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.
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.
Driven by the tremendous technological advancement of personal devices and the prevalence of wireless mobile network accesses, the world has witnessed an explosion in crowdsourced live streaming. Ensuring a better viewers quality of experience (QoE) is the key to maximize the audiences number and increase streaming pro…
Study analyzes factors affecting profits in crypto liquidity provision.
problem Liquidity providers lack guidance for developing profitable strategies.
method Developed a measurement model based on impermanent loss to analyze key parameters.
result Uncovered influences of key parameters on LPs' profits.
Meta-ensemble scheme allocates queries to EC nodes for reduced latency.
problem Efficiently allocating queries to EC nodes to minimize latency.
method Combining ensemble models to decide query allocation based on node and query characteristics.
result Meta-ensemble scheme outperforms traditional allocation methods in reducing query processing latency.
Study shows how to better estimate credit provisions and economic capital.
problem Estimating credit provisions and economic capital accurately.
method Using supermodularity ordering properties and elliptically distributed latent factors.
result Convex risk measures of credit losses are nondecreasing w.r.t. various covariances.
Optimizes liquidity provision in decentralized exchanges with utility indifference market makers.
problem Impermanent loss in decentralized exchanges without transaction fees.
method Mathematical formulation of liquidity provision, focusing on utility indifference market makers.
result No-arbitrage conditions and optimal arbitrage strategies are established.
Paper predicts international trade flows using machine learning and factorization models.
problem Predicting international bilateral trade flows with PTAs.
method Two-stage approach combining SHAP Explainer and Factorization Machine models.
result Enhanced predictive accuracy and deeper insights into trade dynamics.
Optimizes liquidity provision intervals for profitable AMM participation.
problem Financial losses from poor liquidity provision intervals and reallocation costs.
method Developed a tractable stochastic optimization problem.
result Computes optimal liquidity provision intervals for profitable liquidity concentration.
We calculate the dynamics of tax evasion within a multi-agent econophysics model which is adopted from the theory of magnetism and previously has been shown to capture the main characteristics from agent-based based models which build on the standard Allingham and Sandmo approach. In particular, we implement a feedback…
Network slicing promises to provision diversified services with distinct requirements in one infrastructure. Deep reinforcement learning (e.g., deep Q-learning, DQL) is assumed to be an appropriate algorithm to solve the demand-aware inter-slice resource management issue in network slicing by regarding the …
Paper optimizes liquidity provision in decentralized finance markets.
problem Strategic LPs face predictable losses and concentration risk in CL pools.
method Derive optimal liquidity provision strategy based on fees, PL, and concentration risk.
result Optimal strategy increases fee revenue and profit from marginal rate changes.
Tick-by-tick liquidity provision aims to maximize fees and reserves.
problem Maximizing fees and reserves in concentrated liquidity.
method Convex optimization for tick-level liquidity provision.
result Concentrating liquidity around current price is not always best.
The article provides formulas to hedge impermanent loss in decentralized markets.
problem Impermanent loss in concentrated liquidity provision in decentralized markets.
method Analytical characterizations and static replication formulas using European calls or puts.
result Static replication formulas accurately hedge impermanent loss.
The prevalent view in the economics literature is that a high level of infrastructure investment is a precursor to economic growth. China is especially held up as a model to emulate. Based on the largest dataset of its kind, this paper punctures the twin myths that, first, infrastructure creates economic value, and, se…
Paper analyzes pricing model for bonds with early redemption.
problem Analyzing pricing of bonds with early redemption features.
method Structural approach for mathematical modeling of bond prices.
result Existence and uniqueness of default and early redemption boundaries proved.
Proposes a graph neural network for traffic forecasting in WANs.
problem Traffic forecasting challenges in WANs due to dynamic and large data volumes.
method Dynamic diffusion convolutional recurrent neural networks for multistep traffic forecasting.
result Significant improvements in forecasting accuracy compared to classical methods.
This paper uses DRL to optimize liquidity in DeFi protocols, making markets more accessible.
problem Optimizing liquidity provisioning in decentralized finance protocols.
method Modeling liquidity provisioning as an MDP, training an agent with PPO to dynamically adjust positions.
result DRL-based strategy outperforms traditional heuristics in fee maximization and impermanent loss mitigation.
Study liquidity provision in decentralized exchanges considering risk aversion and replication costs.
problem Economic viability of liquidity provision in decentralized exchanges (DEXs).
method Formulated strategic interactions as a sequential game with risk-averse LP, traders, and arbitrageurs.
result DEX liquidity depth is crucial for risk management, influenced by risk aversion and replication costs.
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.
Study liquidity provision with exogenous competition using a reference market maker.
problem Liquidity provision in the presence of exogenous competition.
method Model a reference market maker who optimizes posted depths, competing market makers using a rule of thumb.
result Model admits approximate closed-form solution for a linear-quadratic goal functional.
Forward hedging reshapes incentive provision in firms.
problem How does forward hedging affect incentive provision in firms?
method We consider a CARA framework to jointly characterize optimal production, compensation, and static hedging in equilibrium.
result Delegation and external hedging are partial substitutes, and delegation can increase firm value even when the agent is more risk averse.
The Economist recently reported that infrastructure spending is the largest it is ever been as a share of world GDP. With $22 trillion in projected investments over the next ten years in emerging economies alone, the magazine calls it the "biggest investment boom in history." The efficiency of infrastructure planning a…
The UN Sustainable Development Goals allude to the importance of infrastructure quality in three of its seventeen goals. However, monitoring infrastructure quality in developing regions remains prohibitively expensive and impedes efforts to measure progress toward these goals. To this end, we investigate the use of wid…
Sunshine trading theory predicts lower execution costs and liquidity provision through explicit preannouncements, but evidence is scarce in traditional markets.
problem Adverse selection on liquidity provision
method Reconstructing metaorders and comparing them with visible TWAP executions
result Visible TWAPs face lower execution costs and leave a smaller permanent price impact compared to hidden metaorders.
The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequence is cost overruns, benefi…
Study on liquidity providers' performance in decentralized exchanges.
problem Unclear profitability of liquidity providers in decentralized exchanges.
method Reconstructing LP PnL dynamics from on-chain events, introducing a new metric.
result Only about one out of six LPs avoids losses, suggesting open questions about LP participation motives.
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.
Zero Emission Vehicles (ZEV) play an important role in the decarbonization of the transportation sector. For a wider adoption of ZEVs, providing a reliable infrastructure is critical. We present a machine learning approach that uses unsupervised temporal clustering algorithm along with survey analysis to determine infr…
Pricing Chinese convertible bonds using Monte Carlo simulation and dynamic programming.
problem Pricing Chinese convertible bonds accurately.
method Monte Carlo simulation and dynamic programming with regression and backward induction.
result An underpriced strategy significantly outperforms benchmarks.
A novel outlier score detects new road infrastructure images.
problem Detecting newly observed road infrastructure images.
method Entropy-based outlier score using directed nearest neighbor graphs.
result High potential of the proposed technique in identifying outliers.
Study scaling of optimal solutions for reliability constraints in resource provisioning.
problem Achieving high reliability in resource provisioning under stringent requirements.
method Chance-constrained optimization, distributionally robust optimization, f-divergence balls, line search.
result Correct scaling properties of optimal decisions are preserved by using appropriate f-divergence balls, leading to conservative yet near-optimal solutions.
We combine Bayesian networks (BNs) and structural reliability methods (SRMs) to create a new computational framework, termed enhanced Bayesian network (eBN), for reliability and risk analysis of engineering structures and infrastructure. BNs are efficient in representing and evaluating complex probabilistic dependence …
Natural disasters can have catastrophic impacts on the functionality of infrastructure systems and cause severe physical and socio-economic losses. Given budget constraints, it is crucial to optimize decisions regarding mitigation, preparedness, response, and recovery practices for these systems. This requires accurate…
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.
Traditional market makers are losing their importance as automated systems have largely assumed the role of liquidity provision in markets. We update the model of Glosten and Milgrom (1985) to analyze this new world: we add multiple securities and introduce an automated market maker who uses the relationships between s…
The paper develops a new framework for pricing and hedging liquidity in crypto markets.
problem Arbitrage and risk management in crypto market making.
method Developed a new mathematical framework using a coordinate system defined by price and intrinsic liquidity.
result Established a linear dependence of asset reserves and value functions on intrinsic liquidity, facilitating arbitrage-free pricing and delta hedging.
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.
IntraLayer connects digital finance platforms efficiently.
problem Inefficient interconnectivity in digital finance.
method Core infrastructure and adaptive fiscal policy.
result Optimised transactional efficiency for various agents.
This paper argues, first, that a major problem in the planning of large infrastructure projects is the high level of misinformation about costs and benefits that decision makers face in deciding whether to build, and the high risks such misinformation generates. Second, it explores the causes of misinformation and risk…
CFM fee income is insufficient to hedge market risk, study finds.
problem Inefficiency of CFM fee income in hedging market risk.
method Analysis through continuous-time financial mathematics and multi-agent simulations.
result Fee income is insufficient to compensate for market risk.
Exchange improves liquidity by using different bid and ask tick sizes.
problem Improving liquidity quality in financial markets.
method Model with uncertainty zones to analyze bid and ask side-specific tick sizes.
result Suitable side-specific tick sizes enhance liquidity provision.
This paper improves capital efficiency in AMM protocols with leverage.
problem Improving capital efficiency in Automated Market Makers (AMM).
method Formalizes leveraged liquidity provisioning, defines margin level, assets, and debt.
result Leveraged liquidity positions are safe and possess desirable properties.
Enhances crypto-asset AMM with deep learning for better liquidity and efficiency.
problem Reduced slippage and improved liquidity in decentralized finance.
method Deep reinforcement learning for predicting market equilibrium and optimizing liquidity.
result Improved capital efficiency and reduced slippage for crypto-asset traders.
Machine Learning (ML) and Deep Learning (DL) innovations are being introduced at such a rapid pace that model owners and evaluators are hard-pressed analyzing and studying them. This is exacerbated by the complicated procedures for evaluation. The lack of standard systems and efficient techniques for specifying and pro…
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.
Replicates and improves Uniswap V3 model using DDQN and Mamba.
problem Improving liquidity provision in Uniswap V3 with reinforcement learning.
method Combines DDQN with Mamba and introduces a new reward function.
result Shows stronger theoretical support and better performance than original model.