Bitcoin research increasingly relies on on-chain indicators to study network activity, monetary issuance, transaction demand, miner incentives, coin-age behavior, and long-run monetary dynamics. However, many commonly used Bitcoin metrics are dispersed across commercial platforms, subject to heterogeneous definitions, or not fully reproducible from primary blockchain data. This manuscript introduces Open Bitcoin Metrics (OBM), a reproducible, full-node-derived dataset and reference guide for Bitcoin on-chain time series designed for economic and econometric research. The dataset provides documented daily series covering block production, block-space usage, transaction counts, supply, issuance, fees, miner revenue, mining difficulty, estimated hashrate, Bitcoin Days Destroyed, dormancy, liveliness, UTXO counts, spent output value, and related UTXO-age indicators. Metrics are reconstructed from a locally maintained Bitcoin Core full node, a persistent spent-output indexer, or deterministic transformations of previously generated OBM series. Each series is accompanied by open-source Python code, stable identifiers, explicit definitions, metadata, validation procedures, interpretive caveats, and comparisons with the closest publicly available metrics. The dataset is intended to support transparent empirical research, replication, teaching, and comparative analysis across monetary economics, financial economics, and blockchain studies.
Our study examines the impact of climate policy uncertainty on the volatility of Bitcoin, Ethereum and Litecoin. Using monthly Climate Policy Uncertainty Index data from 2010 to 2024, we forecast daily cryptocurrency volatility with a GARCH-MIDAS model. The results show that higher climate policy uncertainty significantly increases volatility across all three cryptocurrencies over the full sample period. Out-of-sample analysis, which captures structural changes in energy consumption, reveals stronger effects for Bitcoin. Ethereum shows insignificant responses following its transition to a proof-of-stake mechanism, while Litecoin exhibits a significant positive relationship with uncertainty. Overall, climate policy uncertainty proves to be a strong predictor of cryptocurrency volatility, particularly for energy-intensive assets. The findings highlight the importance of policy-related information in shaping investor behaviour in crypto markets and provide useful implications for cryptocurrency issuers, retail investors and portfolio managers seeking to manage risk under changing regulatory and environmental conditions.
Abstract Bitcoin was the breakthrough innovation demonstrating peer-to-peer transfer of value without a central bank and has since expanded to countless innovations such as smart contract applications, decentralized finance protocols and asset tokenization. The EU is moving from scattered state-specific rules governing cryptocurrency activities to a coherent European regulatory regime. This paper review the transition to a harmonized framework in 2024-2025 from a doctrinal-institutional perspective, unpack how to carry out the three main legislative instruments: MiCA, TFR on information accompanying transfers of funds and transfers of certain crypto-assets and amending the EU directive and the EU AML package . Moreover, I look at the implications of DAC8 for the tax treatment of crypto-assets and tokenized assets. In 2025, the market begins institutionalizing, as MiCA requires significant compliance measures in terms of governance, transparency and conduct for CASPs to get licensed. Moreover, in conjunction with the new TFR rules, compliance for CASPs, at least in the business models discussed, effectively transforms into an operational infrastructure issue revolving around data quality, process efficiency and interoperability. By way of comparison, I analyze eight example business models in eight representative EU markets that appear to be impacted. These include: two major exchanges, two broker-dealers offering cryptocurrency on trading platform, a provider of non-custodial software wallets, two DeFi protocol participants and two NFT platform providers. These fall into three general categories depending on their legal status, direct regulatory burden and level of engagement with decentralized technologies. Finally, harmonized regulatory frameworks like the one outlined for the EU increase operational fixed costs and favor consolidation, reduce the benefits for regulatory arbitrage and thereby boost user protection, although part of innovation may pivot towards B2B solutions.
Cryptocurrency regulation faces a fundamental mismatch between static rules and rapidly transforming markets. We demonstrate that Bitcoin alternates between bounded and unbounded price regimes, requiring adaptive rather than uniform regulatory frameworks. Using extreme value theory on over a decade of Bitcoin data, we show that tail risk characteristics switch between finite-limit and heavy-tailed regimes, with profound implications for investor protection, capital requirements, and systemic risk management. Traditional approaches either overregulate during stable periods or underprotect during volatile regimes. We propose regime-contingent regulatory frameworks that automatically adjust oversight intensity based on statistical detection of tail risk characteristics. Backtesting over 2016–2025 demonstrates that the adaptive framework reduces average capital requirements by 79% overall and by 84% during bounded regimes while escalating protections before major crashes, outperforming static Basel III-style rules. Robustness analyses across multiple window lengths (90, 180, 365, and 730 days), thresholds, and bootstrap specifications confirm that regime-switching is a persistent structural feature of Bitcoin markets. Implementation requires international coordination, transparent methodology, and clear adjustment protocols.
Since the first implementation of a blockchain with Bitcoin in 2009, cryptoassets created and transacted using blockchain technologies have grown and diversified significantly. Because regulatory regimes, which govern cryptoassets, do not have global coverage, criminal actors find opportunities to commit cryptoasset fraud. While it can be difficult to distinguish between cryptoassets that are honest but high risk and cryptoassets that are outright fraudulent, investors seeking significant returns frequently invest in unregulated cryptoassets, namely cryptocurrencies and non-fungible tokens (NFTs). This study provides a crime script analysis to examine the chronological and functional steps offenders use to execute cryptoasset fraud. It considers three types of crypto asset fraud and how they have functioned over time: Ponzi schemes, cryptoasset exit scams, such as cryptocurrency “rug pulls,” and NFT “mint-and-run” schemes, where invested value is stolen from a crypto asset project. By outlining the fundamental crime script of cryptoasset fraud, this study considers the implications for regulators. Of note, this study shows that while the stages of cryptoasset frauds are consistent, the speed at which frauds are executed has, on average, increased significantly. This rapidity of execution provides enduring challenges to regulators, who often cannot respond quickly. This challenge must be considered if regulation is to be effective.
Ben Hawkins, Joshua Levett, Siamak F. Shahandashti
We present a longitudinal measurement study on the adoption of detectable, second-generation anonymisation protocols in the Bitcoin network, including CoinJoin, CoinSwap, CoinShuffle and Stealth Addresses. By implementing and refining a suite of heuristic filters, we identify over 5.94 million CoinJoin and 23.3 million CoinSwap transactions. Besides, the use of CoinShuffle was unexpectedly found to be closely aligned with the Wasabi wallet operation period. Our analysis reveals consistently low adoption rates, with these protocols constituting less than 1% of network transactions, and a sharp decline in detectable usage following key regulatory events. Furthermore, we find no evidence of standardised Stealth Address adoption, indicating a failure to converge on a common privacy standard. This study provides a comprehensive picture of a niche ecosystem whose on-chain visibility has been largely suppressed, strongly suggesting the migration of privacy-seeking users to less transparent and less detectable methods.
Prediction markets increasingly list contracts settling on an asset price that holders can move by trading the underlying. We build a model showing that such contracts transfer wealth from prediction-market liquidity traders to manipulators and harm price discovery in the underlying, even as it becomes more liquid. After the launch of Polymarket's five-minute Bitcoin contract, settlement-time spot order flow spikes, causing large price reversals after settlement. Manipulators capture a large amount of profit, mostly from retail. Manipulation is largely absent in the fifteen-minute contracts: lengthening the contract horizon removes it, providing the market-design remedy our model and evidence support.
Liu Hong Yuan Tom, Ruilin Wang, Hairui Wang, Ziqi Cao · 5 authors
This study examines the impact of social media sentiment on Bit-coin market volatility. While existing literature often relies on single-source data or isolated factors, this research introduces a novel three-source pricing framework that integrates Twitter-derived social media sentiment, investor leverage ratios, and historical market data. Using a Weighted Least Squares (WLS) regression model to address heteroscedasticity in financial time series, we analyze daily Bitcoin returns from 2021 to the first half of 2022. Our results indicate that both social media sentiment has a statistically significant positive effect on Bitcoin returns. The model successfully identified high-risk market conditions, as validated by the May-June 2021 crash. These findings demonstrate that social media sentiment has a huge impact on cryptocurrency markets.
This technical report provides an empirical evaluation of Bitcoin Layer-2 execution environments (BOB, Bitlayer, Citrea, Stacks, and Rootstock) against a six-layer architectural framework designed for institutional-grade decentralized finance (DeFi). Using Tage_Root — a purpose-built reference implementation operationalizing Bitcoin-native execution (L1) and trust-minimized bridging (L2) — the analysis assesses conditions required for credible BTC-denominated yield markets, including intent-based routing, autonomous capital allocation, zero-knowledge compliance, and accountable governance. The findings reveal that while several systems have substantially solved the bridge problem at the technical level, critical higher-layer infrastructure remains absent or weak. This architectural gap explains the persistent idleness of bridged BTC and the low capital efficiency observed in BTCFi protocols, despite significant growth in bridging capacity. The report offers a code-grounded diagnostic benchmark and lays the empirical foundation for forthcoming theoretical work on the “Bridge Problem” and the pricing of Bitcoin-denominated yield. It argues that trust-minimized execution alone is insufficient for institutional capital formation in Bitcoin DeFi.
Understanding Proof-of-Work in Blockchain: Foundations, Security, and Limitations Keywords: Blockchain, Consensus, Proof-of-Work, Cryptographic Hash, Cryptography, 51% Attack. 1. Introduction In traditional distributed systems, such as banking databases, a central authority determines transaction validity. In contrast, decentralized networks like Bitcoin lack a central server, allowing unrestricted participation. This structure introduces two significant challenges:This results in two critical challenges: 1. The Byzantine Generals Problem: How do independent nodes agree on a single history of data if some nodes are malicious or untruthful? 2. Sybil Attacks: What stops an attacker from creating 10 million fake virtual nodes to vote and overpower honest nodes? Proof-of-Work (PoW) addresses both challenges. Instead of assigning one vote per identity, which is susceptible to falsification, PoW allocates voting power according to computational resources, which require significant hardware and energy investment. 2. The Core Mechanics: How Mining Actually Works Mining functions as a network-wide lottery, where the probability of success is proportional to computational speed. The process begins with solving a cryptographic puzzle. 2.1 The Cryptographic Puzzle A block consists of a batch of transactions, the hash of the previous block, and a field called a nonce (number used once). Miners repeatedly modify the nonce until the hash of the entire block matches a specific pattern.Specifically, the resulting hash must be less than or equal to a predetermined target value. +---------------------------------------------------------+ | BLOCK HEADER | | [Prev Hash] + [Merkle Root (TXs)] + [Timestamp] + [Nonce] | +---------------------------------------------------------+ | v SHA-256 Hashing | v Is the Hash < Target Threshold? / \ YES NO / \ [Success! Broadcast Block] [Increment Nonce & Try Again] Because SHA-256 is a cryptographic hash function, it has two key properties: Pre-image Resistance (One-Way): You cannot reverse-engineer a hash. If I give you a hash output, you cannot calculate the input. Avalanche Effect: Changing just one bit in the nonce completely alters the final hash output unpredictably. As a result, no mathematical shortcut exists for determining the correct nonce. Miners must use brute-force computation, generating billions of hashes per second (hash rate) until a valid solution is identified (Hash Rate — Measuring Bitcoin's Mining Power, 2026). Once a solution is found, the miner broadcasts the block, and other nodes verify it instantly with a single hash calculation, illustrating computational asymmetry. This mechanism maintains the network's equilibrium. 2.2 Difficulty Adjustment When additional miners join the network, the aggregate hash rate increases, resulting in faster block discovery. To maintain consistent block times, the protocol automatically adjusts the target threshold.If blocks are being found faster than the target time (e.g., 10 minutes in Bitcoin), the target number decreases. A smaller target means the hash must start with more leading zeros, making it statistically harder to guess. 3. Security Framework: The Rules of Engagement PoW operates on the economic principle that securing the network should be more profitable than attacking it. The following rule defines the network's dispute resolution mechanism. 3.1 The Longest Chain Rule If two miners simultaneously discover valid blocks, the network temporarily splits into two branches, known as a fork. Nodes resolve this by following the longest chain, which is defined as the branch with the greatest accumulated proof-of-work, thus maintaining a unified transaction history. [Block 101] ---> (Orphaned / Dropped) / ---- [Block 100] --+ \ [Block 101] ---> [Block 102] <--- Longest Chain (Accepted) 3.2 The 51% Attack If an attacker manages to control more than 50% of the network’s total computing power, they can out-mine the honest portion of the network.An attacker may mine a private chain in secret, spend coins on the public chain, and later broadcast the longer private chain. According to the longest chain rule, the network accepts the attacker's version of history, thereby invalidating transactions on the honest chain. This scenario, known as a Double-Spend Attack, highlights a significant vulnerability and contributes to ongoing criticism of PoW despite its security advantages. 4. Why the Industry is Moving Away from PoW While PoW is incredibly secure, it has two major flaws that make it difficult to scale for modern applications. 4.1 The Scalability Problem In PoW systems, each full node must process and store every transaction for verification. Due to limited block sizes and intentionally high block times to prevent network desynchronization, transaction throughput remains low. For example, Bitcoin processes approximately 7 transactions per second (TPS), whereas Visa handles thousands of TPS. 4.2 Energy Consumption Miners compete to achieve the highest hash rate by continuously operating large-scale data centers equipped with specialized hardware (ASICs). This process consumes substantial amounts of electricity, comparable to the consumption of a medium-sized country, and results in significant environmental impact. 5. Conclusion Proof-of-Work constituted a significant advancement in computer science by linking digital consensus to physical resource constraints, particularly energy. This innovation demonstrated the feasibility of decentralized trust. However, due to limited throughput and substantial energy requirements, newer blockchain networks increasingly adopt alternative consensus mechanisms, such as Proof-of-Stake (PoS), where voting power is determined by cryptocurrency holdings rather than energy expenditure. References Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. (The original whitepaper). Eyal, I., & Sirer, E. G. (2014). Majority is not enough: Bitcoin mining is vulnerable. (Introduced the concept of Selfish Mining). Narayanan, A., et al. (2016). Bitcoin and Cryptocurrency Technologies. Princeton University Press. (An excellent foundational textbook for CS students). (2026). Hash Rate — Measuring Bitcoin's Mining Power. Bitcoin Notes Online. https://www.bitcoinnotesonline.com/learn/hash-rate
Qualitative Jobs-to-be-Done-Längsschnittstudie zur Technologie-Adoption am Beispiel Bitcoin im DACH-Raum (2019–2026). Auf Basis von n=35 Tiefeninterviews und 1.207 Evidence Cards rekonstruiert die Studie die realen Kaufentscheidungen („Pull statt Push") statt Spekulations- oder Preisnarrative. Sechs Segmente plus zwei Sonderfälle. Methode: JTBD R&I Framework (Peter Rochel, Oberwasser Consulting). Alle Einzelauswertungen pseudonymisiert. Änderungen gegenüber Version 1.0 (Stand dieser Fassung: 08.08.2026) Sachliche Korrektur im Kapitel "Warum diese Studie". Die Angabe zu den 27 Kölner Straßenbefragungen war in Version 1.0 falsch beschriftet. Der Wert von 52 Prozent (14 von 27 Befragten) bezeichnet nicht "kennt Bitcoin nicht oder ist neutral", sondern Befragte, bei denen sich kein Anknüpfungspunkt zu einem der Käufersegmente erkennen ließ. Die Passage ist korrigiert und um zwei bisher unveröffentlichte Werte ergänzt: ein Drittel der Befragten war neutral oder hatte nie von Bitcoin gehört, häufigste Barriere war mit 67 Prozent fehlendes Wissen. Dieselbe Falschaussage im Kasten "Kernaussagen für Multiplikatoren" (S. 6) korrigiert. Sie stand dort ein zweites Mal, ausgeschrieben statt als Zahl. Der Kasten ist als kontext-frei zitierbar für Presse gekennzeichnet und damit die Stelle mit der höchsten Weiterverbreitung im Dokument. Zitierhinweis und Versionierungsblock erweitert um Version, Erstveröffentlichungsdatum, Stand der Fassung und DOI. Eine inhaltsleere Seite entfernt (Version 1.0, Seite 32) und das Titelblatt auf August 2026 datiert. Erstveröffentlichung (25.06.2026) und Datenstand (23.06.2026) sind unverändert. Der Volltext ist im Übrigen identisch; ein vollständiger Diff gegen Version 1.0 zeigt keine weiteren inhaltlichen Abweichungen.
NGOs Funding Trust, Blockchain and RedChain Prof. Victor Alvarez, MBA ORCID iD: 0009-0001-7933-3830 Department Research in Economic , IEBS Business School, 08840 Barcelona, Spain Department of Humanitarian Economics and NGO Management ETU Institute, Birkirkara, Malta Abstract Persistent trust deficits between donor agencies and Non-Governmental Organizations (NGOs) continue to undermine the efficiency and effectiveness of humanitarian and development assistance, particularly in low-income and institutionally fragile environments. Concerns regarding fund diversion, beneficiary duplication, limited transparency, and weak accountability mechanisms have intensified demand for innovative governance solutions. This paper explores the potential of blockchain technology to strengthen trust in NGO funding through two complementary models: (1) a permissioned blockchain framework for beneficiary verification and aid tracking, and (2) RedChain, a privacy-preserving blockchain infrastructure for humanitarian assistance developed by the Spanish Red Cross. The proposed NGO Trust framework utilizes a distributed ledger to maintain immutable and auditable records of beneficiary registration and fund allocation. By recording encrypted identity credentials and digitally signed transactions, the system reduces the risk of duplicate beneficiary claims, fraud, and reporting inconsistencies across participating organizations. A participation and penalty mechanism further enhances network integrity by incentivizing honest behavior among stakeholders. RedChain extends this approach by integrating blockchain-based transaction recording with zero-knowledge proof technologies, enabling transparent aid distribution while preserving beneficiary privacy. With nearly one million registered transactions, the platform demonstrates the operational viability of blockchain-enabled humanitarian governance at scale. By synthesizing these approaches, this paper proposes an integrated framework for transparent NGO funding, combining beneficiary integrity verification, transaction traceability, privacy protection, and donor accountability. The findings suggest that distributed ledger technologies can significantly improve trust relationships between donors, NGOs, and beneficiaries, while supporting more efficient, transparent, and equitable aid distribution systems. The study contributes to the emerging literature on digital governance, nonprofit economics, and technology-enabled development finance by identifying blockchain as a foundational infrastructure for next-generation humanitarian and social-impact ecosystems. Keywords Blockchain; NGO governance; Humanitarian aid; Trust; Transparency; Beneficiary duplication; Zero-knowledge proofs; RedChain; Donor accountability; Privacy-preserving technology; Smart contracts; Aid distribution JEL Classification G30 – Corporate Finance and Governance: General L31 – Nonprofit Institutions; NGOs; Social Entrepreneurship O33 – Technological Change: Choices and Consequences; Diffusion Processes F35 – Foreign Aid H84 – Disaster Aid and Relief 1. Introduction Non-Governmental Organizations (NGOs) play a central role in delivering humanitarian assistance, poverty alleviation programs, disaster relief, education, health services, and sustainable development initiatives worldwide. According to the United Nations and international development agencies, NGOs have become increasingly important intermediaries between donors, governments, and beneficiaries, particularly in regions where state capacity is limited or institutional trust is weak. Despite their growing influence, concerns regarding transparency, accountability, and the efficient allocation of resources continue to challenge the nonprofit sector (Edwards & Hulme, 1996; Ebrahim, 2003; Najam, 1996). The economics of nonprofit organizations has long emphasized the importance of trust as a mechanism for overcoming information asymmetries between donors and service providers (Hansmann, 1980). Donors frequently lack direct information regarding how funds are allocated, whether intended beneficiaries actually receive assistance, and whether reported outcomes accurately reflect project performance. This information gap creates principal-agent problems in which monitoring costs are high and opportunities for misreporting, inefficiency, or fraud may arise (Pratt & Zeckhauser, 1985; Tirole, 2006). As charitable donations and development aid increasingly flow through complex international networks, maintaining donor confidence has become a critical governance challenge. A substantial body of research has documented accountability deficiencies within humanitarian and development organizations. Ebrahim (2005) argues that traditional accountability systems often emphasize upward reporting to donors while providing limited mechanisms for beneficiary participation and verification. Similarly, Gugerty and Prakash (2010) note that transparency initiatives frequently rely on self-reported information that is difficult to independently audit. In international aid programs, concerns have emerged regarding duplicate beneficiary registrations, diversion of funds, weak recordkeeping systems, and fragmented information sharing among organizations operating in the same geographic areas (World Bank, 2016; OECD, 2021). Digital technologies have increasingly been proposed as tools to address these governance challenges. The broader literature on e-governance and digital accountability suggests that information systems can reduce transaction costs, improve record accuracy, and strengthen institutional transparency (Heeks, 2002; Cordella & Tempini, 2015). Among emerging technologies, blockchain has attracted considerable attention due to its capacity to create immutable, distributed, and verifiable records without requiring centralized trust authorities (Nakamoto, 2008). Since the introduction of Bitcoin, blockchain applications have expanded far beyond digital currencies into supply chain management, public administration, healthcare, identity systems, and humanitarian operations (Tapscott & Tapscott, 2016; Casino, Dasaklis & Patsakis, 2019). Scholars have argued that distributed ledger technologies may improve transparency and accountability by creating tamper-resistant transaction histories accessible to multiple stakeholders (Swan, 2015; Treiblmaier, 2018). Within development economics, blockchain-based systems have been proposed to improve aid distribution, reduce corruption, facilitate identity verification, and enhance financial inclusion in underserved regions (Kshetri, 2017; Saberi et al., 2019). Recent humanitarian applications provide evidence of growing institutional interest in blockchain-enabled governance. The United Nations World Food Programme's Building Blocks initiative demonstrated the feasibility of blockchain-based refugee assistance by facilitating aid transfers while reducing administrative costs and improving transaction traceability. Similarly, studies by Juskalian (2018), Mikhaylov et al. (2020), and Wang et al. (2022) suggest that distributed ledger technologies may strengthen accountability mechanisms in humanitarian environments characterized by weak institutional infrastructure. Nevertheless, important challenges remain. Public transparency requirements often conflict with the need to protect sensitive beneficiary information. Humanitarian organizations must balance donor demands for accountability with ethical obligations regarding privacy, dignity, and data protection. The emergence of privacy-enhancing cryptographic techniques, particularly zero-knowledge proofs, offers a potential solution to this dilemma by enabling verification without revealing underlying personal information (Goldwasser, Micali & Rackoff, 1989; Ben-Sasson et al., 2014). These technologies have increasingly been incorporated into blockchain architectures seeking to combine transparency with confidentiality. This paper contributes to the growing literature on nonprofit governance and development finance by examining two complementary blockchain-based approaches to strengthening trust in NGO funding systems. The first is a permissioned blockchain framework designed to prevent beneficiary duplication and improve donor oversight through cryptographically verifiable registration and transaction records. The second is RedChain, a privacy-preserving humanitarian aid platform developed by the Spanish Red Cross that combines blockchain technology with zero-knowledge proofs to support transparent aid distribution while safeguarding beneficiary privacy. By integrating insights from these models, the study proposes a comprehensive framework for Transparent NGO Funding that addresses four persistent governance challenges: beneficiary verification, transaction traceability, privacy preservation, and donor accountability. The analysis contributes to the fields of nonprofit economics, digital governance, and development finance by demonstrating how blockchain technologies may reduce information asymmetries, lower monitoring costs, and strengthen trust among donors, NGOs, and beneficiaries. Ultimately, the paper argues that distributed ledger systems can serve as foundational infrastructure for a new generation of accountable, transparent, and privacy-respecting humanitarian ecosystems.
Miners of proof-of-work networks like Bitcoin tend to gravitate towards regions with cheap energy. We analyze risks associated with this geographical centralization by exploiting a local electricity supply shock. Compared to a control group consisting of an energy-efficient proof-of-stake cryptocurrency, the blockchain’s capacity for processing transactions decreases while transaction fees increase substantially. The increased settlement latency on the blockchain also reduces secondary market quality as seen in higher exchange rate volatility, lower liquidity, and larger price differences between exchanges. Overall, our results suggest that geographical centralization poses short-lived but potentially severe system-wide risks to proof-of-work networks.
Decentralised systems are often built to avoid central control, but their evolution almost always depends on centralised platforms, informal maintainer authority, and a surprising amount of unpaid goodwill. To address this uncomfortable mismatch, we introduce TwoStepDemocracy, a technical proof-of-concept for protocol-native software evolution. The prototype combines costly cryptographic identities, peer-to-peer dissemination, issue and solution voting, and Bitcoin-based funding campaigns. Users can express demand by proposing and voting on issues; developers can submit concrete solutions; and accepted work can be linked to voluntary, non-custodial funding. The design deliberately separates demand, approval, and payment. This way, money can support a solution, but it never buys more voting power. The prototype demonstrates that such a coordination layer can be built as a peer-to-peer implementation with local storage, signed governance objects, and Bitcoin integration. We studied performance, scalability, and costs across storage, identity management, and funding. The results show technical feasibility, but not yet social viability. A larger user study is still needed to evaluate whether real communities would, in practice, vote, fund, and coordinate through this mechanism.
We investigate the evolving structure of interactions in cryptocurrency markets using a network-based framework constructed from high-frequency price data spanning 2020-2025. Directed and weighted networks are constructed from statistically significant Granger causal relationships between cryptocurrency log-returns, enabling us to quantify the flow of influence across assets. We find that normalized returns exhibit heavy-tailed distributions, consistent with the presence of large intermittent fluctuations and in line with stylized facts of financial markets. The resulting networks display pronounced heterogeneity in link weights and nodal strengths, indicating that a small subset of cryptocurrencies contributes disproportionately to market dynamics. By ranking cryptocurrencies based on their nodal out-strength, we uncover a dynamically evolving hierarchy of influence. Ethereum consistently emerges as the most influential asset, while Bitcoin shows a gradual decline in its relative importance. The ranking structure exhibits substantial temporal variability, with multiple cryptocurrencies entering and exiting the top positions over time. Our findings reveal a highly competitive and non-stable organization of the cryptocurrency ecosystem.
Cryptocurrencies have received long-term interest among investors because of the features of Bitcoin since its introduction in 2009. However, it is the same features that pose serious and diverse threats. These risks are very dangerous to the security of investors and the integrity of the market. Although their urgency is immense, there are very few systematic analyses that incorporate both regulatory and technological views. In this research, the mixed-method design is used, and an empirical investigation of high-profile security events is combined with the critical analysis of regulatory and technical literature in order to define, classify, and track the causes of the most widespread risks. The article explores the weaknesses and strengths of the existing laws and strategies that would curb identified risks that cryptocurrencies present. It also suggests practical and tangible solutions, which would make use of new technologies to minimize the damages and risks of cryptocurrencies to a greater extent. The analysis in this study proves that properly reducing risks should be performed in a two-faceted way; it should be done with the help of the regulation gaps in action and the utilization of new, protocol-infused technological limits. This study presents a moderate structure that is meant to achieve market security that does not suppress the dynamism and transparency of the cryptocurrency ecosystem. This study analyzes the problem of cryptocurrency security, financial regulation, blockchain technology, risk mitigation, and decentralized finance.
ABSTRACT This report examines the “Bitcoin as digital gold” narrative through the concept of the Retailization of Scarcity. It argues that Bitcoin’s mathematical supply limit does not automatically create value, and that scarcity becomes financially powerful only when it is narrated, packaged, institutionalized, traded, and repeatedly believed by market participants. Rather than claiming that Bitcoin is inherently fraudulent or meaningless, the report focuses on the structures surrounding Bitcoin: price prophecy, financial packaging, retail investor access, media amplification, and the asymmetry of forecast responsibility. It distinguishes Bitcoin as a protocol and speculative asset from the commercial narratives that transform limited code into a simplified investment myth. The report analyzes how the digital gold metaphor compresses technical, market, custody, liquidity, regulatory, and incentive risks into emotionally powerful language. It also examines how forecasts, exchange-traded products, custodial services, and public narratives can turn uncertainty into perceived inevitability for ordinary investors. The central argument is that the problem is not the existence of Bitcoin itself, but the hidden retailization of scarcity: the process through which mathematical scarcity is disguised as inevitable wealth, price prophecy as foresight, convenience as conviction, and monetization as monetary truth. This document is an analytical report and does not constitute investment advice.
In the context of developments in the field of financial technology, cryptocurrencies, emerging as a new asset class, have garnered significant attention in financial markets in recent years, attracting investors, researchers, and regulators, and leading to numerous publications. Bibliometric studies evaluate these publications based on criteria such as the number of publications, their quality, the countries of publication, authors, and journals. This study aims to perform a bibliometric analysis of the academic literature available in the Web of Science (WoS) database, focusing on the volatility of cryptocurrency prices. It analyzes the magnitude and development of academic interest in this field, along with key words, the most cited works, and research trends, in an effort to determine the density of studies, their impact areas, and the academic networks that have emerged in this field. Based on the general findings, it is observed that the number of studies has been on an increasing trend over the years, and that the publications are predominantly in the field of Business Economics. Moreover, it has been found that publications are mainly in finance journals. In terms of network maps, the findings suggest a moderate level of collaboration among authors, with the United Kingdom and the People's Republic of China occupying central positions in international collaboration. In terms of citations, authors such as Lucey, and Katsiampa, Paraskevi, have emerged as prominent figures in the fields of cryptocurrencies and volatility. Regarding key words, terms like 'cryptocurrency', 'cryptocurrencies', 'volatility', and 'bitcoin' are predominantly used in these studies." Keywords: cryptocurrencies, bitcoin, volatility, bibliometric analysis
This study compares the forecasting performance of four deep learning architectures—GRU, LSTM, RNN, and CNN—for one-step-ahead Bitcoin price prediction. A grid search determined the optimal configuration, which was applied uniformly across models to ensure fair evaluation. Using daily BTC closing prices from January 2018 to July 2025, it is found that the GRU model achieved the lowest forecasting errors (MSE, RMSE, MAE, MAPE) and the highest R², with LSTM performing closely behind. Visual analyses confirmed that GRU and LSTM maintained stronger alignment with actual prices during volatile periods. To assess economic value, model forecasts were integrated into a rule-based trading strategy under realistic market frictions, including a 0.10% transaction cost and a 0.10% trading threshold, with both short-selling-enabled and long-only variants tested. The GRU strategy with short-selling generated the highest terminal wealth (approximately 24% higher than the Buy-and-Hold benchmark) and superior risk-adjusted returns, measured by CAGR, Maximum Drawdown, and Sharpe Ratio. The findings demonstrate that careful hyperparameter optimization, coupled with an architecture capable of capturing complex temporal dependencies, can significantly improve both predictive accuracy and trading profitability in cryptocurrency markets. These results provide practical implications for designing AI-driven trading systems.
Ayei E. Ibor, Denis U. Ashishie, John Adinya Odey, Bassey Ele · 5 authors
ABSTRACT Elliptic curve cryptography ( ECC ) underpins the security of most blockchain systems, yet its practical implementations face numerous vulnerabilities. In this systematic literature review ( SLR ), we catalogue and analyze attacks on ECC in the context of blockchain security, including side‐channel attacks, nonce/ PRNG failures, cryptanalysis, and implementation flaws, and we survey proposed countermeasures. We follow rigorous SLR methodology with defined inclusion/exclusion criteria, search strategies across databases such as IEEE Xplore, ACM , Scopus, Web of Science, and clear data synthesis, ensuring replicability. Emphasizing empirical case studies and real‐world exploits, we discuss instances where ECC weaknesses led to blockchain breaches including biased elliptic curve digital signature algorithm nonces exposing Bitcoin/Ethereum private keys, smartphone power analysis revealing wallet keys, and Trezor hardware‐wallet key extraction via single‐trace side‐channel analysis ( SCA ). We tabulate known attack vectors versus affected systems, and similarly compare countermeasure techniques such as hybrid classical/quantum schemes, threshold signatures, and zero‐knowledge proofs, along with implementation trade‐offs. We evaluate advances such as Curve25519/ EdDSA and ARM SVE2 to mitigate side‐channel leakage. Our findings highlight that practical security of blockchain cryptosystems depends on correct ECC implementation and emerging cryptographic upgrades, not merely on the mathematical hardness of the elliptic curve discrete logarithm problem.
Constantine Doumanidis, Anya Kalogerakos, Maria Apostolaki
BGP hijacking enables impersonation attacks in which adversaries divert traffic at the prefix level and serve malicious content to unsuspecting clients. Detecting such attacks has traditionally been the responsibility of network operators, leaving end hosts exposed for hours. We argue that end hosts can detect prefix-level impersonation independently, exploiting a fundamental asymmetry: a BGP hijack diverts traffic for an entire IP prefix, but impersonating every co-hosted service within that prefix is prohibitively difficult at scale, especially if each service is authenticated by a different Certificate Authority. We propose HOWLR, a tool that operationalizes this insight by using co-hosted, TLS-authenticated services as witnesses: if a client can no longer authenticate them, it has evidence of an ongoing attack. This work evaluates the feasibility of this method by quantifying the existence and diversity of witnesses in the wild. We show that HOWLR can protect 89% of Tor relay prefixes, and 75% of Bitcoin pool gateway prefixes.
This paper argues that universal, cross-domain trust scores — from credit ratings and ESG scores to AI-generated trust metrics — face structural limits that better data or better models do not remove. The claim is not that scoring is never useful, but that compressing trust into a single comparable number, used for high-stakes allocation across contexts, recurrently fails. Trust is treated here not as a scalar quantity but as a contextual, relational, and time-dependent state. The paper identifies five recurring failure modes (context collapse, Goodhart's Law, epistemic centralization, irreversibility, and metric substitution for truth), illustrated through documented institutional failures (Enron, Wirecard, Volkswagen Dieselgate, the 2008 subprime crisis, and ESG rating practice). An informal impossibility argument — analogous in form to Arrow's theorem, not a formal mathematical proof — suggests that no single universal trust score can jointly satisfy context-independence, temporal stability, observer-neutrality, and manipulation-resistance. The paper then discusses proof-based verification as a complementary paradigm: for a bounded class of objective, checkable claims, the need for trust is reduced through local verification rather than measurement. Examples include Bitcoin proof-of-work, zero-knowledge proofs, and blockchain-based supply chain traceability. The limits of this approach are discussed explicitly, including the oracle problem and the irreducibly judgmental claims that proof cannot settle. This is version 2.0, a substantial revision repositioning the work from a position paper toward a conceptual analysis: the central thesis is qualified, an explicit scope-and-limitations section is added, the impossibility argument is reframed as informal, and the limits of proof-based verification are addressed directly.