Abstract ValueâatâRisk (VaR), the primary measure of downside risk in market risk management, relies heavily on the accuracy of volatility forecasts produced by risk models. This paper shows that, for forecasting the VaR of cryptocurrencies, the timeâheterogeneous Student's t autoregressive model outperforms standard models commonly used by practitioners.
Abstract Cryptocurrency markets have evolved into a vital segment of the global financial ecosystem, drawing considerable interest from both investors and regulatory bodies. Yet, their extreme price instability demands innovative strategies for risk mitigation and investment that diverge from conventional financial practices. This research focuses on analyzing the volatility patterns of leading cryptocurrenciesâBitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB)âby employing GARCH-family models such as GARCH, EGARCH, TGARCH, and CGARCH. Through a comparative evaluation of these models, the study identifies the optimal framework for characterizing cryptocurrency market volatility. Utilizing daily closing prices from Yahoo Finance (January 1, 2019, to January 8, 2025), the analysis reveals that TGARCH outperforms others for BTC, EGARCH for ETH, and CGARCH for BNB, underscoring the critical role of asymmetric volatility in these markets. This work advances existing research by offering a detailed comparison of GARCH-based approaches and practical insights for risk evaluation and portfolio optimization.
Senior Financial Markets Dealer, Nassau, The Bahamas, Vladyslav Yakymashko
This article investigates the phenomenon of volatility clustering in the cryptocurrency markets, focusing on Bitcoin (BTC) and Ethereum (ETH), through empirical time-series analysis. The study employs quantitative methods, including GARCH modeling, to identify persistent patterns in the price fluctuations of the two leading digital assets. The analysis is based on trading data over an extended period, encompassing both phases of high market turbulence and periods of relative stability. Adopting an interdisciplinary approach that integrates behavioral finance, econometrics, and financial market theory, particular attention is given to identifying autocorrelation, memory effects, and the structure of market shocks. The findings demonstrate that volatility clustering in BTC and ETH significantly differs from similar phenomena in traditional financial markets, largely due to their speculative nature, asset novelty, and the influence of both institutional and retail participants. The identified patterns enhance risk profiling for crypto assets and may be applied in hedging strategies, automated trading algorithm development, and investment portfolio optimization. Additionally, the study highlights the importance of accounting for both micro- and macroeconomic factors influencing market behavior. The article is intended for researchers in digital finance, risk managers, analysts, investors, and anyone examining unstable assets in conditions of high uncertainty and a rapidly changing informational landscape.
This study aims to demystify the link between Bitcoin pricing and the associated electricity costs, constituting the most significant cost in mining Bitcoin. The article revisits the typical Cost-price (electricity consumption -Bitcoin price) relationship in the context of Bitcoin. The research question is answered using the Nonlinear Autoregressive Distributed Lag (NARDL) Model complemented with Multiple Breakpoints Least Squares Regression (MBLSR). The study analyzes monthly data from various sources from March 2017 to September 2023 and is segregated into four different regimes. The convergence in both techniques provides rigour and robustness to the results. The findings reveal the asymmetric relationship where Bitcoin's energy consumption does not increase significantly with a positive change in Bitcoin Price. This behaviour is counterintuitive given that electricity consumption is expected to increase in a high price period because of more profit margins. The flooding of accumulated Bitcoins by the miners in high price periods may be a contributing reason for no significant increase in the electricity consumption in mining Bitcoins. Conversely, the fall in Bitcoin prices will reduce the energy consumed by the Bitcoin Network conforming to the anticipated pattern. This behaviour is in stark contradiction to the Law of Supply and is well explained by the Bitcoin miners' operational strategy in the Boom and Recession period. Relying on the asymmetric behaviour, investors can revamp their strategy to make profits in the market. In addition, findings suggest policymakers try to limit credit accessibility to miners in the bust to reduce the colossal energy consumption of Bitcoin.
Halilibrahim Gökgöz, Aamir Aijaz Syed, Hind Alnafisah, Ahmed Jeribi
The recent economic turmoil and the increasing volatility of bitcoins have necessitated the need for exploring safe-haven assets for bitcoins. In this quest, the present study aims to investigate the safe haven for bitcoins by examining the dynamic relationship between bitcoins, gold, foreign exchange, and stablecoins. This is achieved by calculating hedge ratios and portfolio weight ratios for various asset classes, by employing adaptive-based techniques such as generalized orthogonal generalized autoregressive conditional heteroscedasticity, corrected dynamic conditional correlation, corrected asymmetric dynamic conditional correlation, and asymmetric dynamic conditional correlation under various market and time-varying conditions. The empirical estimate reveals that all the selected asset classes are effective risk diversifiers for bitcoins. However, among all the asset classes, as per the hedge and portfolio weight ratio, Japanese yen, stablecoin for Japanese yen and Great Britain Pound, and Crypto Holding Frank Token (lowest-cost hedging strategies) are the most effective risk diversifiers when compared with bitcoins. Moreover, while considering external economic shocks, the empirical estimate posits that stablecoins are more stable risk diversifiers compared to the asset class they represent. Furthermore, in terms of the bivariate portfolio analysis formed with bitcoin, this study concludes that the weight of bitcoin is more stable when combined with gold, tether gold, Euro, Great Britain Pound, Swiss franc, and Japanese Yen. Thus, these assets are attractive for long-term investment strategies. This study provides investors and policymakers with significant insight into understanding safe-haven assets for bitcoinâs volatility and constructing a flexible portfolio that is dependent on the investment timeline and the prevailing market conditions.
Leila Hedhili Zaier, Syrine Ben Romdhane, Yasmine Jamezi
This article investigates the dynamic connectedness between non-fungible tokens (NFTs), cryptocurrencies and conventional currencies using an innovative approach to R 2 decomposition. We test volatility spillovers and the transmission of shocks across assets by decomposing the connectedness into its contemporaneous and lagged components. The database ranges from March 2020 to December 2023, considering several global situations: the COVID-19 pandemic, the 2021 cryptocurrency bubble, the war in Ukraine and the crash of cryptocurrencies in 2022. Our results suggest that the cryptocurrency and NFTs markets are the primary net volatility emitters, having a significant and immediate impact on the traditional currency market. In contrast, most traditional currencies act as net receivers, primarily adopting a shock-absorbing behaviour rather than shock transmission. The results show that the majority of volatility spillovers are contemporaneous, accompanied by small lagged effects. This research provides important insights into the increasingly essential role of digital assets in the global financial system, particularly regarding their influence on volatility transmission between markets.
This study investigates the dynamic interplay between national currencies of the core BRICS economies and the three strongest monetary assets (US dollar, gold, Bitcoin) in the existing global financial outlook. Using data spanning the inflationary Russia-Ukraine conflict (24 February 2022 to 5 June 2025) and the innovative Quantile-VAR methodology in bear, normal and bull market conditions as expressed by quantiles insights are offered about the potential of transformation of the monetary status quo. Findings reveal that extreme market conditions strengthen the leading potential of Bitcoin and gold in early and later war phases, respectively. This abides by the pseudo-wealth and consumption fluctuations theory of Guzman and Stiglitz (2021) as higher risk-taking appears in turbulent periods for preserving and promoting growth. Shielding from inflation could also work this way. The Brazilian, Chinese and South African currencies gain prominence while the Russian currency acts as a net absorber of shocks. So the US dollar could be partly crowded out. Alterations in monetary asset allocation for investors could serve for better adapting to contemporary financial needs.
Abstract The approval of Bitcoin ETFs by the Securities and Exchange Commission (SEC) on 01/11/2024 was an essential event for both the cryptocurrency market and the traditional financial system. Bitcoin ETFs work as a bridge between digital assets and traditional financial instruments, contributing to increased liquidity and attracting new institutional investors who were reluctant before due to regulatory and security concerns. This study assesses the impact of the approval of Bitcoin ETFs on the stability of the financial system, focusing on the correlations and the volatility spillover effects of Bitcoin and three major financial indices (S&P 500, Dow Jones Industrial Average, and Nasdaq-100). Using Pearson Correlation, Time-Varying Parameter Vector Autoregression (TVP-VAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, this research offers a comprehensive analysis of the influence of Bitcoin on the dynamics of market. The results show that, although the correlations between Bitcoin and stock market indices reached a peak in 2021, they dropped later, suggesting a gradual decoupling from traditional financial markets. However, after the launch of Bitcoin ETFs in 2024, the correlations with financial indices â especially with S&P 500 â started to rise again, suggesting a reintegration of Bitcoin into the traditional financial system. Contrary to initial expectations, the results obtained from data covering 90 days before and after the launch of Bitcoin ETFs donât show a significant increase in short-term correlations, which suggest a smooth adaptation of the market to these new financial instruments. In addition, although Bitcoin ETFs contribute to the stabilization of cryptocurrency volatility, they introduced new types of intra-day fluctuations, highlighting the need for an advanced strategy of risk management. The study concludes that, while Bitcoin ETFs contribute to the stability of financial markets, they introduce systemic risks which require continuous surveillance from the regulatory authorities. Long-term implications of the approval of Bitcoin ETFs remain uncertain, hence more research is needed in order to comprehensively assess the impact of these new financial instruments on the global financial stability.
Hanen Ben Ameur, Fouad Jamaani, Mohammed N. Abu-Alfoul
This study investigates the co-movements between prominent financial assets-crude oil, natural gas, gold, and Bitcoin-and uncertainty indices, including the Infectious Disease Equity Market Volatility Tracker (IDEMV) and the Geopolitical Risk Index (GPR), from January 2017 to January 2023. By employing advanced wavelet techniques-Wavelet Power Spectrum (WPS), Bi-Wavelet Coherence (WCA), Multiple Wavelet Coherence (MWC), and Partial Wavelet Coherence (PWC)-we analyze their time- and frequency-dependent responses to market shocks. The results reveal that Bitcoin and WTI exhibit time-varying sensitivity to IDEMV, particularly at short- and medium-term frequencies, highlighting their vulnerability to health-related crises like COVID-19. In contrast, gold and natural gas respond more strongly to GPR, with gold demonstrating a long-term leading role during geopolitical uncertainties, while Bitcoin and WTI lead in health-related shocks. The Russia-Ukraine conflict further amplified GPR's impact on Bitcoin and increased natural gas's vulnerability to geopolitical disruptions. These findings underscore the need for tailored strategies to address health and geopolitical risks. Policymakers should enhance crisis-response frameworks for Bitcoin and crude oil, while investors can reduce uncertainty by diversifying portfolios with resilient assets like gold and natural gas.
Cristina Dima, RÄzvan CÄtÄlin Dobrea, MÄdÄlina Ioana Moncea, Eduard Laurentiu Ion
Abstract For a long time, among the most controversial topics revolves around technology, which encompasses the financial landscape and changes the way we perceive and interact with money. The cause of this transformation is cryptocurrency - a revolutionary innovation that has captured the imagination of individuals and institutions around the world. For the less informed, investing in cryptocurrencies may seem like a game of chance, while for the younger ones, it represents a promising source of income for the future. The reasons for choosing the theme about cryptocurrencies can be motivated by several current factors such as: the topicality and relevance of cryptocurrencies, technological innovation, financial opportunities, regulations and public policies, social and cultural impact, but the main reason is the monetary future, which can become a significant part of the global monetary system.
The popularity of cryptocurrencies as alternative investments has grown in recent years. However, it remains unclear whether cryptocurrency investors behave irrationally in a similar way to emerging market investors. Using a systematic literature review, this study aims to compare the factors related to the presence of behavioural biases in the cryptocurrency and emerging stock markets. This study highlights similarities and differences between cryptocurrency and emerging stock market investor behaviour. Thus, the study's novelty arises from comparing the role of behavioural inclinations in cryptocurrency and emerging stock markets. The findings indicate that the small amount or lack of available information about small-cap emerging stocks or cryptocurrencies may reinforce investor sentiment and herding behaviour. The herding behaviour among investors in both markets may stem from following the most popular investment trends. Investors in cryptocurrency and emerging stock markets also tend to overreact to market sentiment and changes in market conditions. Extreme market conditions may affect the strength of herding behaviour, disposition effect, price clustering, anomalous behaviour, investor sentiment and uncertainty. Thus, cryptocurrency and emerging stock markets are informationally inefficient most of the time, whilst investorsâ irrationality may be more pronounced during certain periods. Furthermore, investorsâ behaviour in the cryptocurrency and emerging stock markets is more consistent with the adaptive market hypothesis than the efficient market hypothesis. This research suggests that cryptocurrency and emerging stock market investors should actively manage investment portfolios. Policymakers should be more concerned about information accessibility and quality, especially in the case of small-cap investment assets. JEL codes: G14;G15;G41
This study investigates the global adoption of Bitcoin by analyzing its price elasticity of demand (PED) across 46 countries or regions, with a focus on the interplay between economic, regulatory, and technological factors. Utilizing robust econometric techniques, including Huber regression, the research identifies significant variations in Bitcoin demand elasticity between developed and developing economies. The findings reveal that developed economies exhibit a mix of elastic and inelastic demand, driven by market maturity and discretionary consumption, while developing economies predominantly demonstrate inelastic demand, reflecting necessity-driven adoption amidst economic constraints. Key determinants of adoption include regulatory frameworks, such as legality, taxation, and anti-money laundering measures, alongside technological readiness indicators like blockchain infrastructure and internet penetration. These results underscore the critical influence of non-price factors on Bitcoinâs adoption dynamics and provide valuable insights for policymakers, investors, and industry stakeholders aiming to balance innovation with market stability. By offering a nuanced understanding of Bitcoin demand, this research contributes to the broader discourse on cryptocurrency adoption and its socioeconomic implications.
Research background: In todayâs digital age, traditional environmental, social, and governance (ESG) development paths are gradually facing challenges, including from digital technologies. In particular, the potential roles of artificial intelligence (AI), cloud computing (CC), and blockchain (BC) in the ESG market have not been fully explored. Purpose of the article: This study explores the deep integration of digital technology and ESG by evaluating the correlation and spillover effects among AI, CC, BC, and eight global ESG indices. Methods: This study explores the spillovers between AI, CC, BC, and eight global ESG indices by cross-quantilogram and quantile time-frequency connectedness approaches. Findings & value addition: The lower quantile of ESG returns has a weak positive (strong negative) correlation with the lower (upper) quantile of digital technology. Next, the spillover effects vary with time, frequency, and quantile levels. Meanwhile, the North America and Asia-Pacific developed ESG indices serve as the transmitter and receiver of spillover effects, respectively. Furthermore, the dependence between digital technology and ESG returns is insignificant before the COVID-19 crisis but increases after it. This quantile-dependent asymmetry fundamentally challenges linear assumptions prevalent in current ESG-technology integration theories. Overall, this study contributes by integrating AI, CC, BC, and ESG into a unified framework, and analyzing their interaction mechanisms. Furthermore, it dynamically analyzes the asymmetry over long and short-term horizons, and highlights the hedging role of digital technology in stabilizing ESG markets. Moreover, we provide novel insights about the interconnectedness between these markets, offering valuable guidance on risk management. Consequently, regulators should urgently explore the development of digital asset-based ESG derivatives as targeted risk mitigation tools. Positioned at the cutting-edge, this work sets a methodological benchmark for analyzing non-linear, frequency-sensitive interdependencies within the rapidly evolving ESG-digital nexus, transforming the theoretical framework from static linearities to dynamic non-linearities. Finally, this study proposes some reasonable suggestions, including raising risk awareness, promoting digital transformation, building integration and innovation platforms, and leveraging ESGâs diffusion role.
Cryptocurrencies are one of the new financial assets that might provide some hedge, safe havens and diversification benefits towards traditional financial assets.However, the impact of COVID-19 towards their properties was also acknowledged in the literature and showed that COVID-19 significantly changed their properties against other financial assets.However, the comparison of the co-movement for the cryptocurrency and financial assets in the three different periods (pre-COVID-19, during COVID-19, and post-COVID-19) is relatively limited.Therefore, this study aimed to study the differences in the co-movement between Bitcoin and stock indices in ASEAN-5 markets in these three periods.The study period spanned from early January 2018 until the end of June 2024, and the conditional correlation was obtained through the MGARCH-DCC approach.These conditional correlation series were then divided into three periods, and statistically compared their statistical differences using an independent t-test.The results found that the comovement between Bitcoin and market indices was significantly different between pre-COVID-19 and during COVID-19 in all ASEAN-5 markets.Besides, when comparing pre-COVID-19 and post-COVID-19, the result showed that the co-movement between Bitcoin and market indices in Malaysia and Thailand was significantly reduced, while significantly enhanced between Bitcoin and market indices in Indonesia and the Philippines markets.Moreover, the results further revealed the significant differences between the co-movement of Bitcoin and market indices in Malaysia, Singapore and Thailand markets.Some useful implications were obtained from the study's findings, and it is expected to be beneficial to the literature and also to stakeholders.
In this study, the fractal structure, efficiency, and long memory features of Bitcoin are investigated according to different investment horizons. The study utilized daily returns from 01.01.2017 to 22.11.2023, applying the maximum overlap discrete wavelet transform, Rescaled Range (R/S) analysis, and volatility models. The analysis results revealed a deviation of Bitcoin returns from the average and a negative correlation, indicating a lack of permanent behaviour in the series. The analysis demonstrates the rejection of the efficient market hypothesis and reveals a chaotic structure in the Bitcoin market. Furthermore, we observed a hyperbolic rate of decrease in returns at long-term investment horizons due to information shocks. This indicates that past returns can predict future returns. This suggests that instead of the efficient market hypothesis, the fractal market hypothesis is valid due to the existence of recurring trends. Finally, we determined the most appropriate volatility models for Bitcoin. The analysis shows that information shocks in Bitcoin returns at medium- and long-term investment horizons decrease over time, and past returns can predict future returns. However, volatility and information shocks are transitory at short- and medium-term investment horizons but can vary. All analysis methods yield consistent and compatible results, suggesting their potential extension to other cryptocurrency markets beyond the Bitcoin market.