arXiv research

This study examines how supplier and customer networks affect credit spreads.

Supply uncertainty leads to inefficient supply chain network formation.

Supply chain resilience depends on balancing competition and self-interest.

Paper proposes machine learning for pricing 3D printing services in marketplaces.

Model optimizes mediation for insolvent suppliers by finding an optimal contract solution.

Supplier learns to price contracts against a learning retailer.

Suppliers (including companies and individual prosumers) may wish to protect their private information when selling items they have in stock. A market is envisaged where private information can be protected through the use of differential privacy and option contracts, while privacy-aware suppliers deliver their stock a…

Study characterizes community structure in Japanese production network.

Approach for assessing supply chain cyber risks using expert judgment and forecasting.

Study on supply chain networks using wire transfers in Brazil.

Modeling supply chain disruptions from climate hazards with adaptive firms.

Blockchain markets with paid-priority trading can lead to biased prices and reduced liquidity.

We study equilibrium in hedonic markets, when consumers and suppliers have reservation utilities, and the utility functions are separable with respect to price. There is one indivisible good, which comes in different qualities; each consumer buys 0 or 1 unit, and each supplier sells 0 or 1 unit. Consumer types, supplie…

Study develops smart contract framework for procurement under demand variability.

PriceAggregator optimizes hotel price fetching to increase Agoda's bookings.

Blockchain and AI improve invoice financing for supply chains.

We investigate the structure of global inter-firm linkages using a dataset that contains information on business partners for about 400,000 firms worldwide, including all the firms listed on the major stock exchanges. Among the firms, we examine three networks, which are based on customer-supplier, licensee-licensor, a…

This paper explores using graph neural networks for stock market predictions, improving accuracy with richer data.

Modeling market impacts leads to perfect hedging strategies.

We propose a novel approach and an empirical procedure to test direct contagion of growth rate in a trade credit network of firms. Our hypotheses are that the use of trade credit contributes to contagion (from many customers to a single supplier - "many to one" contagion) and amplification (through their interaction wi…

Paper introduces PHI to identify structurally distinct payment patterns in UK municipal procurement.

Study a market with uncertain informed traders, finding price impact depends on both asset value and informed trader count distribution.

Network models assume unrealistic idiosyncratic risk, which can be mitigated by allowing for correlated shocks.

Although standard economics textbooks are seldom interested in production networks, modern economies are more and more based upon suppliers/customers interactions. One can consider entire sectors of the economy as generalised supply chains. We will take this view in the present paper and study under which conditions lo…

The recently announced Energy Union by the European Commission is the most recent step in a series of developments aiming at integrating the EU's gas markets to increase social welfare (SW) and security of gas supply. Based on a spatial partial equilibrium model, we analyze the changes in consumption, prices, and SW up…

Theory for algebraic data on categories via concentration structures.

This paper shows how we can build a model for transactions when goods are given away in the expectation of a later settlement. In settings where people keep track of their social accounts we are able to redefine concepts like account balance, yield curve and the law of diminishing returns. The model provides us with a …

Paper addresses concentration of distances for fractional quasi p-norms, identifying conditions for concentration and anti-concentration.

Study Finsler metric measure manifolds' concentration properties.

Eigenfunctions on manifolds concentrate near nodal sets.

Modeling trading behavior with information signals and limit order books, showing market impact and equilibrium properties.

New method improves missing mass concentration bounds.

The paper studies concentration of measure on manifolds with boundary, focusing on $1$-Lipschitz functions.

Surfaces in 3-manifolds concentrate at curvature critical points.

Sharp concentration bounds for i.i.d. variables.

We survey recent results related to the concentration of eigenfunctions. We also prove some new results concerning ball-concentration, as well as showing that eigenfunctions saturating lower bounds for $L^1$-norms must also, in a measure theoretical sense, have extreme concentration near a geodesic.

A new model CDTM improves text classification by concentrating document topics.

Simplified proof of Gaussian concentration inequality using covariance.

Model predicts fine dust concentrations in Seoul using LSTM.

Study provides bounds for estimating intrinsic dimension using Gaussian kernels.

Study on inequalities for multinomial variables.

Developed concentrated liquidity in n-dimensional AMM with polar coordinates in Rust.

Paper analyzes minimal investment risk with budget and concentration constraints.

Study on volume of tubes and concentration in Riemannian geometry.

Optimal online learning for joint pricing and resource allocation.

This study assesses risk concentration in MDB portfolios using Monte Carlo simulations.

A limit point p of a discrete group of Mobius transformations acting on S^n is called a concentration point if for any sufficiently small connected open neighborhood U of p, the set of translates of U contains a local basis for the topology of S^n at p. For the case of Fuchsian groups (n = 1), every concentration point…

New approach to concentration inequalities for unbounded state space dynamical systems.