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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,786 papers · 148 categories

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371013 · Jan 202619922001200920172026
48 results for Settlement Infrastructure

The study examines how modernizing settlement infrastructure affects inside money elasticity and network efficiency.

problem Understanding the impact of modernizing settlement infrastructure on inside money elasticity and network efficiency.
method Constructed a panel dataset of 809 reform events across 24 advanced economies, decomposed into economic channels and phases, and used a T2S event-study and synthetic control method.
result Modernizing settlement infrastructure generates network-conditional balance sheet efficiencies, with an estimated +13.4 percent efficiency recovery from 2027-2032.

Paper introduces Cycles Protocol to integrate trade credit into market clearing.

problem Liquidity embedded in trade credit outside formal settlement infrastructures.
method Distributed, multilateral clearing mechanism based on double-entry accounting.
result Cycles Protocol maximizes balance sheet compression without redistributing counterparty risk.

Agent-to-agent finance aims to manage payments and trust for AI agents.

problem Managing financial interactions between autonomous AI agents.
method Develops agent-to-agent finance concept and explores blockchain solutions.
result Agent-to-agent finance can address coordination frictions in financial markets.

This study categorizes RWA tokenization challenges and solutions.

problem Navigating the gap between on-chain deterministic code and off-chain probabilistic reality.
method Taxonomy and comparative analysis of RWA protocols, legal and technical standards.
result RWA tokenization requires overcoming legal and technical interoperability issues.

Detecting and mapping informal settlements encompasses several of the United Nations sustainable development goals. This is because informal settlements are home to the most socially and economically vulnerable people on the planet. Thus, understanding where these settlements are is of paramount importance to both gove…

2018-11-30abs ↗pdf ↗

This study reviews decentralized prediction markets, identifying key design variants and open problems.

problem Designing and implementing decentralized prediction markets with desirable properties.
method Modular workflow comprising eight stages: infrastructure, market topic, share structure, pricing, market initialization, trading, resolution, settlement, and archiving. Analysis of design variants and trade-offs.
result Identification of open problems for researchers in the field of decentralized prediction markets.

Prediction markets can be manipulated by traders who can move contract settlements, harming price discovery.

problem Manipulation of settlement times in prediction markets leads to unfair wealth transfer and harms price discovery.
method Developed a model showing how settlement manipulation transfers wealth and harms price discovery, and observed real-world effects on Polymarket's Bitcoin contract.
result Manipulators capture significant profits from retail traders, especially when settlement times are short.

The study analyzes how bonus-malus systems and delayed claims settlement affect insurance companies' financial stability.

problem Analyzing the impact of bonus-malus systems and delayed claims settlement on insurance companies' financial stability.
method Examined a discrete-time risk model with time-varying premiums, evaluating two types of claims and settlement delays.
result Delayed settlement of by-claims leads to lower ruin probabilities under specific assumptions.

PredictionMarketBench benchmarks trading agents on prediction markets.

problem Evaluating trading agents on prediction markets with realistic conditions.
method Deterministic replay of historical data, execution-realistic simulator, agent interface.
result Fee-aware algorithmic strategies outperform naive agents in volatile episodes.

Study cash-flow forecasting for derivatives, aligning with replication strategy and addressing timing frictions.

problem Inconsistencies in cash-flow forecasting under different measures and stochastic payment times.
method Use discounting sensitivities (funding-curve hedge ratios) for replication and propose a liquidity valuation adjustment.
result Aligns forecasting with replication strategy and avoids measure-mixing issues.

In his book with Alan Jolis, Vers un monde sans pauvreté (1997) Yunus gives the example of a microcredit loan of 1000BDT reimbursed via 50 weekly settlements of 22BDT and correctly claims that this corresponds to the annual interest rate of 20%. But this is without taking into account that if the borrower has good reas…

2013-12-08abs ↗pdf ↗

VTrackIt creates a synthetic dataset with infrastructure and vehicle info for AVs.

problem Lack of infrastructure and pooled vehicle info in existing AV datasets.
method Developed VTrackIt, a synthetic dataset with intelligent infrastructure and pooled vehicle info, and introduced InfraGAN for trajectory predictions.
result VTrackIt reduces high-risk edge cases in AV trajectory predictions.

This paper uses a mean-field game to model stablecoin market dynamics and recovery.

problem Understanding who restores the peg during de-pegging events of stablecoins.
method Dynamic, agent-based mean-field game framework for fiat-collateralized stablecoins.
result The equilibrium formulation endogenously maps market frictions into a price path and order flows, allowing for stress testing and attribution of peg-reverting pressure.

Cryptocurrency markets show similar returns but different volatility responses to infrastructure and regulatory shocks.

problem Understanding how cryptocurrency markets differentiate between infrastructure and regulatory shocks.
method Event-level block bootstrap inference on 31 cryptocurrency events across Bitcoin, Ethereum, Solana, and Cardano (2019-2025).
result No statistically significant difference in cumulative abnormal returns between infrastructure failures and regulatory enforcement.

Hybrid framework predicts Arctic permafrost decline, risks infrastructure, and provides tools.

problem Tackles permafrost decline and infrastructure risk assessment in Arctic territories.
method Hybrid physics-machine learning framework integrating 2.9 million observations.
result Projects mean permafrost fraction decline of -20.3 pp under RCP8.5 forcing, with high-risk zones identified.

This study analyzes dynamic connectedness in global supply chain infrastructure portfolios, identifying key risk factors and extreme events.

problem Understanding dynamic connectedness in global supply chain infrastructure portfolios under various risk factors and extreme events.
method Time-varying parameter vector autoregression (TVP-VAR) model to study spillover and interconnectedness of risk factors.
result Risk shocks influence dynamic connectedness between portfolios and risk factors, and extreme events affect investment outcomes.

Research quantifies financial exclusion risks in UK, focusing on cash infrastructure and socio-economic factors.

problem Localised financial exclusion in the UK as cash infrastructure declines.
method Developed a composite indicator using various input variables.
result Financial exclusion is more prevalent in deprived communities and affluent areas.

Fragmented exchanges arise due to speed advantages in high-activity regions.

problem Fragmentation of distributed securities exchanges due to speed advantages in high-activity regions.
method Economic model and Monte Carlo simulations of a decentralized exchange with two miner clusters.
result Speed advantage increases with infrastructure asymmetry between regions.

Infrastructure monitors AI/ML radiology models across multiple sites.

problem Monitoring and improving AI/ML radiology models across multiple sites.
method Interactive radiology reporting, centralized cloud system, post-marketing surveillance.
result Efficient monitoring and iterative development of AI/ML models without radiologist burden.

Automated road infrastructure mapping using connected vehicle data and deep learning.

problem Manual identification of intersections is laborious and time-consuming.
method Geohashing, YOLOv5 algorithm for classification of road segments and intersections.
result Overall classification accuracy of 95%, with high F1 scores for straight roads and intersections.

Methodology measures financial impacts using existing credit loss infrastructure.

problem Measuring the impact of financial scenarios on expected credit losses.
method Captures scenario effects through changes in default probabilities; uses existing provisioning infrastructure.
result Methodology validated through standardized climate scenario exercise in Canada and Quebec.

Develops a framework to assess infrastructure reliability under natural and malicious events.

problem Assessing reliability and costs of infrastructure under various hazards.
method Coupling mechanical reliability analyses with economical reliability analyses using probabilistic considerations.
result Indicators of probable cost of failure for infrastructure, aiding safety investments.

Develop gradient boosting for estimating covariate-dependent GP distributions in insurance.

problem Estimating covariate-dependent Generalized Pareto distributions in insurance.
method Developing a statistical learning theory for gradient boosting.
result Deriving non-asymptotic error bounds for the boosting estimator.

Proposes a multi-objective variational autoencoder for smart infrastructure damage detection.

problem Detecting and diagnosing damage in smart infrastructure using multi-way data.
method Multi-objective variational autoencoder (MVA) method for smart infrastructure damage detection and diagnosis.
result The method accurately detects structural damage, estimates severity, and captures damage locations.