Vincent Adela, Samuel Duku Yeboah, David Korsah, Michael Provide Fumey ¡ 6 authors
Geopolitical crises pose major risks to financial stability, but their implications for digital assets remain poorly understood. While prior studies suggest that cryptocurrencies may act as hedges or highly volatile speculative instruments during periods of uncertainty, the evidence remains inconclusive. This study examines how major cryptocurrencies reacted to geopolitical risk during the RussiaâUkraine war by employing the quantile-on-quantile regression (QQR) method on daily data from February 1 to August 8, 2022. The results reveal heterogeneous and nonlinear effects: Bitcoin (BTC) and Ethereum (ETH) exhibit partial hedging properties under moderate geopolitical risk, whereas alternative cryptocurrencies such as Binance Coin (BNB), Cardano (ADA), and Dogecoin (DOGE) display heightened vulnerability. Stablecoins exhibit contrasting roles, with USD Coin (USDC) acting as a safe haven, whereas Tether (USDT) consistently loses value under periods of uncertainty. These findings underscore that the safe-haven potential of cryptocurrencies is conditional on both market states and the type of asset, highlighting their asymmetry in times of crisis. By clarifying the dynamic role of cryptocurrencies during geopolitical shocks, the study contributes to the debate on whether digital assets enhance diversification or amplify instability, offering practical insights for investors and policymakers seeking resilient risk management strategies.
Oana Panazan, Catalin GHEORGHE, Aamir Aijaz Syed, Ahmed Jeribi
This study examines the dynamic interactions between precious metals, cryptocurrencies, stablecoins, safe-haven currencies, and two key macroeconomic indicators, the 5-year breakeven inflation expectation (T5YIE) and the 10-year minus 3-month Treasury yield spread (T10Y3M), over January 2016âJuly 2025. To capture nonlinear and multi-scale dependencies, the study applies Quantile-on-Quantile Regression (QQR) in combination with wavelet coherence (WCO) and wavelet transform coherence (WTC). The results indicate that major cryptocurrencies such as Bitcoin and Ethereum do not display robust or systematic links with inflation expectations or recession risk, limiting their role as macro-financial hedges. By contrast, the Japanese yen and Swiss franc show pronounced tail sensitivities, reaffirming their safe-haven status, while gold and its tokenized counterparts (DGX, PAXG) exhibit persistent long-run coherence with inflation expectations. Stablecoins demonstrate unstable short-term linkages shaped by liquidity shocks and market frictions. The research provides new evidence on the heterogeneous roles of digital and traditional assets in shaping macroeconomic expectations. The findings carry implications for investors, who should continue to rely on gold and safe-haven currencies for crisis hedging, and for regulators concerned with the systemic stability of emerging digital instruments.
The association between cryptocurrency and sustainability is a complex and growing topic. Given that such linkage requires a continuous investigation, this empirical research, unlike the existing literature, explores if the volatility dynamics of digital assets are driven by the changes in sustainability uncertainty. In doing so, we use a recently developed ESG-based sustainability uncertainty index (ESGUI) and examine its effect on the volatility dynamics of Bitcoin and Ethereum ETFs. Employing the mixed data sampling (MIDAS) approach shows that ESGUI exerts a negative effect on the realized volatility of cryptocurrency markets. One possible explanation for this linkage is that as sustainability-related uncertainty rises, investors tend to adopt sustainability practices and initiatives. This shift towards sustainable practices can result in more consistent and foreseeable long-term economic conditions, thereby reducing the volatility of financial markets including the digital asset class. Our analysis offers key implications to cryptocurrency investors.
Rosa GalvĂŁo, Domingos Santos Martinho, Nuno Nogueira, Rui Dias
The main objective of this study is to compare the efficiency levels, in their weak form, between sustainable cryptocurrencies such as Avalanche (AVAX), Cardano (ADA), Solana (SOL), Toncoin (TON) and Ethereum (ETH) (after 'The Merge'), which use efficient mechanisms such as proof-of-stake (PoS), and Binance Coin (BNB), Litecoin (LTC), Monero (XMR), Ripple (XRP), and Bitcoin (BTC) classified as unsustainable cryptocurrencies due to their excessive energy consumption based on proof-of-work (PoW). The analysed period was from 1 January 2023 to 10 December 2024. The Detrended Fluctuation Analysis (DFA) slopes reveal a significant impact of the 2023 Conflict on cryptocurrency dynamics, with distinct effects per asset. Sustainable cryptocurrencies (AVAX, ADA, SOL) demonstrated greater resilience, maintaining persistence with a brief reduction in long memory, reflecting their relative stability and attractiveness in uncertainty scenarios. In contrast, non-sustainable cryptocurrencies (LTC, XMR) transitioned from persistence to anti-persistence, indicating greater instability and speculation, associated with lower investor confidence. Assets such as TON (white noise) and XRP (consistent persistence) were less affected, suggesting intrinsic characteristics that confer resilience. Distinguishing between sustainability and other market factors is crucial to understand behaviours and build resilient portfolios, providing valuable insights for investors and researchers.
This paper documents a structural break in the risk return characteristics and cultural relevance of cryptocurrencies following the approval of the first spot Bitcoin ETF on January 10, 2024. Using daily price data from January 2021 to June 2026, we compare pre ETF and post ETF performance metrics, betas, and event study cumulative abnormal returns for Bitcoin, Dogecoin, and Ethereum relative to the S&P 500 and gold. We then introduce two independent measures of public interest, Google Trends and Wikipedia page views, to test the hypothesis that Bitcoin lost its cultural "coolness" after institutionalization. The findings are striking. Dogecoin, the quintessential speculative asset, saw its Sharpe ratio collapse from 0.30 pre ETF to 0.01 post ETF, while its annualized return fell from 63.17% to 2.82%. Google search interest for Dogecoin declined 63.1% and its Wikipedia page views collapsed 75.9%. Searches for "how to buy Bitcoin," a proxy for new retail entrants, declined 22.7%. In contrast, general "cryptocurrency" interest fell 47.5%, while Bitcoin maintained a stable Sharpe ratio and saw its beta relative to the S&P 500 decline from 1.33 to 1.11. An event study reveals that the Trump 2024 election produced a +47.37% cumulative abnormal return for Dogecoin, but this proved temporary. The MSTR sale in May 2026, Michael Saylor's first Bitcoin sale since 2022, generated a-6.56% abnormal return for Bitcoin. These results support the thesis that ETF approval marked a cultural as well as financial regime shift, as retail speculative energy exited the crypto market and Bitcoin moved toward more of a diversifier role.
Which crypto asset absorbs capital flight when armed conflict breaks out? Using on-chain Tether (USDT) transfer volumes from conflict-zone exchanges, we document that stablecoin demand surges 69.86% at conflict onset on the local exchange level, with 48-hour cumulative surges as high as 700%, while Bitcoin fell 6â8% at onset in four of five events. We analyse five escalation events across three active wars (RussiaâUkraine, February 2022; Hamasâ Israel, October 2023; IranâIsrael, April and October 2024; USâIran, February 2026). USDT transfer volumes on the Iranian exchange Nobitex spike at E1, E2, and E5 within 48 hours of conflict onset, while Bitcoin returns are negative on day 0 in four of five events. Voluntary crypto donations to Ukraine confirm the pattern: USDT ($83M) dominates Bitcoin ($41M) by a 2:1 ratio. Three robustness checks address exchange-internal settlement, secular growth and infrastructure heterogeneity. The core finding is on-chain rather than price-based: people under fire want dollars (USDT), not Bitcoin. Sanctions tooling and regulatory attention should re-focus on Tron-based stablecoins.
Open access
Blockchain Technology Applications and Security
Environmental and Biological Research in Conflict Zones
This study investigates the existence of long-run relationships between cryptocurrency prices (Bitcoin, Ethereum) and macro-economic and macro-financial variables, addressing a gap in prior research primarily focused on short-run responses. Using time series data on these variables over the period January 2022 to December 2024, statistical co-movement tests are applied to find significant relationships. Tests conducted with monthly data reveal significant co-movement in Bitcoin and Ethereum prices and the Consumer Sentiment Index, global gold reserves (measured in ounces), the MSCI World Index, and the Producer Price Index. Additionally, weekly tests reveal co-movement between Ethereum and gold prices in calendar year 2023. These findings provide empirical evidence that Bitcoin and Ethereum increasingly reflect certain macro-financial and macro-economic conditions rather than trading independently of traditional economic forces, while evidence supporting a stable âdigital goldâ role remains sparse and episodic.
We investigate whether China's 2021 mining ban transformed Bitcoin from a speculative vehicle into a macro-sensitive asset. Using daily data from 2017-2025, we document a decisive structural break. Pre-2021, volatility was endogenous, driven by raw trading volume rather than fundamentals. Post-ban, however, internal microstructure noise loses predictive power. Instead, volatility is now driven by macroeconomic anxiety: Wikipedia searches for "Inflation" improve forecast accuracy by over 7%. We further uncover a "dual narrative" where inflation attention predicts crash risk, while "Recession" queries (pivot speculation) drive rallies. These findings suggest the regulatory shock successfully curtailed noise trading, allowing macro-fundamentals to dominate price discovery.
Persistent double-digit inflation, sharp currency depreciation, and eroding confidence in domestic monetary institutions have led many households in emerging markets to search for assets outside the control of national authorities. Bitcoin, the largest cryptocurrency by market capitalization, is frequently described as "digital gold" and a potential inflation hedge, yet empirical evidence remains mixed, particularly for chronically highinflation economies. This paper examines whether Bitcoin functions as an inflation hedge in Argentina and Turkey, two emerging markets characterized by persistent inflation, currency depreciation, and divergent cryptocurrency regulatory regimes, over the period January 2018 to August 2025. Using monthly data on local-currency Bitcoin returns, changes in inflation, and exchange-rate depreciation obtained from TradingEconomics.com, the study estimates baseline and extended Ordinary Least Squares (OLS) regressions for each country. The baseline results show a statistically insignificant, negative relationship between inflation and Bitcoin returns in Turkey, and a small but statistically significant positive relationship in Argentina. Once exchange-rate depreciation and global Bitcoin returns are introduced as controls, the explanatory power of both models rises sharply (R² â 0.99 in each country), while the coefficient on inflation becomes negligible and statistically insignificant in both cases. These findings suggest that Bitcoin behaves primarily as a currency-depreciation hedge and a vehicle tracking global cryptocurrency market sentiment, rather than as a direct hedge against domestic inflation. The results carry implications for investors, policymakers, and households evaluating Bitcoin's role in high-inflation, capital-constrained economies.
This paper examines the return connectedness between Bitcoin and stock indices of economies with high levels of cryptocurrency adoption. Such economies are predominantly emerging markets characterized by elevated inflation, poor institutional quality, and macroeconomic and political instability, creating conditions under which investors may reallocate from traditional assets to Bitcoin during episodes of increased uncertainty. To assess this linkage, we employ a TVP-VAR framework with frequency-domain decomposition. Our results indicate only modest return connectedness under normal market conditions, which intensifies during periods of market turmoil. This observed pattern, along with low correlation and the identification of Bitcoin as a net return receiver, led to testing the portfolio diversification potential of Bitcoin. The evidence indicates that Bitcoin contributes to both risk mitigation and return enhancement at low hedging costs. The effect is more pronounced for emerging-market portfolios than for developed markets.
Richard Cantillon (1680s-1734), an Irish-French economist and early pioneer of political economy, observed that those closest to new money creation gain purchasing power before prices adjust throughout the economy. Bitcoin miners occupy precisely this position as the exclusive first receivers of every newly minted bitcoin. Yet unlike banks in fiat systems, miners cannot retain this advantage indefinitely because the protocol subjects them to relentless competition. This paper proposes the Lazy Miner Hypothesis: when mining profitability deteriorates following halving-induced supply shocks, inefficient operators exit first, generating a predictable sequence of revenue compression, hash rate decline, and subsequent price recovery that redistributes first-receiver gains from weak miners to patient investors. Using daily data from September 2014 to January 2026, a miner stress indicator combining depressed revenue with declining computational commitment predicts 90-day forward returns of 36.5 percentage points after controlling for Federal Reserve policy and energy costs. The coefficient is virtually unchanged when WTI crude oil volatility is added, confirming a protocol-native effect. Horse race regressions show miner stress dominates technical oversold indicators. Placebo tests with randomized halving schedules produce no comparable effects, and forward Sharpe ratios confirm genuine alpha. The premium declines by 12.5 percentage points per halving epoch, consistent with market learning. The approval of U.S. spot Bitcoin ETFs in January 2024 significantly diminishes the effect, yet the miner stress signal remains positive and statistically significant, indicating that institutional absorption is underway but incomplete. Bitcoin's competitive mining structure thus transforms Cantillon dynamics from permanent insider advantages into temporary, efficiency-driven rewards that erode as markets mature.
GPU compute has become a multi-hundred-billion-dollar exposure underpinning AI, yet whether its price risk can be hedged with existing assetsâand thus whether the dedicated compute-futures markets announced in 2026 are warrantedâhas, to our knowledge, not been tested. Using daily GPU rental-rate benchmark indices (via Bloomberg) for three generations (A100, H100, B200)âthe first such cross-generation panel we are aware ofâwe ask whether compute is "the new oil": a hedgeable industrial commodity. We document its price dynamicsânewer generations are far more jump-prone than oil or equities (though lower in overall volatility), with no volatility clusteringâand a cross-generation price structure whose discounts shift over time. We then test cross-asset proxy hedging out-of-sample. GPU rental returns are weakly correlated (daily |Ď| Ⲡ0.1) with NVIDIA, semiconductors, compute-infrastructure equities, and the broad market, and no minimum-variance proxy hedge delivers out-of-sample variance reduction distinguishable from zeroâacross the three generations, across horizons from daily to weekly (monthly and quarterly results are indicative only, given few non-overlapping blocks), and after multiple-testing, active-day (stale-filtered), and frontier-roll checks; a naĂŻve one-for-one hedge sharply adds risk. This is a negative result on a short, stale sample: a power analysis shows the effective sample cannot resolve a true variance reduction below roughly 9%, so we report the absence of a detectable conventional hedge rather than proof of exact orthogonality. Even so, no detected hedge removes more than a small fraction of a jump-prone exposure, so the practical case for a direct instrument is little changed by that ceiling. We read the result constructivelyâa suggestive incomplete-market rationale for a dedicated marketâwhile noting that the same weak correlation implies a liquidity paradox for those contracts, and we quantify the heightened exposures (not materially reducible by the proxies we test) in AI-training budgets and GPU-collateralized lending.
This study examines the weak-form efficiency and international price integration of Malaysiaâs regulated Bitcoin market. Daily closing prices for Bitcoin traded in Malaysian ringgit (BTC/MYR), the international Bitcoin price in US dollars (BTC/USD), and the USD/MYR exchange rate are analysed over the 2021â2026 period using secondary market data. The international Bitcoin price is converted into ringgit to provide a currency-consistent benchmark for the local market. Random-walk behaviour is evaluated using the runs test, LjungâBox test and variance-ratio test. Market integration is examined through unit-root tests, EngleâGranger cointegration analysis and an error-correction model. The daily results provide mixed evidence regarding weak-form efficiency. Although the runs test does not reject randomness in return signs, the LjungâBox and variance-ratio results indicate dependence at selected horizons. This dependence becomes weaker in the weekly analysis, suggesting that the efficiency assessment is sensitive to data frequency. The local and international Bitcoin prices are cointegrated, with a long-run coefficient close to unity. The error-correction results further show that deviations from the long-run relationship are corrected over time and that international Bitcoin returns significantly influence short-run local price movements. Nevertheless, a small local price premium and residual volatility clustering remain. Overall, Malaysiaâs Bitcoin market is closely integrated with the international market but is not perfectly efficient at all horizons. The findings support policies promoting transparent benchmark pricing, market surveillance, adequate liquidity and volatility-risk controls among Malaysian digital asset exchanges.
This study investigates the relationship between two of the most important assets in the modern market, Bitcoin and gold. While gold has historically been considered a safe-haven asset, Bitcoin has emerged as a new digital alternative to gold. Using daily data from 2014 to 2025, the study applies a purely quantitative comprehensive mathematical framework that includes risk and return analysis, correlation analysis, regression models, granger causality tests, cointegration analysis, vector autoregression and impulse response functions. The results indicate that Bitcoin is a poor alternative to gold for central banks and hedgers, and a successful substitute for gold for speculators and investors, providing higher returns at a higher risk. Furthermore, even though correlation is low, investors may achieve substantial return by focusing on short term market shocks. One of the important results also include that a significant change in Bitcoin price may influence the price of Gold, but changes in the latter do not impact the former. In conclusion, the study recommends the use of Bitcoin and Gold as complements, not as substitutes.
This paper tests whether Bitcoinâs four-year cycle persists in monthlyreturn dynamics after the assetâs recent institutionalization. Weestimate harmonic Fourier regressions with 48- and 24-month componentsand allow the cycle coefficients to shift after a May 2023 structuralbreakpoint. We compare an unconditional model with a macro-conditionedspecification that includes S\&P 500 and U.S. Dollar Index returns.The unconditional results indicate a significant post-break changeand a sharp reduction in cyclical amplitude. However, after controllingfor broader market and liquidity conditions, the residual four-yearcomponent loses statistical significance. The evidence suggests thatBitcoinâs historical halving-related rhythm has weakened and thatits return dynamics are increasingly linked to global macro-financialconditions.
This study examines whether the impact of Tariff Policy Uncertainty (TPU) on gold returns varies depending on Bitcoin market conditions, with the aim of determining whether goldâs safe-haven role is regime-dependent. Using a vector autoregression (VAR) model, Granger causality tests, and impulse response functions (IRFs), the empirical results show that, over the full sample period, TPU has a significantly positive effect on gold returns after a certain lag, confirming that gold partially functions as a safe-haven asset. However, during periods of high Bitcoin investor attention, both the impact of TPU on gold and the causal relationship become statistically insignificant, indicating a weakening of goldâs safe-haven role. In contrast, during low-attention Bitcoin regimes, TPU exerts a strong positive effect on gold returns, accompanied by significant causality and a persistent positive response. These findings suggest that the effects of policy uncertainty shocks on financial markets depend on the substitutive relationship between Bitcoin and gold, implying that goldâs role is partially replaced when Bitcoin attracts high investor attention, while its traditional safe-haven function is reinforced during periods of low attention.
This thesis examines whether cryptocurrencies can function as diversification or risk-reducing assets relative to the Swedish equity market during periods of financial stress. Using daily data for Bitcoin, Ethereum and Ripple from 2018 to 2024, their dynamic relationship with the OMX30 index is analyzed. To provide a broader benchmark, gold, the German DAX index, and the U.S. S&P 500 index are included as comparison assets. Periods of financial stress are identified as episodes in which the OMX30 declines by at least 10 percent from a recent peak. Time-varying correlations are estimated using a Dynamic Conditional Correlation GARCH (DCC-GARCH) model, allowing the analysis of how interasset relationships evolve over time. In addition, hedge effectiveness measures are employed to assess the cryptocurrencies practical ability to reduce portfolio risk.The results show that Bitcoin, Ethereum and Ripple exhibit weak but positive correlations with the Swedish equity market, implying that they may serve as diversifiers but not ashedges or safe-havens. During periods of financial stress, correlations tend to increase rather than decrease, indicating limited protective properties. Hedge effectiveness estimates further suggest that the risk-reducing capacity of cryptocurrencies is unstable and generally weak. Incontrast, gold displays more consistent negative correlations and superior hedging performance. Overall, the findings suggest that cryptocurrencies offer limited diversification benefits for Swedish investors and should not be considered reliable risk-mitigating assets during market stress.
This study investigates time-frequency volatility transmission of both cross-exchange instrument networks and cross-instrument exchange networks of crypto-markets under a unified time-varying parameter vector autoregression (TVP-VAR) framework. 5-minute closing prices of 16 variables throughout the 2021-2025 period are sampled to form the two types of networks by instrument and by exchange, comprising spot and perpetual instruments of Bitcoin (BTC) and Ethereum (ETH) on Binance, OKX, Bitget, and Bitfinex. The hourly logarithmic realized volatility is aggregated to estimate both the time- and frequency-domain connectedness partitioned into short- (1-8 hours), mid- (8-24 hours), and long-term (beyond 24 hours) components. The results indicate that the total connectedness of instrument networks uniformly exceeds that of exchange networks. The long-term component prevails, while the short-term component remains non-negligible with episodic amplification. Bitfinex functions as the sole net receiver across instrument networks, whereas Binance, OKX, and Bitget act as net transmitters. Within exchange networks, ETH instruments more frequently transmit volatility to BTC ones beyond eight hours, while this direction reverses within the 8-hour horizon. Spot instruments dominate perpetuals on OKX, Bitget, and Bitfinex with Binance as the main exception. Eight historical events elicit heterogeneous response modes contingent on the nature of the shocks, with the LUNA collapse and FTX crisis as the most influential in-sample events. The findings carry implications for cross-venue risk monitoring and horizon-aware portfolio management.
This paper studies volatility prediction for Ethereum in the post-Merge era. Using daily ETH/USD returns from 15 September 2022 to 23 April 2026, we compare standard GARCH(1,1), Heston-Nandi GARCH(1,1), cross-validated and aggregated EWMA predictors, and Nadaraya-Watson kernelregression predictors. The kernel forecasts are constructed from a rank-transformed state vector that captures recent volatility and signed-return conditions, allowing the conditional variance function to be nonlinear and state dependent. The results show that forecast performance is strongly horizon dependent. At the one-day horizon, the kernel predictor using the fitted GARCH volatility state delivers the lowest final cumulative squared prediction error, outperforming the standard GARCH benchmark and all EWMA-type competitors. At the ten-day-ahead horizon, the advantage of local nonparametric information weakens, and the mean-reverting structure of GARCH becomes more valuable. The estimated kernel surface reveals that predicted ETH volatility is highest when elevated recent volatility coincides with negative signed-return pressure. Conditional quantile results further show that kernel-based VaR improves lower-tail risk forecasts, especially at the 1% quantile. Overall, the evidence suggests that post-Merge Ethereum volatility is persistent, asymmetric, heavytailed, and nonlinear, and is best modelled by combining economically meaningful volatility states with flexible nonparametric forecasting maps.
We use novel intraday data to study the price discovery process in cryptocurrency markets around U.S. monetary policy, inflation, and labor market announcements. Our analysis reveals the following: (1) volatility, trading volume, and bid-ask spreads rise sharply at announcement times and remain elevated for up to 30 minutes relative to comparable non-announcement intervals, indicating that cryptocurrency investors pay attention to these announcements and that information is quickly incorporated; (2) announcement surprises associated with higher yields or "risk-off" conditions cause substantial cryptocurrency price declines - pointing to a potential strengthening of U.S. monetary policy transmission to the real economy in recent years; (3) the time-varying magnitude and direction of price reactions more closely resemble those of U.S. equities than those of fiat currencies or commodities, suggesting that cryptocurrencies behave primarily as risk-sensitive assets; (4) price impact estimates of order flow around announcements are consistent with rising institutional participation in cryptocurrency markets and their crucial role for price discovery.
We examine whether the institutionalization of digital assets through regulated exchange-traded funds changes the transmission of macro-financial risk. Using daily data from January 2019 to March 2026, we study the launch of the spot Ethereum exchange-traded fund on 23 July 2024 as a dated institutional event and test whether Ethereumâs response to United States inflation surprises changed after the introduction of regulated ETF access. A triple-difference design shows that the interaction between headline Consumer Price Index surprises and lagged Ethereum network activity reverses sign around the ETF launch. Before the ETF, the interaction is small and positive (+0.06, p = 0.04), indicating that a more active network amplified Ethereumâs directional response to inflation news. After the ETF, the interaction becomes large and negative (-0.25, p
Flexible demand is increasingly important in energy systems with high renewable penetration. Bitcoin mining is often cited as a large, theoretically flexible load. Despite electricity consumption rivaling medium-sized industrial economies, the energy market behavior and impacts of Bitcoin miners remain largely unexplored. We exploit the large-scale relocation of Bitcoin mining to Texas, which became the world's largest mining hub following China's 2021 ban, to estimate its effects on local wholesale electricity prices. Combining a novel, hand-collected dataset on mining facility locations with high-frequency wholesale price data, we identify price impacts using a DiD design. We find that miners select into renewable-rich, high-GDP per capita counties with initially lower electricity prices on average. Mining entry has no significant effect on daytime prices but increases nighttime prices by 19.9%, indicating that Bitcoin miners fail to exploit their operational flexibility. Instead they increase baseload demand and reinforce fossil generation during low-renewable periods.