Blockchain Papers

Fuyao Li, Yahua Yin

No abstract is available for this record.

Rihab Belguith, Wafa Kammoun Masmoudi

This study examines the dynamic interconnections and portfolio implications of clean energy ETFs, artificial intelligence (AI) indices, crude oil, and Bitcoin within sustainable and technology-driven financial markets. Using a Time-Varying Parameter Vector Autoregression (TVP-VAR) framework and daily data from January 2019 to December 2024, we analyze time-varying spillovers and construct optimal portfolios based on dynamic connectedness measures. The results show that clean energy and AI-related assets display relatively stable portfolio weights, whereas Bitcoin exhibits highly volatile and generally limited allocations, particularly under risk-averse strategies. Conventional approaches such as the Minimum Variance and Risk Parity portfolios tend to favor traditional assets, while the Maximum Connectedness Portfolio enhances diversification by allocating more weight to weakly connected assets, including Bitcoin and green ETFs. The findings offer practical insights for resilience-oriented and innovation-driven portfolio construction.

Yong Tang, Mrs Faryal, Ifran Khan

This study uses the Diebold-Yilmaz (2012) and Baruník-Křehlík (2018) frameworks to examine time-varying volatility spillovers among five key rare earth minerals, cryptocurrencies, and macroeconomic uncertainty indexes. Our results reveal considerable cross-market spillovers (31.75% of total variance), which are short-term (29.97%, 1–4 days) in nature and over 50% during the COVID-19 pandemic. Ethereum (70.99%) and bitcoin (66.58%) emerge as predominant short-term transmitters, whereas dysprosium (31.45%) has a more long-lasting, cross-horizon effect. Macroeconomic uncertainty indices act as net recipients. This increased short-run spillover requires forward-looking macroeconomic policy and integrated risk management directed at cryptocurrency and strategic rare earths for financial stability.

Hongjun Zeng, Abdullahi D. Ahmed

Abstract The purpose of this study was to assess the dependence structure and volatility connectedness among the COVID-19 crisis, the 2022 Russia–Ukraine war, and their influence on cryptocurrencies, crude oil, developed markets, and the equity markets of China and ASEAN countries under varying market conditions. The analysis segmented the sample into three distinct periods: pre-COVID-19, during COVID-19, and the 2022 Russia–Ukraine conflict. To assess the dependence structure and risk spillover patterns across the markets for each period, we employed the generalized autoregressive conditional heteroskedasticity (GARCH)-extreme value theory (EVT)-vine copula and quantile vector autoregression (QVAR) connectedness methodologies. Findings from our GARCH-EVT-Vine-Copula model indicated that subsequent to the outbreak of COVID-19, market portfolios associated with the MSCI-developed markets index demonstrated significantly lower tail connectedness. However, the impact of the 2022 Russia–Ukraine war on the stock markets of China and ASEAN countries was found to be overestimated. Furthermore, the QVAR connectedness analysis revealed that connectedness was greater in bullish market conditions than in normal and extreme downside periods. Additionally, the portfolio analysis results suggested that the equity markets of China and ASEAN countries, along with the crude oil markets, cryptocurrency indices, and the MSCI developed markets index, were unable to achieve high levels of hedging effectiveness. Concurrently, it was recommended that investments be directed toward Chinese and ASEAN equities as safe-haven assets.

Mingchen Li, Yajie Tian, Jiawei Wang, Haonan Yao · 6 authors

No abstract is available for this record.

Hugo Benedetti, Ehsan Nikbakht, Boris Pastén

This paper examines the directional connectedness between the returns of Bitcoin and Ethereum and the supply of stablecoins across different market conditions. Using a Quantile Vector Autoregression (QVAR) model, we analyze daily log-returns of major cryptocurrencies and changes in stablecoin supply from January 2021 to November 2024, capturing dynamics at the 5th, 50th, and 95th quantiles. Our findings show that the Total Connectedness Index (TCI) nearly triples under extreme conditions, with Bitcoin and Ethereum transitioning from passive roles in normal periods to dominant transmitters of influence during downturns. Stablecoins behave heterogeneously across regimes, with roles varying significantly even within the same subclass. Tether exhibits state-dependent behavior, acting as a net receiver of shocks in most conditions but emerging as a transmitter during bull markets. We also assessed the impact of the Terra-LUNA collapse, revealing a regime shift in the transmission of shocks: connectedness rises under normal and negative conditions but declines in positive markets. These patterns suggest that, under certain conditions, major cryptocurrencies can influence stablecoin issuance in distinct ways, leading to asymmetric adjustments in supply across individual stablecoins and shaping liquidity dynamics throughout the ecosystem. While we do not attempt to model the underlying mechanisms behind these shifts, our results point to the importance of monitoring state-dependent relationships and recognizing the diverse behaviors of stablecoins. The findings motivate the development of regime-sensitive monitoring tools and support ongoing policy discussions around stablecoin design, issuance frameworks, and market transparency.

Sirine Ben Yaâla, Jamel Eddine Henchiri

Purpose This study aims to investigate the dynamic and region-specific comovements between Bitcoin and environmental, social and governance (ESG) returns across emerging and developed markets, in response to recent economic and regulatory transformations in sustainable finance. Design/methodology/approach A dual econometric framework – combining the cross-wavelet transform and time-varying Granger causality (TVGC) tests within recursive expanding windows – is employed to capture both time–frequency comovements and evolving causal linkages between Bitcoin and ESG return. Findings The results reveal that Bitcoin's influence on ESG indices is both time-varying and region-dependent. Medium-term (6–12 months) comovements dominate in emerging markets such as Brazil and Mexico, driven by remittance flows and post-crisis recovery, whereas developed regions like the US and European Union display complex bidirectional linkages over longer horizons (1–2 years) shaped by financial maturity and policy transitions. The TVGC analysis further confirms significant causal interactions: Bitcoin exerts a stronger influence in emerging markets, while developed economies exhibit more balanced and policy-sensitive relationships. Practical implications The findings suggest that investors and policymakers should adapt Bitcoin–ESG strategies to regional contexts – promoting financial inclusion in emerging markets while reinforcing sustainability objectives in developed economies. Originality/value This study is among the first to integrate wavelet-based time–frequency analysis with rolling-window causality tests in exploring the crypto–ESG nexus. It provides novel evidence of the dynamic, region-dependent nature of these relationships and contributes to both academic literature and the design of sustainable investment and regulatory strategies.

Amin Shakourloo, Asil Azimli

No abstract is available for this record.

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 Russia–Ukraine 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 2016–July 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.

Anupam Dutta

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 Galvão, 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.

David Krause

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.

Muhammad Noraiz Abid

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 6–8% at onset in four of five events. We analyse five escalation events across three active wars (Russia–Ukraine, February 2022; Hamas– Israel, October 2023; Iran–Israel, April and October 2024; US–Iran, 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.

Andrusha Parilov Harden, Raanju Sundararajan

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 “digital gold” role remains sparse and episodic.

Bernadett Aradi, Gábor Petneházi

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.

Botirjon Rakhimov

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 ≈ 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.

Michala Moravcova, Peter Albrecht, Šimon Hvizd

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.

Niranjan Sapkota

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.

Doohwi Cha

GPU compute has become a multi-hundred-billion-dollar exposure underpinning AI, yet whether its price risk can be hedged with existing assets—and thus whether the dedicated compute-futures markets announced in 2026 are warranted—has, to our knowledge, not been tested. Using daily GPU rental-rate benchmark indices (via Bloomberg) for three generations (A100, H100, B200)—the first such cross-generation panel we are aware of—we ask whether compute is "the new oil": a hedgeable industrial commodity. We document its price dynamics—newer generations are far more jump-prone than oil or equities (though lower in overall volatility), with no volatility clustering—and 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 |ρ| ≲ 0.1) with NVIDIA, semiconductors, compute-infrastructure equities, and the broad market, and no minimum-variance proxy hedge delivers out-of-sample variance reduction distinguishable from zero—across 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 naïve 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 constructively—a suggestive incomplete-market rationale for a dedicated market—while 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.

Davide Sandretto

No abstract is available for this record.

N. Monika, Sunil Kumar, Mona Sharma

This study investigates the dynamic impact of Bitcoin prices and key macroeconomic variables, consumer price index (CPI), exchange rate, and crude oil prices, on industrial output in India, proxied by the index of industrial production (IIP). The Toda-Yamamoto causality analysis reveals that CPI and oil prices Granger-cause IIP, whereas Bitcoin and exchange rate do not exhibit causal influence. Utilising the auto-regressive distributed lag (ARDL) bounds testing framework for robustness, the study captures both short- and long-run relationships. Impulse response functions (IRFs) and the error correction model (ECM) confirm these findings, showing significant responsiveness of IIP to CPI and oil shocks. Stability tests (CUSUM and CUSUMSQ) validate model reliability, while robust standard errors address heteroscedasticity concerns. Diagnostic tests indicate no autocorrelation or autoregressive conditional heteroscedasticity (ARCH) effects, though non-normality and mild heteroscedasticity are observed. The findings highlight that conventional macroeconomic variables continue to dominate industrial performance, with Bitcoin exerting a negligible real-sector impact.

Grigorios Rapos

No abstract is available for this record.

Mohd. Rahimie Abd. Karim, Saizal Pinjaman, Izaan Jamil, Azmi Abd. Majid · 5 authors

This study examines the weak-form efficiency and international price integration of Malaysia’s 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 2021–2026 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, Ljung–Box test and variance-ratio test. Market integration is examined through unit-root tests, Engle–Granger 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 Ljung–Box 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, Malaysia’s 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.