Centralized exchanges influence staking behavior and decentralization in Proof of Stake blockchain ecosystems.
problem How do centralized exchanges affect staking behavior and decentralization in Proof of Stake blockchain ecosystems?
method Formulate a continuous-time mean field model of miners as validators and traders in a centralized market.
result Centralized trading activities enhance staking participation and promote decentralization through market incentives.
Optimal trading strategy in Proof-of-Stake blockchain using continuous-time control.
problem Finding the optimal balance between stake utility and consumption utility in Proof-of-Stake blockchain.
method Continuous-time control approach, dynamic programming, Hamilton-Jacobi-Bellman (HJB) equations.
result Close-form solutions for linear and convex utility functions, optimal strategies identified.
This paper explores leverage staking with stETH, revealing high returns but also significant risks.
problem Leverage staking introduces risks through intensified selling pressure and cascading liquidations.
method Formal framework for leverage staking, stress tests under extreme conditions of stETH devaluation.
result Leverage staking amplifies risks, leading to intensified selling pressure and price declines.
PoEL protocol aims to efficiently create and secure liquidity for blockchain networks.
problem Lack of sustainable liquidity and network security in Proof of Stake blockchains.
method PoEL uses staking rewards to attract risk capital, structuring incentives for capital efficiency and security.
result PoEL protocol enhances blockchain network security and liquidity sustainability.
New model assesses risks of staking and borrowing in smart contracts.
problem Security and efficiency of staking in smart contract platforms.
method Combines birth-death Pólya processes and credit derivatives models.
result Derivatives can reduce wealth concentration in staking networks.
Model shows PoS networks can be captured by external finance, leading to centralization.
problem Long-term centralization of PoS networks under external finance pressures.
method Heterogeneous macroeconomic model with two actor classes: investors and consumers.
result External finance forces PoS networks to centralize, leading to zero internal staking yield.
Model analyzes Proof-of-Stake network dynamics and speculative capital effects on token prices.
problem Understanding and managing price dynamics in Proof-of-Stake networks.
method Developed an open-economy macroeconomic model to analyze Proof-of-Stake dynamics and speculative capital effects.
result Speculative capital can shift staked-token ownership, potentially improving consensus decentralization.
Proof of Stake (PoS) is a burgeoning Sybil resistance mechanism that aims to have a digital asset ("token") serve as security collateral in crypto networks. However, PoS has so far eluded a comprehensive threat model that encompasses both Byzantine attacks from distributed systems and financial attacks that arise from …
The paper examines stability of shares in Proof of Stake protocol, identifying different investor behaviors and phase transitions.
problem Stability of shares in Proof of Stake protocol.
method Identification of large, medium, and small investors under various rewarding schemes; dynamical population model analysis.
result Phase transitions and thresholds for stability are characterized; chaotic centralization leads to concentration of shares.
Extends PoS proof-of-stake transaction fee mechanism with miner utility model.
problem Designing a transaction fee mechanism for PoS protocol that incorporates miner utility.
method Introduced a new mechanism (BSP(θ)) incorporating a parameter θ to ensure user and miner incentives.
result The new mechanism (BSP(θ)) satisfies user and miner incentives and contract proofness.
Study on wealth and trading in PoS blockchain.
problem Decentralization and trading incentives in PoS.
method Analytic and stochastic tools, optimal control theory, mean field model.
result Miners balance PoS mining and trading for optimal strategy.
Ethereum transition to PoS reduces energy consumption and decentralizes the network.
problem Transitioning from proof-of-work to proof-of-stake to reduce energy consumption and decentralize the network.
method Analyzed the impact of the Ethereum transition to proof-of-stake on network performance, competing platforms, and transaction fees.
result The transition to PoS has reduced energy consumption by 99.98% and decreased network concentration.
Proof-of-Stake networks with EIP-1559 exhibit stable token prices and secure network security.
problem Token valuation and institutional capital in Proof-of-Stake networks under EIP-1559
method Open-economy macroeconomic equilibrium model
result Stable steady-state equilibrium price for ETH
A new method for optimizing stakes in a single event with multiple outcomes.
problem Maximizing expected log wealth in a single event with multiple outcomes.
method Using implicit state positions to derive the optimal stake formula.
result A compact formula and greedy algorithm for support selection.
Research predicts cryptocurrency staking rewards with high accuracy.
problem Predicting cryptocurrency staking rewards.
method Two predictive methodologies: sliding-window average and linear regression models.
result ETH staking rewards can be forecasted with RMSE within 0.7% and 1.1% of the mean value for 1-day and 7-day look-aheads respectively.
Optimizes leveraged staking strategies in decentralized finance.
problem Maximizing returns on staked assets in decentralized lending platforms.
method Developed a mathematical framework to optimize leveraged staking strategies, reducing the multi-market problem to convex allocation over market exposures.
result Rebalanced leveraged positions can achieve up to 6.2% APY, significantly higher than unleveraged staking.
Ethereum's Pectra upgrade introduces 0x02 compounding validators, offering higher stake and potential APR uplifts.
problem Staking rewards on Ethereum
method Analyzing compounding effects on consensus-layer rewards
result 0x02 validators achieve modestly higher median CL APR
New tools found to create hyperbolic links with lower volume bounds.
problem Finding lower bounds on volumes of staked links.
method Defining charm bracelets and constructing hyperbolic links.
result Infinitely many hyperbolic staked links with lower volume bounds.
TRACER improves interpretability in high stakes analytics.
problem Interpreting complex models in high stakes applications.
method TRACER framework with TITV model for healthcare analytics.
result TRACER facilitates both accurate and interpretable analytics.
Optimal Kelly strategy for multi-outcome parlay bets proven using implicit cash approach.
problem Finding optimal Kelly stakes for multi-outcome parlay bets.
method Eventwise Kelly strategy followed by outer product for full menu of bets. Uses implicit cash viewpoint.
result Optimal Kelly stakes for parlay bets factorize across events, with active leg criterion.
The paper analyzes security issues in blockchain ecosystems with multiple SSPs and proposes two models for better stake management.
problem Security issues in blockchain ecosystems with multiple SSPs and stake fragmentation.
method Formalized the Multiple SSP Problem and analyzed two architectures: Model M and Model S through convex optimization and game-theoretic lens. result Model S achieves tighter security guarantees through single validator sets and aggregated slashing logic. Investors optimize liquid staking decisions in LSP and AMM protocols.
problem Optimal timing and allocation in liquid staking protocols.
method Derive optimal allocation strategy and model optimal exit timing using Laplace transforms and free-boundary techniques.
result Optimal stop-loss strategy maximizes expected payoff, influenced by fees and opportunity gains.
Black box machine learning models are currently being used for high stakes decision-making throughout society, causing problems throughout healthcare, criminal justice, and in other domains. People have hoped that creating methods for explaining these black box models will alleviate some of these problems, but trying t…
New framework assesses extreme errors in machine learning models.
problem Current validation methods fail to quantify extreme errors in high-stakes domains.
method Uses Extreme Value Theory (EVT) to estimate worst-case failures.
result Establishes EVT as a fundamental tool for assessing model reliability.
We study hyperbolic bongles and find their volumes.
problem Characterizing and quantifying hyperbolic bongles.
method Provided necessary and sufficient conditions for hyperbolicity, calculated volumes, and established upper bounds.
result All balanced hyperbolic n-bongles have the same volume and this volume is an upper bound for any hyperbolic n-bongle. The paper examines how algorithmic classification affects behavior and proposes democratizing stakes to mitigate predatory practices.
problem The impact of algorithmic classification on individual behavior and fairness in decision-making processes.
method Characterization of optimal classification by an algorithm designer and analysis of the effect of democratizing stakes.
result Optimal classification can lead to surprising behavior patterns, and democratizing stakes can mitigate predatory practices.
Fair active learning selects data points to balance model accuracy and fairness.
problem Ensuring fairness in machine learning models used in high-stakes applications.
method Designing algorithms for fair active learning that select data points to balance model accuracy and fairness, focusing on demographic parity.
result Demonstrated the effectiveness of the proposed fair active learning approach over benchmark datasets.
The study determines conditions for hyperbolicity of links in thickened surfaces with boundary.
problem Conditions for hyperbolicity of links in thickened surfaces with boundary.
method Simple conditions and embeddings of surfaces in ambient manifolds.
result Conditions guaranteeing hyperbolicity of links in thickened surfaces and fiber bundles.
Deep neural networks (DNNs) may outperform human brains in complex tasks, but the lack of transparency in their decision-making processes makes us question whether we could fully trust DNNs with high stakes problems. As DNNs' operations rely on a massive number of both parallel and sequential linear/nonlinear computati…
This study evaluates Algorand and Ethereum 2.0 for blockchain trilemma challenges.
problem Balancing decentralization, security, and scalability in blockchain systems.
method Comparative analysis of Algorand and Ethereum 2.0 using metrics for decentralization, scalability, and security.
result Each system has strengths in addressing the blockchain trilemma, providing insights for other blockchain technologies.
New framework controls statistical dispersion for high-stakes applications.
problem Understanding and controlling the dispersion of loss distributions in high-stakes applications.
method Simple yet flexible framework for distribution-free control of statistical dispersion measures.
result Proposed methods control statistical dispersion measures with societal implications.
A statistical test controls false positives in anomaly localization using diffusion models.
problem Uncertainty and bias in generative models for anomaly localization.
method Selective inference to quantify significance and control false positives.
result The method effectively controls false positive detection rates.
New digital currency aims for equal wealth distribution.
problem Inequality in cryptocurrency wealth distribution.
method Egalitarian coin minting and joint minting across communities.
result Achieves global distributive justice in wealth distribution.
Cryptofinance generates yield through innovative decentralized finance.
problem Lack of intrinsic yield in crypto-assets.
method Analysis of yield-generating mechanisms in cryptofinance.
result Cryptofinance innovations enable yield generation through various decentralized and centralised mechanisms.
Paper formalizes multi-dimensional FSD using geometric methods.
problem Complex measure theory and calculus barriers to formalization in proof assistants.
method Geometric framework for first-order stochastic dominance in N dimensions.
result Geometric approach bypasses complex integration theory for direct comparison of survival probabilities.
Paper proposes SCQ and P-TAMS for structured OOD testing in high-stakes ML.
problem Difficulty of incorporating auxiliary information in traditional conformal methods.
method Structure-adaptive conformal q-value (SCQ) and pseudo-score-guided transductive automated model selection (P-TAMS).
result Unified framework controls false discovery rate and improves power across diverse settings.
Novel AMM model for pegged cryptoassets using nested OU processes.
problem Liquidity and risk management in markets for pegged cryptoassets.
method Multi-level nested Ornstein-Uhlenbeck (OU) processes for exchange rate dynamics, calibrated and filtered AMM model.
result Consistent efficient quotes and improved liquidity provision for pegged cryptoassets.
Amazon SageMaker Model Monitor detects drift in deployed ML models.
problem Ensuring high performance of ML models in production environments.
method Automatically detects data, concept, bias, and feature attribution drift in real-time.
result Maintains high quality models by providing alerts and corrective actions.
The paper explores fairness metrics in automated decision-making and their limitations.
problem Discrimination in automated resource allocation decisions.
method Analysis of fairness metrics and distributive justice principles.
result Prominent fairness metrics fail to address egalitarian and sufficiency concerns in resource allocation.
SIRUS creates interpretable rules from random forests for regression.
problem Lack of interpretability in complex machine learning models.
method Random forest with rule extraction for stability and simplicity.
result SIRUS produces stable and interpretable rule sets.
Systematic review of conformal inference for treatment effect estimation.
problem Uncertainty quantification in treatment effect estimation.
method Conformal prediction methods for treatment effect estimation.
result Current state-of-the-art conformal prediction methods identified and described.
DeFi lending protocols faced challenges during Ethereum's merge, but avoided major liquidations.
problem Ethereum's merge caused volatility and potential liquidations in DeFi lending.
method Analyzed AAVE and Compound lending protocols during the merge and hard fork.
result Borrowing rates spiked but no significant liquidations occurred.
AI systems are being deployed to support human decision making in high-stakes domains. In many cases, the human and AI form a team, in which the human makes decisions after reviewing the AI's inferences. A successful partnership requires that the human develops insights into the performance of the AI system, including …
Framework for responsible LLM deployment with human involvement and decentralized technologies.
problem Challenges in deploying LLMs for high-stakes decisions, including data security and accountability.
method Interactive human involvement through multiple iterations, decentralized technologies, and automated auditing.
result Enhanced security and accountability in LLM deployment for financial decisions.
Fan tokens surged before World Cup matches, but declined during them, revealing cognitive biases.
problem Analyzing the impact of FIFA World Cup matches on fan tokens.
method Event study and intraday analysis of blockchain-based fan tokens.
result Fan tokens experienced a surge in returns six months before the World Cup, followed by a decline during the matches, revealing asymmetries in performance.
New voting strategies show committee-based consensus can scale efficiently.
problem Ensuring honest committees in committee-based consensus protocols.
method Empirical analysis of simpler voting strategies and their convergence to optimality.
result Simpler voting strategies converge to optimality exponentially quickly, ensuring robustness and efficiency.
Optimizes Ethena's yield strategy by controlling stETH and ETH futures positions.
problem Maximizes Ethena's yield while managing price impacts.
method Formulates and solves stochastic control problems for Ethena's yield-generating strategy.
result Explicitly determines optimal control rates for stETH and ETH futures.
Strategic feature selection in high-stakes domains like healthcare.
problem Strategic manipulation of input features in algorithmic predictors.
method Formal study of strategic classification through feature selection and ridge regularization.
result Excluding individual features based on manipulability is generally suboptimal.