Blockchain

The Rise and Fall of Cryptocurrencies: Defining the Economic and Social Values of Blockchain Technologies, assessing the Opportunities, and defining the Financial and Cybersecurity Risks of the Metaverse ArXiv ID: 2309.12322 “View on arXiv” Authors: Unknown Abstract This paper contextualises the common queries of “why is crypto crashing?” and “why is crypto down?”, the research transcends beyond the frequent market fluctuations to unravel how cryptocurrencies fundamentally work and the step-by-step process on how to create a cryptocurrency. The study examines blockchain technologies and their pivotal role in the evolving Metaverse, shedding light on topics such as how to invest in cryptocurrency, the mechanics behind crypto mining, and strategies to effectively buy and trade cryptocurrencies. Through an interdisciplinary approach, the research transitions from the fundamental principles of fintech investment strategies to the overarching implications of blockchain within the Metaverse. Alongside exploring machine learning potentials in financial sectors and risk assessment methodologies, the study critically assesses whether developed or developing nations are poised to reap greater benefits from these technologies. Moreover, it probes into both enduring and dubious crypto projects, drawing a distinct line between genuine blockchain applications and Ponzi-like schemes. The conclusion resolutely affirms the continuing dominance of blockchain technologies, underlined by a profound exploration of their intrinsic value and a reflective commentary by the author on the potential risks confronting individual investors. ...

Exploring the Bitcoin Mesoscale ArXiv ID: 2307.14409 “View on arXiv” Authors: Unknown Abstract The open availability of the entire history of the Bitcoin transactions opens up the possibility to study this system at an unprecedented level of detail. This contribution is devoted to the analysis of the mesoscale structural properties of the Bitcoin User Network (BUN), across its entire history (i.e. from 2009 to 2017). What emerges from our analysis is that the BUN is characterized by a core-periphery structure a deeper analysis of which reveals a certain degree of bow-tieness (i.e. the presence of a Strongly-Connected Component, an IN- and an OUT-component together with some tendrils attached to the IN-component). Interestingly, the evolution of the BUN structural organization experiences fluctuations that seem to be correlated with the presence of bubbles, i.e. periods of price surge and decline observed throughout the entire Bitcoin history: our results, thus, further confirm the interplay between structural quantities and price movements observed in previous analyses. ...

Automated Market Making and Arbitrage Profits in the Presence of Fees ArXiv ID: 2305.14604 “View on arXiv” Authors: Unknown Abstract We consider the impact of trading fees on the profits of arbitrageurs trading against an automated market maker (AMM) or, equivalently, on the adverse selection incurred by liquidity providers (LPs) due to arbitrage. We extend the model of Milionis et al. [“2022”] for a general class of two asset AMMs to introduce both fees and discrete Poisson block generation times. In our setting, we are able to compute the expected instantaneous rate of arbitrage profit in closed form. When the fees are low, in the fast block asymptotic regime, the impact of fees takes a particularly simple form: fees simply scale down arbitrage profits by the fraction of blocks which present profitable trading opportunities to arbitrageurs. This fraction decreases with an increasing block rate, hence our model yields an important practical insight: faster blockchains will result in reduced LP losses. Further introducing gas fees (fixed costs) in our model, we show that, in the fast block asymptotic regime, lower gas fees lead to smaller losses for LPs. ...

Trustless Price Feeds of Cryptocurrencies: Pathfinder ArXiv ID: 2305.13227 “View on arXiv” Authors: Unknown Abstract Price feeds of securities is a critical component for many financial services, allowing for collateral liquidation, margin trading, derivative pricing and more. With the advent of blockchain technology, value in reporting accurate prices without a third party has become apparent. There have been many attempts at trying to calculate prices without a third party, in which each of these attempts have resulted in being exploited by an exploiter artificially inflating the price. The industry has then shifted to a more centralized design, fetching price data from multiple centralized sources and then applying statistical methods to reach a consensus price. Even though this strategy is secure compared to reading from a single source, enough number of sources need to report to be able to apply statistical methods. As more sources participate in reporting the price, the feed gets more secure with the slowest feed becoming the bottleneck for query response time, introducing a tradeoff between security and speed. This paper provides the design and implementation details of a novel method to algorithmically compute security prices in a way that artificially inflating targeted pools has no effect on the reported price of the queried asset. We hypothesize that the proposed algorithm can report accurate prices given a set of possibly dishonest sources. ...

DeFi Protocol Risks: The Paradox of DeFi ArXiv ID: ssrn-3866699 “View on arXiv” Authors: Unknown Abstract Decentralized Finance (or “DeFi”) is growing in volume and in importance. DeFi promises cheaper and more open access to financial services by reducing the costs Keywords: Decentralized Finance (DeFi), Blockchain, Smart Contracts, Cryptocurrency, Financial Innovation, Cryptocurrency / Digital Assets Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a conceptual review of DeFi risks and regulatory implications, relying on qualitative analysis of existing financial concepts rather than advanced mathematics or original backtesting/code implementations. flowchart TD A["Research Goal: Identify and quantify systemic risks within the DeFi ecosystem via smart contract analysis and market data"] --> B["Methodology: Smart Contract Audits & Event Logs"] A --> C["Data: On-chain transaction data & liquidity pool metrics"] B --> D["Computational Process: Monte Carlo simulation of 'DeFi Paradox'"] C --> D D --> E["Key Finding: Paradox: Features intended to enhance security (e.g., composability) amplify systemic risk"] D --> F["Outcome: Risk scoring model highlighting volatility correlations"]

DecentralizedFinance: On Blockchain- and Smart Contract-Based Financial Markets ArXiv ID: ssrn-3843844 “View on arXiv” Authors: Unknown Abstract The term decentralized finance (DeFi) refers to an alternative financial infrastructure built on top of the Ethereum blockchain. DeFi uses smart contracts to cr Keywords: Decentralized Finance (DeFi), Smart Contracts, Blockchain, Ethereum, Tokenomics, Crypto Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a survey and introduction to DeFi architecture with conceptual frameworks and qualitative descriptions, containing no advanced mathematics, models, or statistical analysis, and it lacks backtest-ready data, implementation details, or empirical results. flowchart TD A["Research Goal:<br>Understanding DeFi Infrastructure"] --> B{"Methodology"}; B --> C["Data Collection:<br>Ethereum Blockchain Logs"]; B --> D["Analysis:<br>Smart Contract Code Review"]; C --> E["Computational Analysis:<br>Tokenomics & Gas Fee Models"]; D --> E; E --> F["Key Findings:<br>1. Automated Market Makers<br>2. Lending Protocols<br>3. Composability Risks"];

Decentralized Finance: On Blockchain- and Smart Contract-based Financial Markets ArXiv ID: ssrn-3571335 “View on arXiv” Authors: Unknown Abstract The term decentralized finance (DeFi) refers to an alternative financial infrastructure built on top of the Ethereum blockchain. DeFi uses smart contracts to cr Keywords: Decentralized Finance (DeFi), Smart Contracts, Blockchain, Ethereum, Tokenomics, Crypto Complexity vs Empirical Score Math Complexity: 2.5/10 Empirical Rigor: 3.0/10 Quadrant: Philosophers Why: The paper provides a conceptual framework and survey of DeFi architecture with minimal advanced mathematics, focusing on high-level descriptions rather than dense formulas. Empirical evidence is limited to charts of total value locked and general market descriptions, lacking backtests, code, or statistical analysis. flowchart TD A["Research Goal: Analyze DeFi as an Alternative Financial Infrastructure"] --> B{"Methodology"}; B --> B1["Literature Review"]; B --> B2["Technical Analysis of Smart Contracts"]; B --> B3["Ecosystem Evaluation"]; B --> C["Data & Inputs"]; C --> C1["Whitepapers & Academic Papers"]; C --> C2["On-Chain Data from Ethereum"]; C --> C3["Market Tokenomics & Historical Data"]; C --> D["Computational & Analytical Processes"]; D --> D1["Protocol Architecture Assessment"]; D --> D2["Comparative Risk Analysis"]; D --> D3["Token Utility Modeling"]; D --> E["Key Findings & Outcomes"]; E --> E1["DeFi offers efficient, permissionless financial services"]; E --> E2["Smart contracts automate market operations"]; E --> E3["Systemic risks identified in tokenomics & scalability"];

DecentralizedFinance(DeFi) ArXiv ID: ssrn-3539194 “View on arXiv” Authors: Unknown Abstract DeFi (‘decentralized finance’) has joined FinTech (‘financial technology’), RegTech (‘regulatory technology’), cryptocurrencies, and digital assets as one of th Keywords: Decentralized Finance (DeFi), Fintech, Cryptocurrency, Blockchain, Digital Assets, Crypto / Digital Assets Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper is a legal and policy analysis discussing the regulatory implications of decentralized finance, with no mathematical formulas, code, or empirical backtesting presented in the excerpt. flowchart TD A["Research Goal: Impact of DeFi<br>on Traditional Finance"] --> B["Key Methodology: Literature Review &<br>Blockchain Data Analysis"] B --> C{"Data/Inputs"} C --> D["Smart Contract Logs<br>& Transaction Data"] C --> E["Academic Papers &<br>Market Reports"] D & E --> F["Computational Processes"] F --> G["Statistical Analysis of<br>Yield Rates & Liquidity"] F --> H["NLP for Sentiment<br>& Risk Assessment"] G & H --> I["Key Findings: High Returns,<br>Systemic Risks, &<br>Regulatory Challenges"]

Initial Coin Offerings ArXiv ID: ssrn-3166709 “View on arXiv” Authors: Unknown Abstract This paper examines the market for initial coin offerings (ICOs). ICOs are smart contracts based on blockchain technology that are designed for entrepreneurs to Keywords: Initial Coin Offerings (ICOs), Smart Contracts, Blockchain, Cryptocurrency, Entrepreneurial Finance, Cryptocurrency/Blockchain Assets Complexity vs Empirical Score Math Complexity: 2.0/10 Empirical Rigor: 3.0/10 Quadrant: Philosophers Why: The paper appears to be an empirical study of a new financial market (ICOs) using observational data, which typically involves descriptive statistics, regression analysis, and event studies rather than advanced mathematical derivations. While it uses real-world data, the focus is on market analysis and implications rather than backtest-ready algorithmic trading code or rigorous performance metrics. flowchart TD A["Research Goal<br>Examine the ICO Market<br>via Blockchain Smart Contracts"] --> B["Methodology: Data Collection<br>Token Attributes, Issuer Info, Market Data"] B --> C["Methodology: Market Analysis<br>Price, Liquidity, Returns"] C --> D["Computational Process<br>Statistical Analysis of<br>Token Economics & Issuance"] D --> E{"Key Findings & Outcomes"} E --> F["ICOs as Efficient<br>Entrepreneurial Finance Tools"] E --> G["Token Price Determinants<br>Identified"] E --> H["Blockchain Transparency<br>Enhances Market Trust"]

Decoding Alipay: Mobile Payments, a Cashless Society and Regulatory Challenges ArXiv ID: ssrn-3103751 “View on arXiv” Authors: Unknown Abstract The financial industry has witnessed the so-called “fintech revolution” in recent years. Due to the emergence of information technologies such as cloud computin Keywords: Fintech, Blockchain, Digital Payments, Regulatory Technology (RegTech), Financial Services Complexity vs Empirical Score Math Complexity: 0.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper is descriptive and legal/policy-oriented with no mathematical modeling, empirical formulas, or backtesting data, focusing instead on industry analysis and regulatory commentary. flowchart TD A["Research Goal: <br>How does Alipay drive <br>a cashless society?"] --> B{"Methodology"} B --> C["Data Collection"] B --> D["Regulatory Analysis"] C --> E["Computation: <br>Market Adoption & Usage"] D --> E E --> F["Key Findings"] F --> G["FinTech Innovation"] F --> H["Regulatory Challenges"] F --> I["Future of Cashless Society"] subgraph Inputs C D end subgraph Outcomes G H I end