arXiv subjects

Paolo Tasca

Publications and source records attributed to Paolo Tasca.

At least 19 recordsLinked to original sources

arXiv2026

A Network Inefficiency Metric for Structural Stress Detection in Hedera Transactions

Quantifying structural stress in transaction networks requires metrics that capture structural organization beyond transaction volume alone. In this work, we introduce the Inefficiency Metric, a deterministic indicator designed to characterize the routing structure of capital flows in decentralized systems. Using Principal Component Analysis and Pearson correlation matrices computed from a six-year Hedera transaction dataset, we identify two dominant and largely independent structural dimensions: the effective diameter, related to the spatial extension of transaction propagation, and the closeness centrality, associated with the efficiency of network-level flow processing. The proposed metric reveals significant topological fluctuations associated with major macroeconomic and ecosystem-level events. Increased inefficiency is observed during periods marked by intermediary fragmentation or rapid smart-contract expansion, whereas lower inefficiency corresponds to phases of network compaction during market stress or institutional concentration. Comparison with a seven-dimensional Isolation Forest approach shows that the metric effectively captures severe multidimensional anomalies while preserving a clear structural interpretation. Overall, these results provide a physics-inspired framework for relating the large-scale organization of decentralized transaction networks to observable economic dynamics.

physics.soc-ph↗

arXiv2026

SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergence

The integration of Artificial Intelligence (AI) with Distributed Ledger Technology (DLT) has become a growing research area, yet contributions tend to cluster around specific application domains or examine only one direction of the integration, leaving the broader architectural interplay between the two technologies poorly understood. This work addresses that gap through a structured, bidirectional review of peer-reviewed studies published between 2020 and 2025. We classify contributions along two directions: AI-enhanced DLT, and DLT-enhanced AI. In the first case, we examine how AI techniques improve DLT systems across five layers: data, network, consensus, execution, and application layers. In the second case, we analyse how DLT supports AI systems across five layers: infrastructure, data, model, inference, and application layers, with particular attention to federated learning, model evaluation, and multi-agent coordination. The analysis reveals that most works concentrate on a small subset of layers: execution and consensus for AI-enhanced DLT, data and model for DLT-enhanced AI. Other layers remain comparatively neglected. Despite reported improvements in controlled settings, no study demonstrates deployment at production scale, and the field has not yet offered satisfying answers to fundamental questions around scalability, interoperability, and verifiable execution. We argue that progress will require cross-layer co-design and empirical validation in real-world settings.

cs.CR↗

arXiv2026

DLT-Corpus: A Large-Scale Text Collection for the Distributed Ledger Technology Domain

We introduce DLT-Corpus, the largest domain-specific text collection for Distributed Ledger Technology (DLT) research to date: 2.98 billion tokens from 22.12 million documents spanning scientific literature (37,440 publications), United States Patent and Trademark Office (USPTO) patents (49,023 filings), and social media (22 million posts). Existing Natural Language Processing (NLP) resources for DLT focus narrowly on cryptocurrency price prediction and smart contracts, leaving domain-specific language underexplored despite the sector's ~$3 trillion market capitalization and rapid technological evolution. We demonstrate DLT-Corpus' utility by analyzing patterns of technology emergence and market-innovation correlations. Findings reveal that technologies first appear in our scientific literature subset before reaching patents and social media, following traditional technology transfer patterns. While social media sentiment remains overwhelmingly bullish even during crypto winters, scientific and patent activity grows less tied to short-term sentiment, tracking overall market expansion in a virtuous cycle in which research precedes and enables economic growth that, in turn, funds further innovation. We release the DLT-Corpus and companion artifacts: LedgerBERT (+23% over BERT-base on DLT-specific Named Entity Recognition (NER) task), a sentiment analysis dataset of 23,301 crypto news headlines and descriptions, tools, and code.

cs.CL↗

arXiv2025

Investigating Sharding Advancements, Methodologies, and Adoption Potential in Hedera

Sharding has emerged as a critical solution to address the scalability challenges faced by blockchain networks, enabling them to achieve higher transaction throughput, reduced latency, and optimized resource usage. This paper investigates the advancements, methodologies, and adoption potential of sharding in the context of Hedera, a distributed ledger technology known for its unique Gossip about Gossip protocol and asynchronous Byzantine Fault Tolerance (ABFT). We explore various academic and industrial sharding techniques, emphasizing their benefits and trade-offs. Building on these insights, we propose a hybrid sharding solution for Hedera that partitions the network into local and global committees, facilitating efficient cross-shard transactions and ensuring robust security through dynamic reconfiguration. Our analysis highlights significant reductions in storage and communication overhead, improved scalability, and enhanced fault tolerance, demonstrating the feasibility and advantages of integrating sharding into Hedera's architecture.

cs.DC↗

arXiv2025

Consensus Power Inequality: A Comparative Study of Blockchain Networks

The distribution of consensus power is a cornerstone of decentralisation, influencing the security, resilience, and fairness of blockchain networks while ensuring equitable impact among participants. This study provides a rigorous evaluation of consensus power inequality across five prominent blockchain networks - Bitcoin, Ethereum, Cardano, Hedera, and Algorand - using data collected from January 2022 to July 2024. Leveraging established economic metrics, including the Gini coefficient and Theil index, the research quantitatively assesses how power is distributed among blockchain network participants. A robust dataset, capturing network-specific characteristics such as mining pools, staking patterns, and consensus nodes, forms the foundation of the analysis, enabling meaningful comparisons across diverse architectures. Through an in-depth comparative study, the paper identifies key disparities in consensus power distribution. Hedera and Bitcoin demonstrate more balanced power distribution, aligning closely with the principles of decentralisation. Ethereum and Cardano demonstrate moderate levels of inequality. However, contrary to expectations, Ethereum has become more concentrated following its transition to Proof-of-Stake. Meanwhile, Algorand shows a pronounced centralisation of power. Moreover, the findings highlight the structural and operational drivers of inequality, including economic barriers, governance models, and network effects, offering actionable insights for more equitable network design. This study establishes a methodological framework for evaluating blockchain consensus power inequality, emphasising the importance of targeted strategies to ensure fairer power distribution and enhancing the sustainability of decentralised systems. Future research will build on these findings by integrating additional metrics and examining the influence of emerging consensus mechanisms.

cs.CR↗

arXiv2025

LLM-Powered Multi-Agent System for Automated Crypto Portfolio Management

Cryptocurrency portfolio management requires the fusion of heterogeneous multi-modal signals, including structured price and on-chain time series, unstructured news text, and technical indicators, under high-volatility and real-time constraints. While deep learning approaches show predictive capability, their opacity limits practical adoption, and single large language model (LLM) agents struggle to process the breadth of modality-specific inputs needed for robust decision-making. We propose a multi-agent system (MAS) framework in which three modality-specialised agents, a Crypto Agent for market dynamics, a News Agent for weekly news sentiment, and a Trading Agent for signal fusion and portfolio execution, decompose the task across three communication architectures: hierarchical, collaborative, and debate. We evaluate four capability configurations: zero-shot, chain-of-thought (CoT), retrieval-augmented generation (RAG), and skill-augmented. In a 52-week backtest over calendar year 2025 across the top 15 L1 blockchain native cryptocurrencies by market capitalisation as of January 2025, the best configuration, Hierarchical (Skill), achieves a cumulative return of 133.52% and a Sharpe ratio of 1.502, outperforming single-agent variants, passive benchmarks, and deep learning baselines. An ablation study identifies the Crypto Agent as the most critical component, with its removal reducing cumulative return by 42.57 percentage points. A cross-model comparison further shows that MAS outperforms the single-agent baseline under GPT-4o, GPT-5, and Claude Sonnet 4.5, suggesting that the benefit of multi-agent coordination is model-agnostic. Unlike black-box deep learning models, every portfolio decision is traceable to explicit agent reasoning, offering an interpretable and effective approach to multi-modal cryptocurrency portfolio management.

q-fin.TR↗

arXiv2024

The Unintended Carbon Consequences of Bitcoin Mining Bans: A Paradox in Environmental Policy

The environmental impact of Bitcoin mining has become a significant concern, prompting several governments to consider or implement bans on cryptocurrency mining. However, these well-intentioned policies may lead to unintended consequences, notably the redirection of mining activities to regions with higher carbon intensities. This study aims to quantify the environmental effectiveness of Bitcoin mining bans by estimating the resultant carbon emissions from displaced mining operations. Our findings indicate that, contrary to policy goals, Bitcoin mining bans in low-emission countries can result in a net increase in global carbon emissions, a form of aggravated carbon leakage. We further explore the policy implications of these results, suggesting that more nuanced approaches may be required to mitigate the environmental impact of cryptocurrency mining effectively. This research contributes to the broader discourse on sustainable cryptocurrency regulation and provides a data-driven foundation for evaluating the true environmental costs of Bitcoin regulatory policies.

cs.CY↗

arXiv2024

No Questions Asked: Effects of Transparency on Stablecoin Liquidity During the Collapse of Silicon Valley Bank

Fiat-pegged stablecoins are by nature exposed to spillover effects during market turmoil in Traditional Finance (TradFi). We observe a difference in TradFi market shocks impact between various stablecoins, in particular, USD Coin (USDC) and Tether USDT (USDT), the former with a higher reporting frequency and transparency than the latter. We investigate this, using top USDC and USDT liquidity pools in Uniswap, by adapting the Marginal Cost of Immediacy (MCI) measure to Uniswap's Automated Market Maker, and then conducting Difference-in-Differences analysis on MCI and Total Value Locked (TVL) in USD, as well as measuring liquidity concentration across different providers. Results show that the Silicon Valley Bank (SVB) event reduced USDC's TVL dominance over USDT, increased USDT's liquidity cost relative to USDC, and liquidity provision remained concentrated with pool-specific trends. These findings reveal a flight-to-safety behavior and counterintuitive effects of stablecoin transparency: USDC's frequent and detailed disclosures led to swift market reactions, while USDT's opacity and less frequent reporting provided a safety net against immediate impacts.

q-fin.TR↗

arXiv2024

Piercing the Veil of TVL: DeFi Reappraised

Total value locked (TVL) is widely used to measure the size and popularity of decentralized finance (DeFi). However, TVL can be easily manipulated and inflated through "double counting" activities such as wrapping and leveraging. As existing methodologies addressing double counting are inconsistent and flawed, we propose a new framework, termed "total value redeemable (TVR)", to assess the true underlying value of DeFi. Our formal analysis reveals how DeFi's complex network spreads financial contagion via derivative tokens, increasing TVL's sensitivity to external shocks. To quantify double counting, we construct the DeFi multiplier, which mirrors the money multiplier in traditional finance (TradFi). This measurement reveals substantial double counting in DeFi, finding that the gap between TVL and TVR reached \$139.87 billion during the peak of DeFi activity on December 2, 2021, with a TVL-to-TVR ratio of approximately 2. We conduct sensitivity tests to evaluate the stability of TVL compared to TVR, demonstrating the former's significantly higher level of instability than the latter, especially during market downturns: A 25% decline in the price of Ether (ETH) leads to a \$1 billion greater non-linear decrease in TVL compared to TVR via the liquidations triggered by derivative tokens. We also document that the DeFi money multiplier is positively correlated with crypto market indicators and negatively correlated with macroeconomic indicators. Overall, our findings suggest that TVR is more reliable and stable than TVL.

q-fin.GN↗

arXiv2023

AMM-based DEX on the XRP Ledger

Automated Market Maker (AMM)-based Decentralized Exchanges (DEXs) are crucial in Decentralized Finance (DeFi), but Ethereum implementations suffer from high transaction costs and price synchronization challenges. To address these limitations, we compare the XRP Ledger (XRPL)-AMM-Decentralized Exchange (DEX), a protocol-level implementation, against a Generic AMM-based DEX (G-AMM-DEX) on Ethereum, akin to Uniswap's V2 AMM implementation, through agent-based simulations using real market data and multiple volatility scenarios generated via Geometric Brownian Motion (GBM). Results demonstrate that the XRPL-AMM-DEX achieves superior price synchronization, reduced slippage, and improved returns due to XRPL's lower fees and shorter block times, with benefits amplifying during market volatility. The integrated Continuous Auction Mechanism (CAM) further mitigates impermanent loss by redistributing arbitrage value to Liquidity Providers (LPs). To the best of our knowledge, this study represents the first comparative analysis between protocol-level and smart contract AMM-based DEX implementations and the first agent-based simulation validating theoretical auction mechanisms for AMM-based DEXs.

cs.CE↗

arXiv2023

Evolution of ESG-focused DLT Research: An NLP Analysis of the Literature

Distributed Ledger Technology (DLT) faces increasing environmental scrutiny, particularly concerning the energy consumption of the Proof of Work (PoW) consensus mechanism and broader Environmental, Social, and Governance (ESG) issues. However, existing systematic literature reviews of DLT rely on limited analyses of citations, abstracts, and keywords, failing to fully capture the field's complexity and ESG concerns. We address these challenges by analyzing the full text of 24,539 publications using Natural Language Processing (NLP) with our manually labeled Named Entity Recognition (NER) dataset of 39,427 entities for DLT. This methodology identified 505 key publications at the DLT/ESG intersection, enabling comprehensive domain analysis. Our combined NLP and temporal graph analysis reveals critical trends in DLT evolution and ESG impacts, including cryptography and peer-to-peer networks research's foundational influence, Bitcoin's persistent impact on research and environmental concerns (a "Lindy effect"), Ethereum's catalytic role on Proof of Stake (PoS) and smart contract adoption, and the industry's progressive shift toward energy-efficient consensus mechanisms. Our contributions include the first DLT-specific NER dataset addressing the scarcity of high-quality labeled NLP data in blockchain research, a methodology integrating NLP and temporal graph analysis for large-scale interdisciplinary literature reviews, and the first NLP-driven literature review focusing on DLT's ESG aspects.

cs.IR↗

arXiv2023

REA, Triple-Entry Accounting and Blockchain: Converging Paths to Shared Ledger Systems

The concept of shared ledger systems offering a single source of truth has repeatedly called traditional bookkeeping into question. Improving upon the long-standing double-entry system, solutions such as the Resource-Event-Agent (REA) accounting framework, triple-entry accounting (TEA) and blockchain have been advanced. However, to date, the historical development of these concepts remains murky. This paper conducts a genealogical analysis of shared ledger systems, in particular tracing the development of REA, TEA and blockchain. We show how the REA framework has had a distinct influence on independent streams of research in the field of TEA, and how this interaction may be traced to the present incarnation of shared ledger systems in blockchain. In doing so, we duly acknowledge the influence of key individuals contributing to this development, correct common misconceptions and map out how the paths of REA, TEA and blockchain overlap in the realm of shared ledger systems.

cs.CY↗

arXiv2022

The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work

Popular distributed ledger technology (DLT) systems using proof-of-work (PoW) for Sybil attack resistance have extreme energy requirements, drawing stern criticism from academia, businesses, and the media. DLT systems building on alternative consensus mechanisms, foremost proof-of-stake (PoS), aim to address this downside. In this paper, we take a first step towards comparing the energy requirements of such systems to understand whether they achieve this goal equally well. While multiple studies have been undertaken that analyze the energy demands of individual Blockchains, little comparative work has been done. We approach this research question by formalizing a basic consumption model for PoS blockchains. Applying this model to six archetypal blockchains generates three main findings: First, we confirm the concerns around the energy footprint of PoW by showing that Bitcoin's energy consumption exceeds the energy consumption of all PoS-based systems analyzed by at least three orders of magnitude. Second, we illustrate that there are significant differences in energy consumption among the PoSbased systems analyzed, with permissionless systems having an overall larger energy footprint. Third, we point out that the type of hardware that validators use has a considerable impact on whether PoS blockchains' energy consumption is comparable with or considerably larger than that of centralized, non-DLT systems.

cs.DC↗

arXiv2021

Stochastic modelling of blockchain consensus

Blockchain and general purpose distributed ledgers are foundational technologies which bring significant innovation in the infrastructures and other underpinnings of our socio-economic systems. These P2P technologies are able to securely diffuse information within and across networks, without need for trustees or central authorities to enforce consensus. In this contribution, we propose a minimalistic stochastic model to understand the dynamics of blockchain-based consensus. By leveraging on random-walk theory, we model block propagation delay on different network topologies and provide a classification of blockchain systems in terms of two emergent properties. Firstly, we identify two performing regimes: a functional regime corresponding to an optimal system function; and a non-functional regime characterised by a congested or branched state of sub-optimal blockchains. Secondly, we discover a phase transition during the emergence of consensus and numerically investigate the corresponding critical point. Our results provide important insights into the consensus mechanism and sub-optimal states in decentralised systems.

cs.DC↗

arXiv2021

A Digital Currency Architecture for Privacy and Owner-Custodianship

In recent years, electronic retail payment mechanisms, especially e-commerce and card payments at the point of sale, have increasingly replaced cash in many developed countries. As a result, societies are losing a critical public retail payment option, and retail consumers are losing important rights associated with using cash. To address this concern, we propose an approach to digital currency that would allow people without banking relationships to transact electronically and privately, including both internet purchases and point-of-sale purchases that are required to be cashless. Our proposal introduces a government-backed, privately-operated digital currency infrastructure to ensure that every transaction is registered by a bank or money services business, and it relies upon non-custodial wallets backed by privacy-enhancing technology such as blind signatures or zero-knowledge proofs to ensure that transaction counterparties are not revealed. Our approach to digital currency can also facilitate more efficient and transparent clearing, settlement, and management of systemic risk. We argue that our system can restore and preserve the salient features of cash, including privacy, owner-custodianship, fungibility, and accessibility, while also preserving fractional reserve banking and the existing two-tiered banking system. We also show that it is possible to introduce regulation of digital currency transactions involving non-custodial wallets that unconditionally protect the privacy of end-users.

cs.CY↗

arXiv2021

Triple-entry Accounting, Blockchain and Next of Kin: Towards a Standardisation of Ledger Terminology

Triple-entry accounting (TEA) is simultaneously a novel application in the blockchain universe and one of the many concepts applied in blockchain technology. Its Wild Wild West status is accompanied by a lack of consistent and comprehensive set of categories, a state of play that impedes a proper apprehension of the technology, leading to contradictions and oversight of important nuances. To clearly delineate the confines of TEA within the world of blockchain, we provide building blocks to standardise its terminology. Particularly, we distinguish between essential elements such as accounting and bookkeeping, as well as between decentralised systems, distributed ledgers and distributed journals.

cs.CR↗

arXiv2020

An Analysis of Blockchain Adoption in Supply Chains Between 2010 and 2020

In this research, the evolution of Distributed Ledger Technology (DLT) in supply chains has been mapped from the inception of the technology until June 2020, utilising primarily public data sources. Two hundred seventy-one blockchain projects operating in the supply chain have been analysed on parameters such as their inception dates, types of blockchain, stages reached, sectors applied to and type of organisation that founded the project. We confirm generally understood trends in the blockchain market with the creation of projects following the general hype and funding levels in the industry. We observe most activity in the Agriculture/Grocery sector and the Freight/Logistics sector. We see the shift of market interest from primarily private companies (startups) to public companies and consortia and the change in blockchain adoption from Ethereum to Hyperledger. Finally, we observe higher success and lower failure rates for Hyperledger-based projects in comparison to Ethereum-based projects.

cs.CY↗

arXiv2020

Digital Currency and Economic Crises: Helping States Respond

The current crisis, at the time of writing, has had a profound impact on the financial world, introducing the need for creative approaches to revitalising the economy at the micro level as well as the macro level. In this informal analysis and design proposal, we describe how infrastructure for digital assets can serve as a useful monetary and fiscal policy tool and an enabler of existing tools in the future, particularly during crises, while aligning the trajectory of financial technology innovation toward a brighter future. We propose an approach to digital currency that would allow people without banking relationships to transact electronically and privately, including both internet purchases and point-of-sale purchases that are required to be cashless. We also propose an approach to digital currency that would allow for more efficient and transparent clearing and settlement, implementation of monetary and fiscal policy, and management of systemic risk. The digital currency could be implemented as central bank digital currency (CBDC), or it could be issued by the government and collateralised by public funds or Treasury assets. Our proposed architecture allows both manifestations and would be operated by banks and other money services businesses, operating within a framework overseen by government regulators. We argue that now is the time for action to undertake development of such a system, not only because of the current crisis but also in anticipation of future crises resulting from geopolitical risks, the continued globalisation of the digital economy, and the changing value and risks that technology brings.

cs.CY↗