Crypto

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. ...

Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis ArXiv ID: 2305.13123 “View on arXiv” Authors: Unknown Abstract We are interested in the nonparametric estimation of the probability density of price returns, using the kernel approach. The output of the method heavily relies on the selection of a bandwidth parameter. Many selection methods have been proposed in the statistical literature. We put forward an alternative selection method based on a criterion coming from information theory and from the physics of complex systems: the bandwidth to be selected maximizes a new measure of complexity, with the aim of avoiding both overfitting and underfitting. We review existing methods of bandwidth selection and show that they lead to contradictory conclusions regarding the complexity of the probability distribution of price returns. This has also some striking consequences in the evaluation of the relevance of the efficient market hypothesis. We apply these methods to real financial data, focusing on the Bitcoin. ...

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"];