significantly to select news categories, particularly in the pre-announcement period. US monetary policy news consistently drives volatility across all phases, with a heightened impact during the pandemic. Ethereum shows greater sensitivity to US announcements than Bitcoin but remains unresponsive to non-US news, especially before the pandemic. Our findings highlight the need to account for both pre- and post-announcement periods when evaluating the intraday price impact of macroeconomic news on cryptocurrencies. ⢠We examine the response of Bitcoin and Ethereum volatilities to macroeconomic figures. ⢠We show that volatility reacts only to a few news categories. ⢠US monetary policy news consistently affects volatility before, during, and after its release. ⢠Ethereum volatility is more sensitive to US announcements compared to Bitcoin. ⢠Ethereum exhibits less pre-announcement volatility and less sensitivity to non-US news.
This paper surveys the academic literature concerning the bubble periods in the cryptocurrency market. This study aims to understand the historical and developmental trajectory of the cryptocurrency market through its various bubble periods. This study also identifies the factors contributing to bubble formation. The study is based on the PRISMA framework for literature review. Based on the review, the cryptocurrency market experienced four major bubbles in 2011, 2013, 2017, and 2021. The enthusiasm for cryptocurrency innovation triggered the 2011 bubble. The 2013 bubble was influenced by the economic crisis that channeled funds to the cryptocurrency market due to their centralized nature. In 2017, the possibilities of Web 3.0 and altcoins increased the enthusiasm of crypto investors. The crypto winter of 2017 subsided with the rise of non-fungible tokens (NFTs), stimulating interest and driving prices in the cryptocurrency market. Specifically, speculation, media coverage, investor sentiment, herding, volatility, and coexplosivity are significant factors that trigger bubble development. Moreover, government policies and regulations can be crucial in sustaining and bursting the bubbles. This review offers a comprehensive view of academic studies on bubble periods in the cryptocurrency market. This study also provides a chronological overview of major bubble periods that have significantly influenced the market development. This study is one of the first reviews conducted to understand the development of the cryptocurrency market through bubble periods and the factors contributing to bubble formation. The study also follows the PRISMA framework for structuring the review, as the literature lacks reviews on bubble periods on the basis of this framework.
CÄtÄlin Gheorghe, Oana Panazan, Hind Alnafisah, Ahmed Jeribi
This study investigates the asymmetric responses of AI and ESG Exchange Traded Funds (ETFs) to geopolitical and financial uncertainty, with a focus on resilience across market regimes. The NASDAQ-100 and MSCI ESG Leaders indices are used as proxies for thematic ETFs, and their dynamic interlinkages are examined in relation to volatility indicators (VIX, GPR), alternative assets (Bitcoin, Ethereum, gold, oil, natural gas), and safe-haven currencies (CHF, JPY). A daily dataset spanning the 2016â2025 period is analyzed using Quantile-on-Quantile Regression (QQR) and Wavelet Coherence (WCO), enabling a granular assessment of nonlinear, regime-dependent behaviors across quantiles. Results reveal that ESG ETFs demonstrate stronger downside resilience under extreme uncertainty, maintaining stability even during periods of elevated geopolitical and financial risk. In contrast, AI-themed ETFs tend to outperform under moderate-risk conditions but exhibit greater vulnerability during systemic stress, reflecting differences in asset composition and investor risk perception. The findings contribute to the literature on ETF resilience and cross-asset contagion by highlighting differential behavior patterns under varying uncertainty regimes. Practical implications emerge for investors and policymakers seeking to enhance portfolio robustness through thematic diversification during market turbulence.
This study analyzes the volatility of Bitcoin using stochastic volatility models fitted to one-minute transaction data for the BTC/USDT pair between 1 April 2023, and 31 March 2024. Bernstein polynomial terms were introduced to accommodate intraday and intraweek seasonality, and flexible return distributions were used to capture distributional characteristics. Seven return distributionsânormal, Student-t, skew-t, Laplace, asymmetric Laplace (AL), variance gamma, and skew variance gammaâwere considered. We further incorporated explanatory variables derived from the trading volume and price changes to assess the effects of order flow. Our results reveal structural market changes, including a clear regime shift around October 2023, when the asymmetric Laplace distribution became the dominant model. Regression coefficients suggest a weakening of the volumeâvolatility relationship after September and the presence of non-persistent leverage effects. These findings highlight the need for flexible, distribution-aware modeling in 24/7 digital asset markets, with implications for market monitoring, volatility forecasting, and crypto risk management.
This article presents a comprehensive analysis of the impact of cryptocurrencies on the economic and environmental security of the G7 countries, exploring both the potential risks and prospects. The study focuses on the United States, Canada, the United Kingdom, France, Germany, Italy, and Japan, offering a detailed exploration of the increasing adoption of cryptocurrencies in these nations. Despite the benefits such as enhanced financial inclusion and cross-border transaction efficiency, cryptocurrencies pose significant challenges, including their use in illicit activities like money laundering and terrorism financing. The research critically examines the substantial energy consumption associated with certain cryptocurrency mining processes, particularly Proof-of-Work mechanisms, and their consequent environmental impacts, including carbon emissions, electronic waste, and air pollution. It investigates the corresponding energy policies and regulatory responses emerging within the G7 to address these concerns, alongside the development of more energy-efficient alternatives like Proof-of-Stake and the push for renewable energy in mining. The article critically examines these dual aspects, highlighting the measures implemented by regulators and policymakers to mitigate risks. It also delves into the evolving landscape of Central Bank Digital Currencies (CBDCs) and their potential role in enhancing financial system efficiency and security, including considerations for their energy footprint. The study employs a robust methodological framework, combining statistical analysis of market trends, case studies, and policy analysis to provide a balanced view of the current state and future trajectory of cryptocurrencies in the G7 countries. By offering a nuanced understanding of both the opportunities and threats posed by digital currencies, including their energy and environmental dimensions, this article contributes to the ongoing discourse on their integration into global financial systems and their implications for sustainable economic security.
Among the plethora of literature on interlinkages in markets, more focus has been on peripheral factors. This study attempts to fill this gap by exploring volatility as driver for interlinkages between Bitcoin, Ethereum, Tether, USD-Coin, Binance Coin (BNB), and the crypto-volatility-index (CVI) from April 2019 to August 2022. Using various wavelet techniques, the study depicts significant interlinkages across short-term, medium-term, and long-term horizons, with relatively stronger interlinkages in the long term. The findings confirm that while CVI does not drive these interlinkages, Ethereum, Bitcoin, and CVI play dominant roles in the short, interim, and medium-term periods, respectively, offering new insights into the dynamism of cryptocurrency markets.
This study delves into the differences between traditional financial markets, as proxied by their corresponding future contracts, and the cryptocurrency market, focusing on Bitcoin, during major global events: the COVID-19 pandemic, the Russia-Ukraine war, and the IsraelâPalestine conflict. It reveals Bitcoinâs increased trading volume post-COVID-19, highlighting its appeal as a digital safe haven. This trend persists during subsequent crises, suggesting a strategic shift towards cryptocurrencies as diversification tools. Despite volume fluctuations, Bitcoinâs price stability reflects investor confidence in its long-term viability. The significant change in EuroStoxx 50 returns during the IsraelâPalestine conflict, highlights localized geopolitical influences on markets. The study underscores the importance of considering both global and regional factors in investment decisions. It emphasizes cryptocurrenciesâ growing significance in the global financial market, particularly during crises, and suggests further exploration into investor behavior and regulatory effects. Understanding these dynamics is crucial for navigating the evolving financial landscape.
ABSTRACT This study aims to conduct an inâdepth analysis of the complex nonlinear dependence relationships between cryptocurrencies and gold within the stocks of BRICS countries. The study employs a GARCHâEVTâVineâCopula and wavelet coherence models to evaluate the interconnectedness, tail risk and Coâmovement pattern of these assets before and after the outbreak of COVIDâ19. The findings reveal that, prior to COVIDâ19, significant tail dependence existed between China's stock market, the cryptocurrency index, and the indices of India and Russia, while other indices exhibited only weak dependence. However, after the outbreak of COVIDâ19, the tail dependence among variables became more pronounced. The South African stock market appears to have emerged as the center of extreme lowerâtail risk spillovers among the studied variables. During the COVIDâ19 outbreak, cryptocurrency markets demonstrated stronger coherence with global stock markets than gold, especially in the US market, potentially compromising their diversification effectiveness. Furthermore, our empirical results were validated by the Kupiec test and the Christoffersen test. The results of this study not only enhance the theoretical understanding of risk management in emerging markets during periods of extreme market crises but also provide valuable insights for policymakers in formulating strategies to ensure financial market stability.
This study employs novel quantile time-frequency connectedness approach to explore the dynamic connectedness among sustainable assets (sustainable, green bond, and clean energy index), traditional assets (traditional index and crude oil), and cryptocurrency. This method assesses the impact of uncertain events on asset relationships. Findings indicate median connectedness of 36.94% in the short run and 4.81% in the long run, with short-term dynamics dominating system transmission. The traditional index is the primary transmitter of short-run shocks, while the green bond index leads in long-run shocks. Diversification across asset classes is recommended for effective hedging and optimal returns during extreme market conditions.
ABSTRACT This study aims at bridging critical gaps in the existing cryptocurrency research by exploring combinations of technological, macroeconomic and behavioural factors, namely, economic agents' expectations and the size of influence that each of them has on the Bitcoin price movements. In contrast to the existing studies that focused on individual determinants and estimated aggregate effects thereof, in this study, fuzzyâset qualitative comparative analysis (fsQCA) is applied to determine configurations of drivers to determine the Bitcoin price and used necessary condition analysis (NCA) to quantify the magnitude of the effects using the monthly data between 2011 and 2022. Findings show that economic agents' expectations such as OECD's Business Confidence Index, Consumer Confidence Index and Composite Leading Indicator emerge as influential variables of Bitcoin, surpassing traditional drivers like Gold and Financial Stress Index. Among these, Business Confidence Index and Composite Leading Indicator exhibit a very large effect on Bitcoin prices, and from the technology variable group, Average Block Size exhibits a very large effect on Bitcoin prices. fsQCA indicates that nine distinct configurations contribute to high Bitcoin prices and eight configurations lead to low Bitcoin prices, thus depicting equifinality in Bitcoin price determination. These insights can provide policymakers and investors with a better understanding of the Bitcoin price dynamic by finding out necessary variables and equifinal pathways towards either high or low prices, thus promoting better risk management activities, as well as regulatory approaches to this highly dynamic asset class.
ABSTRACT In this article, we discuss how far Bitcoin has come since its formulation 16 years ago and explore promising areas for future research in finance. The future research topics fall into the following three broad areas: institutional and country adoption, criminality, and Bitcoin's relationship to stablecoins. After a brief discussion of the existing literature, we provide a list of open research questions for future research to explore.
Erdinç AkyÄąldÄąrÄąm, Ahmet Faruk Aysan, OÄuzhan Ăepni, Shaen Corbet
This study investigates the influence of news-based sentiment on the returns of Decentralized Finance (DeFi) coins using a sample of 27 coins from January 2017 to March 2022. Our results indicate that news sentiment significantly impacts DeFi returns, with negative sentiment exerting a stronger influence than positive sentiment. Transaction volume and network security also emerge as critical drivers of DeFi coin returns. Smaller coins are more sensitive to news sentiment, showing greater return volatility. The impact of news-based sentiment is more pronounced during weekdays, likely due to reduced participation by institutional investors and trading algorithms. These findings have important implications for investors and policymakers, suggesting multiple pathways for market manipulation under specific conditions. ⢠We investigate the relationship between DeFi coins and news-based sentiment. ⢠Negative sentiment has a greater impact on returns. ⢠Transaction volume and network security drive returns. ⢠Smaller DeFi coins are more susceptible to news sentiment and greater return volatility. ⢠DeFi returnsâ sensitivity to news-media sentiment is significantly elevated during weekdays.
We investigate the high-frequency dynamics of Bitcoin and Ethereum perpetual futures traded on Binance from January 2020 to December 2024. After a thorough discussion of the stylized facts and particularities of Bitcoin perpetual futures, based on previous research in futures markets, we evaluate the fit of two competing models of market microstructure: the Mixture of Distributions Hypothesis (MDH) and the Intraday Trading Invariance Hypothesis (ITIH). Using intraday data at different levels of aggregation, we investigate the relationship between return volatility per transaction and trade size. We find evidence favoring the MDH in the crypto futures market.
This study explores the sustainability-enhancin g financial effects of blockchain on carbon-linked digital markets. Drawing on a panel dataset of daily transactions from leading tokenized carbon platforms between 2020 and 2023, the study applies a fixed-effects Difference-in-Differences (DiD) framework to assess how the introduction of blockchain-based infrastructure influences carbon asset prices and trading volumes. Our findings reveal that higher transaction costs, often viewed negatively, may actually signal trusted infrastructure in illiquid sustainability markets, boosting investor confidence. The results confirm that blockchain adoption improves pricing efficiency under specific liquidity conditions, while exhibiting limited short-term effects on volume. It offers new evidence on how blockchain can strengthen carbon markets; reduce transactional inefficiencies, and advance climate action and sustainable development goals (SDGs). These insights inform policymakers, regulators, and investors aiming to design resilient, efficient, and scalable digital carbon markets.
Silvia Edelweiss Crusco dos Santos, HĂŠlder SebastiĂŁo, Nuno Silva
Using daily data from November 9, 2017 to December 31, 2022, this paper uses Granger causality in the mean and the distribution to investigate the transmission of information between return, volume, volatility, and illiquidity for Bitcoin and the nine most important altcoins in terms of market capitalization. Additionally, the forecastability of Bitcoin returns is examined using linear models with different predictor spaces estimated using LASSO and the performance of several trading strategies devised upon those forecasts is assessed. The causal relationships between returns, volumes and volatilities of Bitcoin and each altcoin are more evident in the left tail of the distribution, where Bitcoin acts mostly as a transmitter of information, and in the right tail for causality regarding illiquidity. In bullish markets, Bitcoin acts mostly as a receiver of information. The best Bitcoin trading strategy is based on the model which incorporates the information on all cryptocurrencies, exhibiting a cumulative return of 331% and an annualized Sharpe ratio of 94.59%, considering an enter/exit threshold of 0.25% and after 0.5% round-trip transaction costs. These results are statistically significant when compared with the buy-and-hold strategy, which renders a cumulative return of 121% and a Sharpe ratio of 64.74%. These results point out the importance of considering information from other cryptocurrencies to forecast and trade on Bitcoin.