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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., Comment: 16 pages, 3 figures, 4 tables

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.

Total value locked (TVL) is widely used to measure the size and popularity of decentralized finance (DeFi). However, the prevalent TVL calculation framework suffers from a "double counting" issue that results in an inflated metric. We find existing methodologies addressing double counting either inconsistent or flawed. To solve this, we formalize the TVL framework and propose a new framework, total value redeemable (TVR), to accurately assess the true value within DeFi. TVL formalization reveals how DeFi's complex network spreads financial contagion via derivative tokens, amplifying liquidations and stablecoin depegging in market downturns. We construct the DeFi multiplier to quantify the double counting, which mirrors the money multiplier in traditional finance (TradFi). Our measurement finds substantial double counting in DeFi. During the peak of DeFi activity on December 2, 2021, the difference between TVL and TVR was \$139.87 billion, with a TVL-to-TVR ratio of about 2. We further show that TVR is a more stable metric than TVL, 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. We also observe a substitution effect between TradFi and DeFi.

Decentralized Finance (DeFi) has emerged as a transformative force in the financial sector, with Automated Market Makers (AMMs) playing a crucial role in facilitating asset exchange and liquidity provision. However, most AMMs operate on the Ethereum blockchain and face challenges such as high transaction fees and price synchronization issues mainly due to Ethereum scalability issues. This paper addresses these limitations by investigating the performance of an Automated Market Maker (AMM) integrated at the protocol level of the XRP Ledger. Using game-theoretic simulations, we compared the XRPL-AMM to a Generic CPMM-based AMM (G-AMM) on Ethereum, akin to established players like Uniswap's V2 AMM implementation. The results demonstrate that the XRPL-AMM outperforms in terms of price synchronization with external markets, lower slippage, reduced impermanent loss, and improved returns for liquidity providers, particularly under volatile market conditions. The unique Continuous Auction Mechanism (CAM) of the XRPL-AMM further enhances its efficiency by incentivizing beneficial arbitrage. These findings highlight the potential of protocol-level AMM integration. To the best of our knowledge, the XRPL-AMM is one of the first AMMs built directly at the protocol level of a blockchain. Therefore, this inaugural study ventures into the unexplored domain of evaluating AMMs with protocol-level integration compared to traditional smart contracts implementations.

As Distributed Ledger Technologies (DLTs) rapidly evolve, their impacts extend beyond technology, influencing environmental and societal aspects. This evolution has increased publications, making manual literature analysis increasingly challenging. We address this with a Natural Language Processing (NLP)-based systematic literature review method to explore the intersection of Distributed Ledger Technology (DLT) with its Environmental, Social, and Governance (ESG) aspects. Our approach involves building and refining a directed citation network from 107 seed papers to a corpus of 24,539 publications and fine-tuning a transformer-based language model for Named Entity Recognition (NER) on DLT and ESG domains. Applying this model, we distilled the corpus to 505 key publications, enabling an inaugural literature review and temporal graph analysis of DLT's evolution in ESG contexts. Our contributions include an adaptable and scalable NLP-driven systematic literature review methodology and a unique NER dataset of 54,808 entities, tailored for DLT and ESG research. Our inaugural literature review demonstrates their applicability and effectiveness in analyzing DLT's evolution and impacts, proving invaluable for stakeholders in the DLT domain.

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.

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.

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., Comment: 24 pages, 6 figures, 1 table. arXiv admin note: substantial text overlap with arXiv:2006.03023

Triple-entry accounting (TEA) is one of the novelest notions in the blockchain world. However, the lack of a consistent and comprehensive set of categories to give account of it impedes a proper apprehension of the concept, leading to contradictions and to overlooking its specificity. In order to clearly delineate the confines of TEA, we create a typology to distinguish between essential elements such as accounting and bookkeeping, as well as between decentralized systems, distributed ledgers and distributed journals.

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., Comment: 20 pages, 11 figures, 6 tables

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., Comment: 32 pages, 6 figures, 1 table

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., Comment: 73 pages, 5 figures

A comparative study across the most widely known blockchain technologies is conducted with a bottom-up approach. Blockchains are disentangled into building blocks. Each building block is then hierarchically classified in main and subcomponents. Then, alternative layouts for the subcomponents are identified and compared between them. Finally, a taxonomy tree summarises the study and provides a navigation tool across different blockchain architectural configurations., Comment: 43 pages, 1 figure

Systemic risk in banking systems remains a crucial issue that it has not been completely understood. In our toy model, banks are exposed to two sources of risks, namely, market risk from their investments in assets external to the banking system and credit risk from their lending in the interbank market. By and large, both risks increase during severe financial turmoil. Under this scenario, the paper shows the conditions under which both the individual and the systemic default tend to coincide., Comment: 26 pages, 35 figures, 21st Computing in Economics and Finance (CEF2015)

Excessive leverage, i.e. the abuse of debt financing, is considered one of the primary factors in the default of financial institutions. Systemic risk results from correlations between individual default probabilities that cannot be considered independent. Based on the structural framework by Merton (1974), we discuss a model in which these correlations arise from overlaps in banks' portfolios. Portfolio diversification is used as a strategy to mitigate losses from investments in risky projects. We calculate an optimal level of diversification that has to be reached for a given level of excessive leverage to still mitigate an increase in systemic risk. In our model, this optimal diversification further depends on the market size and the market conditions (e.g. volatility). It allows to distinguish between a safe regime, in which excessive leverage does not result in an increase of systemic risk, and a risky regime, in which excessive leverage cannot be mitigated leading to an increased systemic risk. Our results are of relevance for financial regulators.